Conference Agenda

Passive systems (PSs), both for reactor driving system and safety features, are currently significantly discussed because they will surely take an important role in the coming reactor designs including small modular reactors (SMRs), irrespective of water-cooled or non-water-cooled ones. Great many kinds of developmental effort are underway including the confirmation of their performances especially in the reactor safety aspects. While PSs should have many favorable points, their stability and thus reliability have been discussed with some concerns because of their small driving force especially in the coolant injection capability to maintain integrity of nuclear fuels under any kinds of accidents. This paper revisits two past efforts: ROSA-AP600 and passive containment cooling system (PCCS) horizontal heat exchanger for advanced boiling water reactor (ABWR) containment vessel under severe accident conditions, thus reactor system response and component performances of PSs, to consider key thermal-hydraulic capabilities assessed to assure the reliability in such a practical use of PSs.

The forensic analysis of Fukushima Daiichi have underscored the significant role played by Units 1-3 suppression pools in attenuating Source Term to the environment. However, such a role is not limited to Boiling Water Reactors (BWR), but extend to accident scenarios in Pressurized Water Reactors (PWR), like Steam Generator Tube Ruptures (SGTR). The fission products trapping in water ponds, also referred to as pool scrubbing, was profusely investigated in the 80’s of last century and, eventually, encapsulated in stand-alone codes, like SPARC90, which formulation was embedded later in MELCOR. Despite the investigation effort, which was revived by the Japanese accidents, the diversity of accident scenarios involving pool scrubbing and the extraordinary complexity of its multi-physics nature, have made it hard to build a complete and sound database. As a consequence, modelling are still open for further development, testing alternate approaches and, awareness of uncertainties affecting pool scrubbing estimates.

This keynote lecture reviews the status of knowledge, pinpoints gaps necessary to be addressed and proposes a path to do it.

The validation of decay heat removal (DHR) systems and the characterization of thermal hydraulic phenomena in the plena of the liquid metal-cooled, pool-type research reactor MYRRHA, under design at SCK CEN, the Belgian Nuclear Research Centre, is accomplished by experiments and numerical investigations. For this purpose, the E-SCAPE facility at SCK CEN is a thermal hydraulic 1/6-scale 3-D model of the primary system of MYRRHA, with an electrical core simulator, and cooled with Lead Bismuth Eutectic (LBE). Its scaling is based on the preservation of the overall system behavior and the reproduction of the major thermal hydraulic phenomena under DHR conditions. Results from steady-state and transient thermal hydraulic experiments in forced and natural circulation demonstrate that in loss of flow conditions, a natural circulation flow establishes, driven by buoyancy, that can remove the core power, with fuel cladding and reactor structure temperatures that are within safety limits. In natural circulation, thermal stratification occurs in the upper plenum of the facility. System Thermal Hydraulics (STH), Computational Fluid Dynamics (CFD) and coupled STH/CFD models of E-SCAPE have been built in different phases of its lifecycle for scaling, design, pre-test and post-test analyses. The results of post-test simulations are compared with experimental data, showing that the phenomena driving the flow are accurately represented in both the numerical models and the experimental facility. This paves the way for the validation of numerical tools used in the safety analyses of MYRRHA

Helical Cruciform Fuel (HCF) has a cruciform shape with helically twisted surface, which provides about 35% larger heat transfer area compared to standard cylindrical fuel. From a thermal-hydraulic perspective, this geometry results in a lower wall average heat flux leading to a power uprate potential. This study investigates two key thermal hydraulic-related phenomena for the HCF rods using Computational Fluid Dynamics (CFD) simulation: Departure from Nucleate Boiling (DNB) and fluid-elastic instability. The NuScale-like Small Modular Reactor (SMR) with a low mass low rate is considered as a reference plant design.

First, a numerical boiling test is conducted for a hot fuel pin using a Eulerian-based two-fluid approach, using the CASL boiling models to estimate the Critical Heat Flux (CHF) and Minimum Departure from Nucleate Boiling Ratio (MDNBR). Additionally, post-CHF cladding surface temperature is estimated to provide boundary conditions for a future fuel performance analyses. The performance of HCF is compared with that of standard cylindrical fuel under the same conditions to assess its relative advantages.

Furthermore, a Fluid-Structure Interaction (FSI) simulation is performed to estimate the Fluid-elastic Instability Margin (FIM) in the HCF geometry through vibration analysis. An unsteady simulation is carried out for a 2x2 lattice using the STRUCT-𝜀 turbulence model, which can capture vibrations without the need for LES-level mesh refinement. By using the vibration frequency and damping ratio—computed using the displacement data from the simulation —the FIM and fretting wear rate are estimated.

A global research effort is underway to develop Small Modular Reactors (SMRs) with diverse applications beyond just providing baseload power, while simultaneously enhancing safety. One design of interest is the NuScale concept reactor design, which utilizes natural circulation driven by temperature differences in the primary system, allowing for operation without pumps. This design has attention in worldwide for its high safety profile. However, a significant limitation of the natural circulation reactor concept is the lack of extensive operational experience. To overcome limitations, it is crucial to construct and operating scaled experimental facilities that can simulate natural circulation. In this study, the URI-SMR (UNIST Reactor Innovation-SMR), a scaled-down experimental facility based on the NuScale concept design, was employed to evaluate the natural circulation performance. The URI-SMR is well-suited for natural circulation study because its primary system is constructed of acrylic, which enables simultaneous performance evaluation and visual observation of the natural circulation flow. Through the URI-SMR, steady state experiments at various power levels were conducted, and the feasibility of load following operation being considered for SMR was also evaluated. In addition, the comparison between experimental results and system code analyses enhanced the reliability of system code modeling and established a foundation for the analysis of transient behaviors that are challenging to try in experiment. This research validates the natural circulation operational performance of integrated SMR designs like NuScale concept and extend confidence in next-generation SMR options, such as load-following capabilities.

Based on large PWR and SMART SMR (Small Modular Reactor) technologies, the innovative SMR,referred to as the i-SMR, is under development. The i-SMR incorporates an in-vessel helical coil steam generator.
Boiling in helical tubes differs from straight tubes due to the interplay of centrifugal and buoyancy
forces, which influence pressure drop and flow regimes. Heat transfer models used in safety analysis codes are largely based on straight-tube boiling phenomena, offering limited applicability to helical tube heat transfer predictions. Furthermore, flow instabilities under extreme conditions may compromise the structural integrity of pipes due to vibration, affecting flow stability, flow rate, and heat transfer performance, thereby potentially impacting system safety. To optimize performance and validate heat transfer in helical coil steam generators under conditions similar to the i-SMR, heat transfer tests are being conducted, and a test database is being developed. Additionally, to ensure the safety of integral reactor designs like the i-SMR, ongoing assessments aim to refine and evaluate heat transfer and pressure drop models specific to helical coil steam generators, which significantly differ in geometry and heat transfer characteristics compared to large-scale nuclear steam generators.
This study serves as an initial step in validating the heat transfer performance of the helical coil steam generators for the i-SMR. It focuses on evaluating existing heat transfer models, based on prior research, to determine their applicability to helical coil steam generators.

The passive auxiliary feedwater system (PAFS) is one of the advanced safety systems in the innovative Small Modular Reactor (i-SMR). The PAFS has a heat exchanger tube bundle submerged in the emergency cooling tank (ECT). In the PAFS, the heat is removed by the condensation in the heat exchanger tube having 3 degree inclination. To know the heat removal performance of the PAFS, the heat transfer rate for the condensation in tube should be accurately predicted. In this study, to evaluate the predictability of SPACE code for the condensation in the PAFS, the SPACE code analyses were conducted for the PASCAL and PICON experiments. For the PASCAL experiments which simulated a PAFS heat exchanger tube and the PICON experiments which simulated the condensation in the nearly horizontal tube, the heat transfer coefficient and flow regime were compared between the experimental results and the SPACE code analysis results. The SPACE code predicted well the condensation heat transfer rate in the PASCAL and PICON experiments when the condensation model developed by Ahn et al. (2014) was applied.

Supercritical carbon dioxide (sCO₂), nitrogen (N₂), and helium (He) Brayton cycles are promising power conversion systems for advanced nuclear reactors, including molten salt reactors (MSRs), sodium-cooled fast reactors (SFRs), and gas-cooled reactors (GCRs). Recuperators play a crucial role in enhancing thermal efficiency in these cycles but require volume minimization due to their high thermal duty and large size. This study investigates the thermal-hydraulic performance of straight-channel recuperators for sCO₂, N₂, and He Brayton cycles. Gas-to-gas experiments were conducted using printed circuit heat exchangers (PCHEs), covering a wide range of Reynolds (Re) numbers from laminar to turbulent regimes to accommodate various design conditions. Experimental results were analyzed based on Re numbers, and existing thermal-hydraulic correlations were evaluated for their applicability in recuperator design. In laminar regime, the developing flow effects are important for heat transfer and pressure drops. In transition and turbulent regimes, existing correlations have enough predicting performances. With the evaluated correlations, a validated one-dimensional (1-D) in-house PCHE design code was employed to determine the optimal recuperator volume while satisfying target effectiveness and pressure drop constraints. The optimal design results, derived under fixed thermal duty and pressure drop conditions, were examined across different Brayton cycle working fluids. The findings provide insights into the thermal-hydraulic performance of straight PCHE channels across a broad Re number range and offer valuable design-level guidance for recuperators in gas Brayton cycles. It is worth noting that these results contribute to improving the efficiency and feasibility of compact recuperators for advanced nuclear power systems.

Due to its high latent heat, pool boiling exhibits excellent heat dissipation capability and is widely used in many industries such as electronic devices, steam generators, nuclear reactors, etc. This paper experimentally investigates the heat transfer enhancement effect of bi-conductive surfaces in pool boiling and reveals its underlying mechanism.Because of the enormous difference in conductivity, the heat transferred through the low-conductive epoxy can be ignored, and boiling only occurs on the high-conductive copper surface. This provides a method that can create specifically appointed spatial surface temperature variations and induce ordered liquid and vapor paths by changing the pattern of epoxy.This paper designs two types of epoxy patterns with a fixed copper area ratio of 60%, including reticular epoxy samples and more complex reticular epoxy with squares in the middle samples. At the same time, the number and width of stripes in the reticular epoxy are changed in each category. According to the result, almost all reticular epoxy samples enhance the CHF compared with bare copper. With the increase in the number of stripes in the reticular epoxy, the CHF displays the tendency to rise at first and decline in the end, reaching the peak of 77.2% CHF increase. Under the same number of stripes, reticular epoxy with squares in the middle samples have higher HTC and CHF compared with reticular epoxy samples because of superior wetting effect of epoxy. The results also suggest that overly narrow epoxy can lead to insufficient wetting effect and trigger CHF in advance.

During flow boiling, two different regimes are observed namely nucleate boiling and convective flow boiling. Nucleate boiling is dominant at high heat fluxes where bubbles produced at the wall are attributed the control of the heat transfer. Convective flow boiling is dominant at low heat fluxes and the heat transfer coefficient is observed to be directly dependent on the mass flux and the thermodynamic quality. The transition between to these two regimes has motivated vast research to determine if the transition is triggered sharply or there is a region where both mechanisms are presented. In this work, we study the nucleate flow boiling to convective flow boiling transition experimentally in a horizontal heated pipe.

Accurate prediction of heat flux is essential for various industrial and scientific applications, particularly in heat transfer and thermal management systems. Traditional methods for heat flux estimation often rely on complex physical modeling and intrusive sensor-based measurements, limiting their applicability in dynamic boiling conditions. Recent advancements in deep learning, particularly Convolutional Neural Networks (CNNs), have enabled non-intrusive heat flux prediction directly from boiling images. In this paper, we propose a multi-branch convolutional neural network architecture for heat flux prediction from boiling images. The key innovation lies in the introduction of multi-branch convolutional components (MB-Conv), which integrate multiple convolutional branches with varying kernel sizes to extract a comprehensive set of features.

The proposed model leverages a multi-branch architecture to enhance its representational power, allowing it to effectively learn from a diverse range of spatial features that are critical in predicting heat flux in boiling systems. Experimental results demonstrate that our model significantly improves prediction accuracy compared to the traditional single-path convolutional neural model. Moreover, the proposed multi-branch architecture outperforms several well-established CNN models, such as AlexNet, VGG, ResNet, DenseNet and EfficientNet in terms of predictive performance, highlighting the effectiveness of our approach in capturing the complex thermal phenomena present in boiling images. The ability to predict heat flux from boiling images opens up new possibilities for optimizing system performance and ensuring safety in thermal systems.

Enhancing the heat transfer is of interest for a wide spectrum of industries to achieve higher thermal efficiency. During subcooled flow boiling, liquid-to-vapour phase change causes high heat transfer rates, although the coolant bulk temperature is below its saturation temperature. When the required wall superheat is developed, vapour bubbles form over the heated surface marking the onset of nucleate boiling. When a bubble sufficiently grows in size, it departs from the heated surface, and its departure size and frequency dictate the enhancement of heat transfer rates. Formation of larger bubbles near the heated surface may result in their coalescence forming a local dry patch which may eventually lead to Critical Heat Flux (CHF). Although there are numerous correlations available in the literature, to estimate the bubble departure size, most of the correlations perform well at high pressure conditions. To this end, it is important to study the bubble departure size and its influence on the subcooled flow boiling characteristics at low pressure conditions. In the present study, Eulerian-Eulerian multiphase flow (EEMF) model is employed to simulate the subcooled flow boiling conditions. Instead of using an existing empirical correlation, a force balance model is developed to predict the departure size and validated against the experimental data at low pressure conditions. Based on this model, a correlation for departure diameter is developed which is coupled with the EEMF model framework. The developed correlation is found to be more accurately capturing the local vapour volume-fraction profiles compared to the existing correlations.

We employ three fast and synchronized optical techniques (white-light interferometry, infra-red thermography, shadowgraphy) to study the near-wall phenomena during the growth of a single bubble in saturated pool boiling of water at atmospheric pressure. Our focus is on the impact of applied heating on bubble growth dynamics, as well as the near-wall features: dry spot spreading, the liquid thin film (microlayer) that can form between the heater and the liquidvapor interface of the bubble and the interfacial thermal resistance. We found that varying the applied heating power does not significantly impact the bubble macroscopic and near-wall features. It is explained by large heat capacity of the heater. The only affected parameter is the waiting time, which decreases with the applied heating power. The interfacial thermal resistance shows no dependence with heat flux, and increases monotonously over time due to the progressive accumulation of impurities at the interface. We show that the triple contact line dynamics depends on the wall superheating at the contact line.

In 2024, a novel separate-effect-test (SET) facility for two-phase critical (TPCF) flow studies was commissioned at LUT University’s Nuclear Engineering Laboratory. CRiticAl Flow Test facility (CRAFTY) utilizes a straight long tube for discharging subcooled water from an upstream pressure vessel to atmospheric pressure. Prior, a plethora of two-phase critical flow experiments have been carried out in the world. A preliminary literary survey found out that there is a lack of two-phase critical flow experiments utilizing very long length-to-diameter (L/D) ratio tubes (>200). In a postulated primary-to-secondary leak in a PWR, the L/D ratio of the tube can be upwards from 1000 depending on the steam generator design.

In CRAFTY, the L/D ratio and tube diameter can be conveniently changed with interchangeable discharge tubes. A discharge tube with an inner diameter of 13 mm and closely resembling the VVER-440 steam generator tube (inner diameter of 13.2 mm) was utilized in the tests conducted in 2024. The length-to-diameter ratio of the tube was 350 which is close to the half of an average length of the VVER-440 steam generator tube.

Altogether 12 discharge experiments with subcooling varying from 5 °C to 60 °C and upstream pressure from 5 MPa to 8 MPa were conducted. The nominal pressure difference between the primary and secondary circuit in VVER-440 is around 7 MPa.

This paper discusses the experiment results, introduces a simplified critical mass flux model utilizing a modified Jakob number, and presents some simulation results obtained with a system thermal hydraulic code.

In order to realistically simulate the thermal-hydraulic behavior and accident progression during a multiple failure accident, an integral effect test was performed to simulate an SBLOCA (Small break loss-of-coolant accident) with failure of safety injection in the ATLAS-CUBE test facility, which can simulate the thermal hydraulic interaction between the RCS (Reactor coolant system) and the containment. With the break at the cold leg, failure of the safety injection was assumed, whereas an accident management (AM) action was implemented to initiate the safety injection pumps (SIP). The test result confirmed the sufficient grace time during the multiple failure scenarios, including safety injection failure and loop seal clearing phenomena. The compartments acted as passive thermal sinks, effectively maintaining containment pressure below the set-point of spray injection, and ensuring long-term cooling without spray system operation. The test data in the ATLAS-CUBE facility was utilized to assess SPACE and CAP codes. The linked calculation of both codes was performed with considering the M/E (Mass and energy) transport and the P/T (Pressure and temperature) build-up in the containment. From comparing the test and calculation result, it was found that a higher pressure and temperature of the containment was predicted in the multi-volume of the containment in the CAP code calculation. The uniform temperature inside the containment in the single-volume case could overestimate the heat transfer at the passive heat sink and it affected a slower increase of the pressure and temperature of the containment.

Natural circulation imbalance or interruption (NCI) phenomena observed in C3.1 test of OECD-ATLAS3 project will be described in the present paper. When the primary forced flow is lost, the reactor core decay heat is generally removed through natural circulation (NC) convection: the flow is driven by the coolant density differences in the steam generators (SGs) as heat sink and in the reactor pressure vessel (RPV) as heat source.
During an asymmetric cooldown conditions between two steam generators, especially for the case of APR1400, Natural circulation imbalance between the two loops might occur. Moreover, natural circulation imbalance trend can be resulted in NCI phenomenon that means a complete loss of natural circulation flow in a certain loop (or loops) of the primary system. This NCI scenario may prevent the RCS to reach the entry conditions for the residual heat removal system (RHRS). Therefore, an understanding on the NCU is important.
C3.1 test consists of two separated tests named by Run1 and Run2 to compare an effect of primary coolant inventory. These two runs were performed on December 4th and 6th, 2023, respectively. Main objectives of the test were to investigate natural circulation imbalance and NCI phenomenon induced from an asymmetric cooldown transient operation, and to investigate an effect of related parameters such as the decay core power rate, injection flow rate of auxiliary feed water to unaffected SG, and discharge flow rate of ADV. In the paper, test results were compared with post-test calculation results.

Ensuring the safety of nuclear power plants is paramount, Integral Effect Test (IET) facilities have been utilized to verify the performance of reference reactors and assess the application of newly proposed technologies. Before the construction of IET facilities, System behavior analysis should be conducted to ensure that IET facilities can adequately represent reference reactors. In this study, Platform for Advanced TRaining and Integrated OPR1000 Thermal-hydraulic Test (PATRIOT), using refrigerant as the working fluid, was demonstrated to exhibit behavior similar to a reference reactor under station blackout (SBO) conditions through the utilization of system analysis codes. The PATRIOT, developed at UNIST based on the OPR-1000 design, operates with R134a refrigerant at 26.5 bar on the primary side and 13.5 bar on the secondary side. The MARS-KS code was used to analyze SBO behavior, and the R134a properties were generated within compatible pressure ranges for system analysis. The results were compared to the ATLAS, an IET facility developed by KAERI for APR-1400, which has similar design characteristics to OPR-1000. Compared to ATLAS, PATRIOT exhibited less pressure reduction and faster onset of dry-out phenomena, attributed to the lower latent heat and heat transfer of R134a. Despite these differences, the behavior of PATRIOT was similar to ATLAS, which demonstrated the feasibility of utilizing R134a in IET facilities. Therefore, It is confirmed that PATRIOT can simulate the reference reactor. Furthermore, considering the necessity of refrigerants for IET facilities to scale down, this study could contribute to the development and validation of refrigerant-based IET facilities.

In September 2024, SMART100 with a Passive Safety Injection System and Containment Pressure and Radioactivity Suppression System obtained standard design approval from the Korean regulatory agency. SMART-ITL built to evaluate the operating performance and safety of SMART100 was equipped with all passive safety systems except CPRSS. It is designed to simulate most accidents that can occur in SMART100, including transient accidents such as CLOF, SGTR, and FLB as well as SBLOCA. The role of the PSIS during SBLOCA is to supply coolant to the reactor for 72 hours without operator intervention, and its injection performance by gravity head was verified using SMART-ITL. The Passive Residual Heat Removal System operated in almost all accidents occurring in SMART100 is a natural circulation cooling system in which the condensation heat exchanger connected to the secondary side of the steam generator is contained in the Emergency Cooling Tank, and removes the core residual heat absorbed in the steam generator to the ECT. The heat removal performance of the PRHRS was verified through various types of accident simulation tests. This paper deals with the performance of the PSIS and the PRHRS confirmed from the thermal-hydraulic test results using SMART-ITL. In all individual accidents where the passive safety systems were activated, they performed sufficiently to bring the reactor coolant system to a safe shutdown.

Swiss NPPs undergo a Periodic Safety Review (PSR) every ten years. In this framework, the deterministic safety analyses must be updated following the requirements of the regulatory body ENSI. In September 2018 ENSI put a revision of the guideline for technical safety analyses (ENSI-A01) into effect. As a result, new events must be analyzed at DBA level (safety level 3) and BDBA level (safety level 4a). Besides, the fulfilment of the safety goals (acceptance criteria) must be proved also for operating conditions other than full power (such as zero-power or start and shutting-down conditions).

In preparation of the next PSR, the Gösgen NPP, a 3-Loop PWR; is working in tight collaboration with its vendor Framatome GmbH to evaluate and update the existing accident analyses. The present paper reports on the main findings from the new safety analyses, which are being carried out with the proprietary system code S-RELAP5. Attention is given on the update of the plant operational procedures, which are optimized for increasing safety margins and reducing the radiological impact of the accident.

A SBLOCA (break of a measuring line connected to main coolant line or pressurizer) is analyzed implementing a new fast secondary-side cooldown, which allows the stable shutdown without core uncovering (DBA). Operational procedures have been optimized in case of SGTR, preventing the interruption of natural circulation in the affected loop (DBA). New analyses have been performed for ATWS sequences (BDBA). The importance of operator measures is highlighted in the accident mitigation to reach the cold-shutdown state.

Helical coil steam generators play a critical role in the operation of small modular reactors, primarily due to their superior heat transfer capabilities. However, the intricate design of these systems makes it challenging to fully understand the boiling phenomena occurring within the helical coil tube, which is crucial for reactor safety. During boiling, it is common to observe oscillatory flows, which can have a substantial impact on the operating conditions of the reactor and introduce potential safety risks. While thermal-hydraulic system codes have been widely used over the past decades, they often fall short of accurately capturing reverse flows, staggered grid issues, and simplistic spatial discretization. These limitations might result in discrepancies between experimental data and code predictions.

In response to these challenges, a new system code (in-house code for helical coil steam generator) is currently under development, designed to bridge the gap between theory and experimental observation. The goal of this enhanced approach is to provide a more accurate representation of the oscillatory movements induced by two-phase flow within the helical coil tube. By improving the depiction of complex bubble dynamics, this new system code aims to advance the understanding of these oscillations, ultimately contributing to more effective reactor safety analysis and providing a solid foundation for the validation of reactor designs.

The NOUS is a Python™ based software which is capable of setting the initial plant data for the VVER-1200 type reactor for coupled thermo-hydraulic and neutron kinetic (TH-NK) calculation. The program can define the thermo-hydraulic (TH) parameters both for the primary and secondary circuit and can vary the spatial discretization.

The neutron kinetic coupling can be selected between point kinetic, 3D Fuel Assembly (FA) or even pin-wise resolution.

A further option is that the user can choose the availability of the safety and non-safety system trains during an initiating event and the corresponding safety functions.

The software can be used for testing of maneuvering modes, for deterministic safety analysis and for functionality analysis, as well.

Airborne radioactive materials are inevitably released through stacks during nuclear power plant operation. Accurate monitoring is crucial to assess environmental impact and ensure regulatory compliance, as it depends on samples that accurately represent stack radioactivity.

According to the ISO 2889-2023 standard, the study simulated the flow field of a 5:1 scaled model of a stack. The diameter and the height of the scaled model are of 0.6 meters and 12 meters. The gas carrying aerosols in the scaled stack model enters through a horizontal mixing pipeline, with the Reynolds number ranges from 400,000 to 700,000 in the vertical main stack. The Standard k-epsilon Model was employed to calculate the flow field, while the Species Transport Model was used to simulate the mixing processes of tracer gas and air. After achieving convergence, the Discrete Phase Model was employed to compute the trajectories of aerosol particles, thereby obtaining the characteristics of the motion and distribution.

By analyzing the airflow streamlines, aerosol particle trajectories and contour plots at different sampling sections, the study reveals the flow characteristics, the concentration distribution patterns of tracer gases and aerosol particles. The results were further processed to evaluate whether the sampling sections at different elevations meet the well-mixed criteria based on five parameters: average resultant angle, velocity variation coefficient, maximum tracer gas concentration deviation, tracer gas concentration variation coefficient and aerosol particle concentration variation coefficient. The findings of this study serve as a reference for selecting sampling sections and evaluate the mixing performance of the model.

Tritium extraction is a universal challenge in advancing all types of nuclear power: fission plants must dispose of, and fusion plants must fabricate fuel from it. Gas-liquid contactors (GLCs) which leverage two-phase dynamic mixing to supercharge the mass transfer of tritium are an untapped concept in the field. In theory GLCs should be capable of achieving more surface area than static liquid-solid interface extractors with sufficiently small & many bubbles, but bubble coalescence has been a major challenge. By building on Volume of Fluid (VoF) multiphase simulation support in the computational fluid dynamics tool OpenFOAM, we developed an extensible Continuum Species Transport (CST) solver for the loosely coupled concentration field of a dilute miscible species. This establishes a new framework for the design and pre-experimental evaluation of novel GLC concepts in mass transfer applications for molten salt. To demonstrate the utility of our new solver, a simple evaluation of a bubble column with one large Ar inlet against four small Ar inlets is performed, showing a straightforward correlation between bubble size and tritium extraction efficiency.

Molten salt reactors (MSRs) have gained much interest in the nuclear community over the past few years, and efforts are currently being made in the design and deployment of a molten salt research reactor (MSRR) at Abilene Christian University. Multiple experimental salt loops are being designed to test various aspects of MSRs and understand the fluid dynamics of molten salts at a higher level. One such experiment is a bubble flow salt loop built at Texas A&M. High fidelity models of this experiment have been constructed, utilizing the computational fluid dynamics (CFD) modules of the MOOSE software. These CFD models, being at a high fidelity, may provide important information and a more wholistic view of the mechanics of molten salts, and may be included as a digital twin (DT) component in the experimental loop, as well as provide useful information to the MSRR. However, these CFD models require computationally expensive runs to provide reasonable and usable data. To combat this, a reduced order model (ROM) algorithm will be developed for these CFD models, solving these high fidelity and high dimensional problems in a significantly lower dimensional latent space, reducing cost with acceptable losses in accuracy. For these models, various ROM algorithms are created, using methods such as proper orthogonal decomposition (POD), neural networks (NN), and convolutional neural networks (CNN). These algorithms are then tested in an offline mode, comparing the forward propagation of the lower dimensional problem against the propagation of the full dimensional model.

The Stable Salt Reactor (SSR) integrates features of molten salt reactor technology with conventional light water reactor fuel assembly designs to achieve enhanced safety and economic benefits. Utilizing a fast reactor configuration, the SSR employs recycled nuclear waste as fuel, contained within salt-filled fuel pins submerged in a liquid salt coolant. Effective heat transfer between the molten fuel salt and coolant salt is critical to the reactor's core safety and operational reliability.

This study investigates conjugate heat transfer (CHT) processes in the SSR's narrow salt-filled fuel pins using the high-fidelity spectral element computational fluid dynamics (CFD) code, NekRS. The analysis encompasses internal natural convection within the molten fuel salt and external forced convection in the liquid salt coolant under both normal and transient conditions. Parametric studies are conducted to assess the influence of reactor power and coolant flow rates on heat transfer performance. The resulting data are leveraged to develop and validate heat transfer models for integration into the SAM system code, facilitating efficient transient safety analyses. The findings of this work refine safety system models, enhance the predictive accuracy of SSR core designs, and quantify uncertainties in molten salt CHT simulations. This study highlights the critical role of advanced CFD technologies in expediting the engineering design and licensing of next-generation nuclear reactors like the SSR.

Molten Salt Reactor (MSR) is currently one of the most promising Generation IV reactors, actively being developed internationally due to its high economic efficiency and safety. While evaluating the economic feasibility of developing MSR is important, assessment of various accident scenarios is also required for safety evaluation. One of the most anticipated scenarios in MSR is a salt spill accident caused by the crack or rupture of reactor pipes and the reactor vessel. In such cases, it is necessary to effectively cool the spilled molten salt and contain it within the desired location such as drain tank. To design an efficient molten salt transport structure, a detailed analysis of the molten salt behavior is essential. Furthermore, there is a possibility of releasing fission products into the atmosphere in the form of aerosols from the molten salt, for which boundary conditions can be provided. Lagrangian-based Computational Fluid Dynamics (CFD) calculations are considered a more advantageous numerical method for analyzing solidification behavior compared to Eulerian CFD methods. This is due to its meshless analysis characteristics, which allow free changes of boundaries between fluid and wall according to phase changes. In this study, the Moving Particle Semi-implicit (MPS) method was used to analyze salt spill behavior in MSR. To accurately simulate behavior accompanied by solidification, a model was developed to account for heat transfer and wall adhesion based on phase changes. A comparative analysis was conducted with results from other numerical methods, including Eulerian-based analysis.

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation.

Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed.

This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

An Annular Linear Induction Pump (ALIP) was designed for driving Lead Bismuth Eutectic (LBE). The basic parameters of the ALIP were calculated by the multi-physics coupling software COMSOL. The ALIP have 4 pole pairs, a frequency of 50 Hz, an input line current ranging from 0 to 80 A, and a corresponding output head ranging from 0 to 500 kPa, with a flow rate of 0 to 10m³/h. Experiments were conducted within the current range from 28 to 52A, the results showed that the experimental values matched well with the calculated values. Experiments on the output head of the ALIP was conducted with LBE at temperatures of 250, 300, and 350℃. The results showed that the output head of the ALIP varied little under the same electromagnetic parameters. This is due to the small change in the resistivity of the LBE with temperature, which is significantly different from sodium. The head curve of the ALIP was tested at a LBE temperature of 300℃ by adjusting the input electromagnetic parameters. The results indicate that the output head and LBE flow rate of the ALIP increase with the increase of input current, voltage, and power. However, under the same input electromagnetic parameters, the output head of the ALIP decreases as the flow rate increases.

The development of pool-type reactor MYRRHA, utilizing heavy liquid metal coolant necessitates primary pumps with extended massive shafts supported below the coolant free-surface level. Hydrostatic bearings are the most suitable choice for these specific conditions. However, conventional calculation methods for hydrostatic bearings are inadequate for the unique operational parameters presented by this application. This study focuses on the computational fluid dynamics (CFD) analysis and optimization of hydrostatic bearing designs for primary pumps in MYRRHA. Three bearing design candidates with different numbers of pockets were initially evaluated using CFD simulations on a scaled-down test model of the primary pump. The most promising design underwent iterative refinement to meet specific performance requirements, including pressure drop, load capacity, pressure ratio, and frictional torque. A comprehensive parametric analysis was conducted on the optimized design to characterize its performance across various operational scenarios, including the study of the influence of rotational speed and eccentricity. The CFD model developed for this analysis incorporated mesh optimization and turbulence modelling, simulating heavy liquid metal flows in the restrictors, the pockets, and the narrow gap of the hydrostatic bearing. The outcome of this research is a hydrostatic bearing design that satisfies all specified requirements for use in the scaled-down test model of the primary pump of MYRRHA. The CFD modelling approach provides a robust and reliable framework for future design and optimization efforts in this field, contributing to the advancement of primary pump hydrostatic bearing technology in heavy liquid metal-cooled reactors.

Amongst Generation IV reactor designs, liquid metal-cooled reactors boast high power density owing to the high thermal conductivity of metals. The thermo-hydraulic phenomena that occur in the reactor pool in different scenarios (steady operation, accidents, non-critical transients, etc.) are a topic of great interest in the research community. One such reactor concept is MYRRHA, a flexible fast-spectrum research reactor cooled by lead-bismuth eutectic (LBE) under design at SCK CEN. To support the design of MYRRHA and provide data that gives insight into such phenomena and for numerical code validation, a 1/6th scale model called European SCAled Pool Experiment (E-SCAPE) was developed.

As part of the European project PASCAL, NRG aims to perform multi-scale simulations of E-SCAPE subjected to asymmetric accident scenarios of Heat Exchanger and Single Pump Failure coupling the in-house System Thermal Hydraulic (STH) code SPECTRA to the commercial Computational Fluid Dynamics (CFD) code STAR-CCM+ via the in-house coupling tool myMUSCLE: MultiphYsics MUltiscale Simulation CoupLing Environment.

In previous articles, the standalone as well as coupled models of E-SCAPE have been validated against a steady state isothermal scenario. In this article, the next step is taken by performing coupled calculations of the steady active operation at a mass flow rate of 93.2 kg/s and 80% power, i.e 73kW, that serves as the pre-accident state to the Heat Exchanger Failure scenario, and comparing to the standalone STH and experimental results. The calculations reveal stable solutions that are well in agreement with the standalone STH as well as the experimental results.

Lead(Pb) and lead bismuth(Pbbi) reactors are potential types of fourth generation reactors. Lead reactors have higher thermal efficiency and natural circulation capabilities. At present, there are almost no publicly reported experimental data on the heat transfer characteristics of liquid lead, especially the data under natural circulation mode. In this study, a pool-type natural circulation experimental platform was first designed, which includes a simulated core(simulated with 37 heating rods with a length of 1200mm, and P/D of 1.3), a hot pool, a cold pool, upper and lower channels, and four symmetrical lead-oil heat exchangers. During the experiment, liquid lead undergoes endothermic expansion in the simulated core and flows into the top lead-oil heat exchangers through a hot pool. After heat exchange, the liquid lead flows downwards along the cold pool into the bottom of the simulated core, completing natural circulation. The T/H characteristics of liquid lead at simulated core, hot pool, cold pool, etc. were analyzed and studied. At the same time, experimental modeling based on system code was also carried out, and the experiments were compared and verified with the code. The research results can provide support for the design of liquid lead pool-type natural circulation reactors.

System codes can efficiently handle system-level problems and obtain transient characteristics of whole system. However, they lack the ability to analyze the local flow and heat transfer characteristics of components. CFD codes have the ability to perform highly precise analysis of local components, but cannot analyze the whole system. Therefore, it is an important direction of current research that achieving the coupling calculation of system and CFD codes. To obtain the flow and heat transfer characteristics of the core and transient response of the lead-bismuth fast reactor, a coupling code between system code and CFD was developed. Through a data transferring platform based and explicit coupling method, the simulation of the primary loop of lead-bismuth fast reactor core was achieved. To verify the coupling code, system code and coupling code under the same operating conditions were performed. The flow rate and coolant temperature in the primary loop of the lead-bismuth fast reactor were compared. It was found that the coupling simulation results were consistent with the results of system code, indicating that the coupling code can accurately predict the flow and heat transfer characteristics and system response of the lead-bismuth fast reactor core, and verify the feasibility and rationality of the coupling method. This study provides a coupling method for the thermal hydraulic analysis of lead-bismuth fast reactors.

In this work, we compare human-developed and Artificial Intelligence (AI)-generated models for predicting Critical Heat Flux (CHF) in nuclear reactor safety analysis. This study harnesses AI and Machine Learning (ML) to develop predictive models that learn from experimental data, specifically using the extensive NRC CHF database. We compare human-developed models optimized via deep ensemble methods and Bayesian optimization with AI-agent-developed models using large language models (LLMs).

The human models use a Gaussian distribution approach for predictions, with uncertainty quantified through variance. Bayesian optimization refines hyperparameters such as learning rate and batch size, enhancing prediction accuracy measured by Root Mean Square Error (RMSE).

In contrast, an AI agent system, developed using a Large Language Model (LLM), autonomously created CHF predictive models with a neural network architecture. The LangChain suite facilitates system interactions, the execution of Python scripts, and task management through LangSmith and LangGraph, simulating a multi-agent system for an automated workflow that encompasses model development, training, and evaluation.

The performance comparison between the human and AI-developed models focuses on prediction accuracy, uncertainty quantification, and computational efficiency. The AI models demonstrated performance comparable to that of human-optimized models, showcasing their potential to automate nuclear safety analysis tasks.

This study highlights the promise of AI in enhancing nuclear reactor safety analysis. Future work should focus on integrating AI models with advanced simulation tools and expanding their application to broader safety analysis cases, including transients.

Accurate prediction of Critical Heat Flux (CHF) is crucial for the safe and efficient operation of nuclear reactors. Traditional CHF modeling methods often require extensive experimental data and are computationally expensive. In this work, we propose a novel approach to CHF prediction that combines active learning with Variational Inference (VI) in a Bayesian Feedforward Neural Network (BFNN) setting. By utilizing the uncertainty quantification inherent in Variational Inference, the most informative data points can be strategically chosen to incrementally train the model, thereby minimizing the computational cost as well as the data required for accurate predictions. VI is less expensive than other Bayesian inference methods, making it a feasible option for active learning with neural networks

BFNN begins with a small subset of training data and applies the reparameterization trick to approximate the posterior distribution of model weights. As new data is strategically selected based on uncertainty, the network updates its posterior distribution, improving accuracy while staying computationally efficient. This active learning framework prioritizes areas of high uncertainty, reducing data requirements and speeding up the learning process.

We evaluate our method on a CHF dataset, demonstrating substantial improvements in performance compared to traditional approaches. The framework is particularly suited for digital twins of nuclear reactors, where real-time updates and efficient learning from sparse data are essential. We aim to assess the performance using Mean Absolute Percentage Error (MAPE) and R² on a test set to show that our variational approach will achieve comparable accuracy and prediction quality at much lower data.

This study aims to enhance the prediction accuracy and expand the practical applicability of critical heat flux (CHF) calculations by integrating the thermal-hydraulic sub-channel analysis code COBRA-TF with machine learning techniques. A machine learning model was trained using the 2006 Groeneveld Lookup Tables released by the Nuclear Regulatory Commission (NRC), offering a comprehensive reference dataset for CHF prediction. Key input parameters required by the ML model include system pressure, mass flux of the working fluid, and critical quality, ensuring an accurate representation of thermal-hydraulic conditions. For COBRA-TF performance testing, 200 independent calculations were performed and assessed. The CHF values in these scenarios range from 400 to 4000 kW/m², providing a broad spectrum of conditions to validate the ML CHF model's performance. Comparative results show that, while all models demonstrated relatively good predictive performance, the machine learning-coupled COBRA-TF model significantly outperforms the standalone COBRA-TF predictions. This improvement is evidenced by a reduction in mean absolute error (MAE) from 161.64 to 117.58 (27% error reduction) and a decrease in root mean square error (RMSE) from 231.74 to 175.65 (24% error reduction). These findings highlight the ML-enhanced COBRA-TF model’s advanced predictive capability, presenting it as a reliable and versatile tool with potential for broader applications across diverse thermal-hydraulic environments.

In light water reactors, critical heat flux (CHF) is a thermal limit at which a boiling crisis occurs, marking the onset of departure from nucleate boiling (DNB) or dryout (DO). Several ML methods have been studied to predict CHF, but purely data-driven approaches struggle with interpretation, data limitations, and lack of physical context. This study builds on a hybrid approach that incorporates knowledge-based empirical correlations. Three ML techniques were evaluated in predicting correlation-measurement residuals and quantifying model uncertainties: deep neural network ensembles (DNNs), Bayesian neural networks (BNNs), and deep Gaussian processes (DGPs). These models were implemented using the public CHF dataset from the 2006 Groeneveld lookup table, focusing on cases of DO. Two training sizes were considered: a nominal case (80% of the original dataset) and a throttled case (0.1%). Hybrid DNN ensembles outperformed pure ML models and other methods, particularly in throttled cases, maintaining metrics below standalone correlations. They exhibited high confidence with low variability in predictions. BNNs showed similar results but with higher relative standard deviation and slightly elevated errors. Hybrid models resisted performance degradation with limited data, though errors were higher than bare correlations. DGPs had the least favorable metrics but small uncertainties in nominal cases. This methodology was then implemented in the thermal hydraulic code CTF as a first proof of implementation. Overall, these hybrid approaches were shown to offer a high degree of accuracy with low uncertainties, in addition to having a more interpretable basis compared to purely data-driven CHF modeling approaches.

The development of an accurate model to predict Critical Heat Flux (CHF) is essential for advancing nuclear power technology, where safety and efficiency are paramount. In this context, a Machine Learning (ML)-based model has been constructed based on the latest released NEA benchmark dataset on CHF. Comprehensive analyses have been conducted on feature selection, extraction, and features engineering to enhance model learning capacity. Additionally, a data augmentation process incorporating background noise was employed to increase robustness. Preliminary results indicate that this purely data-driven machine learning architecture, an 8-layer feedforward neural network with batch normalization and optimized dropout layers, outperforms traditional empirical models and lookup tables in regression tasks. The network leverages hidden data relationships for improved accuracy, suggesting that ML approaches could offer a more adaptable and precise tool for predicting the CHF, which is valuable in optimizing reactor cooling system design and operation. Future work could explore integrating physics-informed neural networks (PINNs) to blend data-driven insights with established physical laws, potentially enhancing model reliability and interpretability. Additionally, the inclusion of pretrained models could offer a powerful baseline, enabling the framework to leverage previously learned features and patterns, which may reduce computational costs and improve generalizability. Furthermore, applying explainability techniques like SHAP or LIME could provide critical insights into feature importance, helping refine feature engineering and model interpretability.

Following the TMI accident, the concept of ‘risk’ was introduced to comprehensively evaluate the safety of complex systems in NPPs. Risk means potential losses that may occur in the future due to certain factors and is defined as the probability of an event occurring multiplied by the consequence of the event. Current methodologies such as Probabilistic Safety Assessment (PSA) are used for risk evaluation. However, these methodologies have some limitations, making them inefficient for assessing the risks of individual accident sequences. To address this issue, this study proposes a methodology to develop risk profiles for each accident sequence through source-term analysis. In this study, a source term analysis uncertainty assessment was conducted specifically for core damage accident sequences of Loss of Feedwater (LOFW) and Small Loss of Coolant Accident (SLOCA) based on the OPR-1000 level 1 PSA model. Based on the result, we quantified the consequences for each sequence and developed risk profiles by visualizing the risk through frequency-consequence curves (F-C curve). This approach can efficiently evaluate the risks of each accident sequence efficiently and present them in a clear visualization. These results contribute valuable information to the risk communication process.

As part of ASNR's development of Level 1 and 2 Probabilistic Safety Assessments (PSA), various support studies are conducted for internal events (IE) PSAs and internal and external hazards PSAs (fire, internal and external flooding, internal explosion, seismic, heat wave…) for operating French nuclear power plants and for some other nuclear facilities. Among these, several thermohydraulic studies are performed using tools developed by ASNR such as the SOFIA simulator (Simulator for Observation of Incident and Accident Scenarios) for the Level 1 PSA, and the ASTEC integral code for the Level 2 PSA. Those tools can simulate a wide range of operational conditions, from full power to shutdown states for 900, 1300, and 1450 MWe PWRs, as well as for the EPR. These thermohydraulic simulations play a crucial role in assessing the kinetic and the consequences of accidental scenarios, to determine whether core or fuel damage occurs, to identify the mitigation systems success criteria and to understand when and how the core uncover. They also contribute to the human reliability assessment by providing available time for diagnosis, decision-making and operator actions. Furthermore, these studies allow the examination of uncertainties inherent to key parameters, such as the size and location break in primary circuit, and their impact on the progression of the accident.

The paper presents the status and perspectives of these studies for PWRs or other facilities and introduces some expectations for possible other reactor designs (e.g. Small Modular Reactors - SMRs).

Passive safety systems employing physical processes and phenomena, such as natural circulation, have been widely applied to the contemporary design of Light Water (LW) Small Modular Reactors (SMRs). The demonstration of passive system reliability requires mechanistic analysis of the system performance in all possible accident scenarios. During the assessment, identification of the “failure domains” i.e. the domains of scenario parameters where the passive system fails to fulfil its mission, and associated “failure modes” of the system is challenging due to a wide range of operational conditions that need to be assessed. The brute-force search is computationally impractical due to the high-dimensional nature of the input space and the significant computational cost associated with Full Model (FM) evaluations.

The goal of this work is to demonstrate the feasibility of using advanced search methods, i.e. genetic algorithm, for the identification of the “failure domain” and its boundaries in the multidimensional space of accident scenario parameters. The primary objective is to improve the search efficiency by reducing a Figure of Merit (FOM) defined as the total number of FM evaluations by the number of identified boundary points. Three frameworks are developed, tested and compared on a benchmark case. The method that integrates GA and Adaptive Triangulation Sampling (ATS) demonstrates a good performance.

The Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) Committee on the Safety of Nuclear Installations (CSNI) has directed the NEA Expert Group on Small Modular Reactors (EGSMR) to identify and prioritize knowledge gaps where cooperative research would facilitate the safe deployment of small modular reactors (SMRs). EGSMR is executing a pilot project to demonstrate a method to generate research recommendations for advanced technology (AT-), non-water cooled, designs. High-temperature Gas Cooled Reactors (HTGRs) were selected to pilot this process; however, it is meant to be generally applicable with future application to other AT-SMR technologies. The identification and prioritization of phenomenological knowledge gaps has been built into a procedure to be completed by a task team in coordination with subject matter experts and NEA Working Groups. Phenomena Identification and Ranking Tables (PIRTs) are tools used to identify phenomena important to reactor safety by numerical ranking of importance and knowledge level. In the current work, PIRT information is collected by the task team and sorted into phenomenological groupings before being ranked based on PIRT knowledge gaps, safety significance and suitability for international collaborative experimental research. Consulting with subject matter experts, the task team will refine the prioritization list into a final set of high priority research subjects. In a later phase of the AT-SMR pilot project, these subjects will be linked to experimental facilities and compiled into a final set of detailed research activity recommendations.

Post-Critical Heat Flux (Post-CHF) is one of the most complex two-phase phenomena significantly affecting the coolability of nuclear fuel during a loss of coolant accident (LOCA) in light water reactors. Wall heat transfer characteristics in inverted annular film boiling (IAFB), inverted slug film boiling (ISFB), and dispersed flow film boiling (DFFB) regimes have been widely investigated in the literature to develop heat transfer models/correlations to predict the peak cladding temperature among other parameters. However, lack of comprehensive data necessary for validating physical assumptions made during modeling of the IAFB/ISFB/DFFB regimes has led to limited predictive capabilities of existing models and correlations. In this study, a series of quasi steady-state IAFB, ISFB, and DFFB experiments were performed in the Post-CHF Heat Transfer (PCHT) test facility at the University of Michigan that employs a direct hot-patch technique to stabilize the quench fronts in a tubular test section made of Incoloy 800H with an inner diameter of 12.95 mm. Experimental conditions spanned over a relatively broad range to investigate the effects of the liquid subcooling, mass flux, and system pressure on heat transfer in those regimes. Detailed test section wall temperature was acquired using thermocouples and the void fraction in the test section was measured using a gamma densitometer and an X-ray radiography system. In addition, the predictive capabilities and limitations of the existing models for those regimes were evaluated using the acquired film boiling experimental data. Based on the model benchmark results, improvements were proposed to enhance the model accuracy for IAFB/ISFB/DFFB wall heat transfer.

[1] This abstract is intended for Dr. Sun’s American Nuclear Society Thermal Hydraulics Division Technical Achievement Award (ANS THD TAA) Lecture.

This abstract was prepared as an account of work sponsored by an agency of the U.S. Government. Neither the U.S. Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for any third party's use, or the results of such use, of any information, apparatus, product, or process disclosed in this paper, or represents that its use by such third party would not infringe privately owned rights. The views expressed in this paper are not necessarily those of the U.S. Nuclear Regulatory Commission.

Microlayers beneath nucleating vapour bubbles are pivotal in enhancing bubble growth through evaporation during boiling, making their formation and depletion critical for accurate boiling heat transfer predictions. Recent studies employing advanced techniques such as Synchrotron X-ray imaging and Direct Numerical Simulations (DNS) have revealed significant morphological variations in microlayers during nucleate pool boiling on micro-structured surfaces. Bubble coalescence, a common phenomenon in nucleate pool boiling, further complicates microlayer dynamics. This study addresses a commonly observed but poorly understood coalescence event, where an ejecting bubble merges with a nucleating bubble on a micro-structured surface. Leveraging Synchrotron X-ray imaging of nucleate pool boiling and DNS of the bubble merging process, we report a jet formation mechanism induced by such a coalescence phenomenon, which leads to the rapid depletion of the microlayer. These findings provide essential insights for improving the accuracy of boiling heat transfer predictions.

Corrosion of structural materials is a critical issue for the nuclear industry. A major challenge concerns devices operating under boiling conditions, where corrosion can be influenced by various factors, in particular wall temperature, heat flux at the wall, and boiling. To enable an accurate modeling of corrosion in such industrial conditions, a comprehensive understanding of bubble behavior and associated thermal characteristics is imperative. This study aims to investigate the bubble dynamics and heat transfer through direct numerical simulations using the well-validated open-source code TRUST/TrioCFD. In this study, two-dimensional axisymmetric simulations are performed to investigate the growth and departure of bubbles originating from a single nucleation seed, focusing particularly on the effect of micro-region adjacent to the liquid-vapor-solid triple contact line and the transient conjugate heat transfer between the fluid and the adjacent solid wall. A multiscale modeling approach is adopted. The CFD-algorithm at the bubble-size scale is coupled to a sub-grid micro-region model. The micro-region model describes the partial wetting case. It takes the wall superheating and microscopic contact angle as inputs, and predicts the apparent contact angle and heat flux. Entire boiling cycles, including growth and departure phases followed by a waiting period, were simulated. We obtained detailed information on wall surface temperature and heat flux, directly applicable in corrosion models. Sensitivity analysis to the wall properties demonstrated that materials with higher thermal diffusivity exhibit a larger apparent contact angle, longer growth time, larger departure diameter, and shorter waiting time.

Dynamical System Scaling (DSS) is an innovative scaling methodology focused on incorporating transient behavior in the scaling criteria. This paper applies DSS to bubble dynamics by comparing experimental data to analytical solutions of the Rayleigh-Plesset equation. The Rayleigh-Plesset equation governs the motion of bubbles in an infinite body of fluid, and it is derived by simplifying the Navier-Stokes momentum equation with spherical symmetry. The motivation of this study is to evaluate a bubble growth correlation for rapid vaporization transients, which was identified in a previous DSS analysis with a peculiar initial growth rate. A simplified Rayleigh-Plesset equation is derived assuming that the bubble growth is solely inertially controlled. Atomic bomb test data is used for comparison purposes as it is presumed to have negligible heat transfer on the shockwave interface. DSS is employed to calculate the distortion between the experimental data and the analytical solution. Additionally, results will be compared to theoretical DSS work previously performed which applied DSS to bubble dynamics. This asymptotic analysis concludes that the correlation is unsupported, and the original test data does not cover the early stage. Therefore, DSS successfully identified that further improvement is needed to the existing correlation.

Small Modular Reactors (SMRs) constitute a significant advancement in nuclear technology, where Pressurized Water Reactors (PWRs) are extensively applied. Within PWRs, pressurizers play a critical role in maintaining pressure and help ensuring thermohydraulic safety. Nitrogen gas pressurizers offer advantages such as rapid response, compact design, and simplicity, rendering them more suitable for SMRs than steam pressurizers. Nonetheless, nitrogen may dissolve in cooling water and desorb as bubbles during pressure transients, leading to two-phase flow and damage reactor safety. Currently, a substantial gap exists in the accurate prediction of the conditions under where and when bubbles nucleate, how they evolute and impact on thermohydraulic safety. To establish a reliable predictive model and identify solutions for enhancing reactor safety, it is imperative to investigate the nucleation and growth behaviors of bubbles under supersaturated conditions during depressurization. This study aims to elucidate the supersaturation ratios at which bubble formation occurs and to characterize their evolution over time. We conducted microscopic experiments and numerical simulations of bubble dynamics at supersaturation ratios ranging from 0.1 to 3 on hydrophilic and hydrophobic surfaces. The results indicate that the initial bubble nuclei sizes are below 20 μm, significantly smaller than the conventional view of over 100 μm. The bubble growth behavior conforms to the Epstein-Plesset equation, and Ostwald ripening occurs at specific sites. Besides, surface wettability is proved to have significant influences on bubble nuclei size and density. These results provide experimental evidence that the existence of nanobubbles may contribute to inaccuracies in classical theoretical predictions.

The behavior of bubbles in multiphase flow systems is critical to many industrial applications, including nuclear reactors and separation processes. While significant research has been done on bubble dynamics, the effect of perforated plates in downward flow conditions remains less explored. This study aims to investigate the dynamics of air bubbles in a downward flow as they interact with perforated plates, focusing on bubble penetration probability and bubble residence time near the plate.

Preliminary results suggest that the perforated plate significantly interrupts the two-phase flow, with a smaller open area ratio leading to fewer bubbles passing through the plate. Experiments were conducted in a vertical water channel with a perforated plate positioned to obstruct the downward flow. To focus on the bubble motion, a single bubble was injected into the channel. The bubble motions were recorded using high-speed imaging, and varying flow rates and hole geometries were tested. The Bond number and other dimensionless parameters were analyzed to understand the characteristics of the flow and the air bubbles.

The study is expected to reveal how flow rate and perforation geometry influence bubble motion when the bubble encounters a perforated plate in downward flow. The findings from this research will contribute to a deeper understanding of bubble behavior in two-phase flow systems with perforated structures, which can inform the design of more efficient separation devices and reactors.

A series of experiments were conducted to investigate bubble characteristics in a vertical annular channel under a wide range of pressure conditions. For this purpose, a custom-designed 4-sensor optical fiber probe (4S-OFP) was developed to measure key local two-phase flow parameters, including local void fraction (α), bubble velocity (V_b), and Sauter mean diameter (D₃₂). The 4S-OFP demonstrated applicability in high-pressure, high-temperature environments up to 15 MPa and 350°C, with measurement uncertainties of approximately 2% for α, 5% for V_b, and 16% for D₃₂. The experimental conditions covered outlet pressures of 0.2–10.0 MPa, mass fluxes of 400–5,000 kg/m²s, inlet subcooling temperatures of 7–25°C, and heat fluxes of 300–620 kW/m². Local bubble parameters were systematically measured and analyzed under varying flow conditions, including mass flux, inlet subcooling, heat flux, and system pressure. The results showed that void fraction was strongly influenced by flow conditions, particularly heat flux and system pressure, while bubble velocity demonstrated a strong sensitivity to changes in mass flux. Additionally, the Sauter mean diameter (D₃₂) exhibited noticeable variations depending on both the inlet subcooling and the system pressure. These findings provide valuable experimental data for validating and improving existing thermal-hydraulic models, particularly under diverse pressure and subcooled boiling flow conditions. The dataset also highlights the importance of precise measurement techniques, such as the 4S-OFP, for advancing the understanding of local bubble dynamics in two-phase flow systems.

A critical heat flux (CHF) occurring on a heat transfer surface under forced flow conditions has different mechanisms depending on the flow channel geometry and flow conditions. In the thermal design of reactor cores, the CHF is an important phenomenon, and it is essential to understand the CHF characteristics under actual flow conditions to improve the CHF prediction method. In this study, steady-state CHF experiments were conducted in forced convection boiling flow at low velocities under high-temperature and high-pressure conditions using a 2 × 2 heated rod bundle with a heated length of approximately 1.2 m. An optical fiber sensor inserted in a 0.5 mm diameter metal tube was mounted on the rod surface and captured the axial distribution of the rod surface temperature at a frequency of 100 Hz and a spatial resolution of 2.6 mm. The experimental results showed intermittent increases and decreases in the rod surface temperature at the top of the heated rod bundle section with stepwise increases in the rod bundle thermal power. This corresponds to repeated localized dry patch formation and rewetting. As the inlet subcooling decreased, the onset of the rod surface temperature increase shifted upstream and dry patches formed over a larger area in the flow direction. A slight increase in the thermal power of the rod bundle near the CHF expanded the area of dry patches or increased the frequency of their occurrence, leading to a transition to a continuous increase in rod surface temperature.

Subchannel analysis is the most competitive approach in thermal hydraulics analysis of rod bundles. It considers transport of mass, momentum and energy axially along the subchannel and laterally across the gaps between the subchannel. Turbulent mixing is an influential parameter for lateral exchange across the gaps which is caused due to velocity fluctuations in the axial direction. Several factors such as rod bundle geometry, coolant flowing properties, gap distance between the subchannels and eddy diffusivity play an essential role in the turbulent mixing parameter. A wide number of experimentally fitted empirical correlations are present to predict turbulent mixing parameter for different subchannel geometry with a significant average mean error among themselves. In 2018, Shen et.al. performed Computational Fluid Dynamics (CFD) for a square bare rod bundle and developed a correlation for square-square center subchannel interaction for the turbulent mixing parameter. In this paper, a similar CFD analysis is performed for a hexagonal bare rod bundle between two triangular center-center subchannel and a center-side subchannel using Reynolds Stress Model (RSM) for a range of Pitch to Diameter ratio varying from 1.1-1.5 for the Reynolds number in the range 8000 to 100000. A new correlation is being developed for turbulent mixing parameter using this numerically generated data. The developed correlation is then compared with the existing empirical correlations.

The void fraction is a key parameter for affecting the coolability and neutron-moderating performance of water-cooled nuclear reactor. More refined experimental data are required to develop multi-fluid dynamics models for determining the void fraction distribution. A Wire Mesh Sensor (WMS) with rod electrodes was developed to measure the cross-sectional distribution of void fraction in a 7 × 7 heated rod bundle with a diameter of 9.5 mm and pitched at 12.6 mm, and applied to a boiling two-phase flow experiment under atmospheric pressure conditions assuming at accident in pressurized water reactor (PWR). The sensor consists of 8-wire by 8-wire and 7-rod by 7-rod electrodes. Wire electrodes with a diameter of 0.2 mm are arranged in a horizontal and vertical crosswise between the rod bundles. For each measurement, the local void fraction in the subchannel center at 64 points were obtained from the wire by wire electrodes and 196 void fraction points near the rod surface were obtained from the wire to rod electrodes. The temporal resolution of the void fraction measurements was 2500 frames. The axial and radial power distribution of the heated rod bundle is uniform.

This study presents the development of a detailed experimental database for two-phase flow interfacial parameters in a 5×5 rod bundle channel featuring a spacer grid. The investigation aims to elucidate the spatial and transport characteristics of gas-liquid interfacial structures and the influence of spacer grids on two-phase flow dynamics.

A comprehensive experimental system was designed, incorporating flow visualization, four-sensor conductivity probe, and two-phase PIV (Particle Image Velocimetry) measurement technologies. Key interfacial parameters, including void fraction, bubble size, interfacial area concentration, and velocities of gas and liquid phases, were systematically measured and analyzed under various flow conditions.

Results reveal distinct distributions of void fractions transitioning from "core-peak" to "gap-peak" patterns as liquid velocity increases, driven by enhanced turbulent mixing. Spacer grids significantly disrupt flow characteristics, causing bubble breakup and coalescence, with effects extending approximately 20 hydraulic diameters downstream. Existing drift and fluctuation velocity models underpredict the impact of spacer grids, highlighting the need for model optimization.

This work provides critical insights into the complex behavior of two-phase flow in rod bundle channels, offering validated datasets to enhance computational models for reactor thermal-hydraulics and guiding the design of spacer grid structures for improved flow stability.

The boundary layer forms the main thermal resistance for heat transfer between the coolant and the fuel rod. Therefore, the structures of the velocity boundary layer greatly affect the thermal hydraulic performance of the fuel rods. The present study performed experimental investigation on effects of pulsating flow on evolution of the velocity boundary layer in a 5×5 rod bundle channel. The Time Resolved Particle Image Velocimetry (TR-PIV) technique is used to directly measure the velocity distributions near the rod surface under different flow conditions. The velocity boundary layer is reconstructed from the measured velocity. The dimensionless velocity distribution over the surface of the fuel rod is obtained by fitting the experimental data to the Spalding formula. The structure of the boundary layer and flow characteristics are analyzed and compared quantitatively. The experimental results indicate that the perturbation introduced by the pulsating flow can disrupt the development of the boundary layer and significantly reduce the thickness of the inner layer of the boundary layer. The larger the amplitude and the smaller the period, the greater the perturbation introduced by the pulsating flow.

Sodium-cooled fast-neutron reactors are currently considered to be the most mature type of reactor able to closing the fuel cycle. In France and throughout the world, pool-type reactors are selected to build generation IV power plants. Complex liquid sodium flows are known to occur in reactors in several conditions. In order to predict these phenomena, CEA developed the MATHYS code (Multi-scale Advanced Thermal-HYdraulics Simulation). This tools enables the coupling of the system thermal hydraulics code CATHARE, the sub-channel code TrioMC and of the 3D thermal-hydraulics code TrioCFD. Thanks to this coupling approach, the entire primary side of a reactor can be modelled, accounting for the feedbacks for the different scales (core, inter-wrapper flow, pools). In the late 1980s, the CLAUDINA test facility was operated at the CEA Cadarache research centre. The experimental campaigns aimed at the characterisation of the behaviour of an intermediate heat exchanger (IHX) under a variety of operation conditions. The CLAUDINA facility is a mock-up of a sodium –sodium IHX. Tests at different flow conditions were performed. The experimental data from these tests are very valuable for the validation of the intermediate heat exchanger modelling in MATHYS. In this paper, the CLAUDINA facility is first introduced. The CATHARE, TrioCFD and Neptune_CFD codes are then presented, and the models of the CLAUDINA facility are described. The results of these different modelling approaches for several tests are presented and discussed. Conclusions and recommendations are proposed.

The inherent safety features make lead-cooled fast reactors (LFRs) an attractive solution for the increased energy demand and the development of advanced nuclear power plants. Due to the limited operational experience with these reactors, simulation and analysis with system thermal-hydraulic (STH) codes become crucial to study the plant behaviour under safety-relevant conditions and to support the reactor design. In this paper, the LFR modelling has been carried out with different STH codes, such as RELAP5 Mod 3.3 version Beta, modified by University of Pisa to account for lead as working fluid, ASYST-LM and ATHLET codes.

The simulation activity aimed at assessing the code capabilities to reproduce selected phenomena occurring in LFRs under normal and accidental conditions, derived from some of the most representative transient scenarios, such as unprotected loss of flow (ULOF), unprotected loss of heat sink (ULOHS), unprotected transient of overpower (UTOP) and unprotected loss of offsite power (ULOHS+ULOF). Particular attention has been paid to the establishment of natural circulation following the loss of primary pumps, which affects the sizing of the safety features derived from such operating conditions.

The obtained results will support the verification and validation efforts of the STH codes applied to LFRs. The investigated codes show a good agreement and the comparison proposes some open perspectives and future improvements.

Passive safety systems employing physical processes and phenomena are increasingly applied to contemporary nuclear reactor design. Assessment of the performance of these systems under various scenarios relies heavily on numerical analysis using codes from 1D to 3D depending on different levels of the design and safety demonstration purposes. Thermal-hydraulic (TH) phenomena in pool-type Lead-cooled Fast Reactors (LFRs) often exhibit multi-dimensional characteristics such as the development of thermal stratification and mixing during natural circulation. Accurate prediction of mutual interaction between these phenomena in the pool and its effects on loop dynamics requires 3D analysis.

Computational Fluid Dynamics (CFD) provides high-fidelity 3D TH analysis but is computationally expensive for analysis of prototypical conditions. System Thermal-Hydraulic (STH) codes (e.g., RELAP5) offer efficient calculation but are inadequate to resolve 3D phenomena. A compromised solution is to use system-level TH codes with 3D features, e.g., (GOTHIC, CATHARE). The recent development of GOTHIC enables the modeling of Lead-Bismuth Eutectic (LBE) flow while its suitability and validity for safety analysis need to be confirmed.

Therefore, this work aims to assess GOTHIC predictive capabilities for LBE 3D phenomena through code-to-code and code-to-experiment comparisons. Validation data is obtained from a forced to natural circulation transient produced in TALL-3D facility which is a 7m LBE loop featuring a 3D pool-type test section. Simulations are performed using CFD code ANSYS Fluent and system TH code GOTHIC. The focus will be pool thermal stratification and mixing in the 3D test section.

Current major international nuclear reactor system analysis codes predominantly utilize the two-fluid six-equation model to study the behavior of nuclear power plants under accident conditions, which presents considerable limitations. Most studies of the two-component two-fluid model have focused on water-steam systems, while liquid metal-gas systems at high temperatures have received relatively less attention. This paper studies the two-component two-fluid model and its rapid solution method to address the demands of full-scale simulations for both existing and conceptual nuclear reactor systems. The conservation equations of the two-component two-fluid model are discretized using a first-order upwind semi-implicit method, based on the staggered grid and finite volume difference. A system of linear equations is derived by substituting the equation of state and solved using the NRLU method. The mathematical suitability of the model is enhanced by introducing a virtual mass force. When one phase of the two-component two-fluid model is absent, the fraction of the virtual phase is assigned a small value to prevent the coefficient matrix from becoming singular. By simulating the natural circulation and gas injection-enhanced circulation conditions at varying power levels on the lead-bismuth loop test bench NACIE, the numerical accuracy and computational stability of the semi-implicit numerical algorithm for lead-bismuth-gas two-component two-fluid model are successfully demonstrated. It lays the foundation for further research on the two-component two-fluid model and the development of related code.

Lead-cooled Reactors (LFRs) are considered a promising concept in the framework of designing new Generation-IV reactors. The analysis of the thermal-hydraulics phenomena can be performed by means of numerical RANS simulations. This paper aims to evaluate the best practices for the mesh generation of a grid spaced fuel-bundle assembly. The results are compared to the experimental results provided in the LFR-T/H benchmark promoted by OECD NEA. The work focuses on different strategies to generate the background mesh and alternative modelling tools (e.g baffles) for capturing detailed geometry and dealing with the contact points in OpenFOAM. Initially, the bundle geometry without the grid is simulated under isothermal conditions and the results in terms of pressure drop are compared with existing correlations. In the second part, a single grid is included in the numerical domain, and it is characterized in terms of pressure drop as function of the flow velocity.

Liquid metal cooled fast reactors is one of the most promising fourth-generation nuclear systems. Y-junctions are commonly adpot in piping system. Non-Isothermal fluids frequently mixed in these components, lead to thermal pulsation on the solid-wall, and may induce thermal fatigue to piping system.To understand the mechanism of thermal pulsation and thermal fatigure, we independently set up a non-isothermal mixing test platform of the working fluid, and obtained the temperature distribution of the working fluid during the non-isothermal mixing process in the 90° Y-shaped component. This verifies the correctness of the Dynamic Smagorinsky Sublattice model in the non-isothermal mixing simulation, so as to correctly simulate the flow and heat transfer of liquid metal. On this basis, large Eddy Simulation (LES) approach for liquid metals in Y-junctions was applied. Angle and velocity pulsation behavior caused by the mixing of hot and cold fluids in Y-junctions under different incident angles (θ=30-90°), and momentum ratios (M_R=0.25–4.51) were discussed. The results show that the momentum ratio and the angle significantly influence the mixing characteristics of hot and cold fluids. At a 90-branch angle, fluid mixing is uniform, the thermal pulsation peak is larger. As the momentum ratio increases, the peak temperature pulsation gradually decreases. The findings offer valuable insights for the thermal-hydraulic design of future liquid metal cooled fast reactors.

Argonne is participating in the International Atomic Energy Agency (IAEA) coordinated research project (CRP) on “Benchmark of Transition from Forced to Natural Circulation Experiment with Heavy Liquid Metal Loop (NACIE)”. The NACIE loop includes a fuel pin simulator section which is a hexagonal array of 19 wire-wrapped, electrically heated pins and uses lead-bismuth eutectic as a working fluid. Argonne’s work on the CRP includes CFD simulations with the NekRS and Cardinal codes. Both LES and RANS turbulence models were used in NekRS coupled via Cardinal to a solid conduction model to account for conjugate heat transfer. Via comparisons against experimental measurements from the NACIE tests, these benchmark simulations are being performed to expand the validation basis of these codes. The objective of this paper is to present recent progress on NACIE test simulations which cover both forced and mixed convection conditions with uniform and skewed heating profiles. Results from simulations will be compared to available experimental data.

CFD becomes more and more important in nuclear reactor safety considerations. For multiphase flows in the related medium and large scales the Euler-Euler approach is most frequently used and often the only feasible one. In many flow situations, the involved interfaces cover a wide range of scales leading to different coexisting morphologies. Established simulation methods differ for the different interfacial scales. Large interfaces are represented in a resolved manner usually basing on the one fluid approach, e.g. Volume of Fluid (VOF) or Level Set. Unresolved (dispersed) flows are modelled using the two- or multi-fluid approach. A simulation method that requires less knowledge about the flow in advance would be desirable and should allow describing both interfacial structures – resolved and unresolved – in a single computational domain.

The morphology adaptive multifield two-fluid model MultiMorph, which is developed at HZDR based on the software from the OpenFOAM Foundation, is able to handle unresolved and resolved interfacial structures coexisting in the computational domain with the same set of equations. An interfacial drag formulation for large interfacial structures is used to describe them in a VOF-like manner, while the usual closure models are applied for the unresolved phases. In addition, MultiMorph allows to simulate transitions between the morphologies. This concerns both empirical transitions such as entrainment and detrainment as well as transitions resulting from a change in the size of the numerical mesh within the domain. The basic framework including the handling of transitions between the morphologies will be presented.

Blockage in a reactor fuel assembly is considered to be one of the most important accidents that should be analyzed in detail. A variety of factors can contribute to the occurrence of such an accident, among which are fuel element bending or local deformation and swelling of the cladding. The reduction of coolant flow area can cause local heat transfer deterioration and temperature augmentation, which can further lead to dry-out and possible loss of fuel assembly integrity. It is challenging to evaluate the consequence of flow blockage accident due to lack of knowledge about local flow parameters as well as their response mechanism, especially when two-phase flows are concerned. Moreover, due to negligible influence on global mass flow, it is difficult to detect the accident through protection system. Owing to the availability of advanced computer systems, simulation using either system or CFD codes has become an important tool in assisting the analysis of these local phenomena and evaluation of their impact on the safe operation of nuclear reactors. This study presents a CFD study of three vertical pipe bubbly flow cases, one empty pipe, one with a ring obstacle and one with a baffle obstacle, and both obstacles block a half of the flow area. The focus is put on analyzing the effect of blockage on the velocity and turbulence field as well as the development of bubble size. Different turbulence models and mechanisms leading to bubble coalescence and breakup are discussed and evaluated with the aid of experimental data.

During severe nuclear accidents, hydrogen generated in the reactor core can mix with air to form potentially explosive mixtures. The severity of such explosions depends on the mixture composition and the combustion regime. In highly turbulent conditions, combustion is significantly accelerated, and simulations have shown that heat loss has minimal impact on flame propagation due to its slower rate relative to combustion. However, in the case of slower deflagration, heat loss is expected to play a more significant role in flame evolution.

This study focuses on modeling the effects of conductive and radiative heat losses in a slow hydrogen-air-steam combustion scenario during the HD-22 experiment at the THAI experimental facility. Unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations were conducted using computational fluid dynamics software OpenFOAM software and combustion model flameFoam. Heat loss was modeled through conductive heat transfer to an isothermal wall and the P1 model for radiative transfer.

Simulation results showed good agreement with experimental data, indicating that including heat loss mechanisms slightly delayed the completion of combustion and slighlty reduced the maximum overpressure, as well as slowed down the vertical flame propagation. Results show that the conductive and radiative heat loss contribute similarly to the total heat loss, emphasizing radiative heat loss importance in modeling slow combustion.

Overall, the study highlights the critical role of heat loss, particularly radiative heat transfer, in accurately simulating slow hydrogen explosions.

The pressure drop of PWR fuel assemblies has an importance in the core itself (global flowrate, flow distribution, hydrodynamic forces) but also in the storage pools and in the different cells or casks in which it may be stored. The behavior in nominal conditions is well known and has been largely experimentally and numerically investigated, however the characteristics at much lower Reynolds numbers are less studied.

The first objective of this paper is to discuss the adequate turbulence models for those low turbulence situations. Available experiments provide useful data of pressure drops and velocity of different elements in a large range of Reynolds numbers (device made of a typical fuel bundle (17x8) with 4 mixing and supporting grids, at full scale). CFD computations with RANS, URANS, Detached Eddy Simulations and Large Eddy Simulation turbulence models are performed and compared with measurements. The modeling of the wall friction is also discussed. The computational meshes are obtained from an automatic process and are based on polyhedrons.

The second objective is the influence of the domain modeled in such quasi-periodic configurations and the associated boundary conditions. The different periodicity conditions are particularly investigated on 2x2 simplified models, with the transverse effect of mixing vanes.

The commercial Ansys-Fluent and Star-CCM+ codes are both used and conclusions are drawn on the two objectives mentioned above.

Finally, this paper concludes on the recommended setup in order to provide industrial values of pressure drops of the components of the fuel assembly in the different off-reactor situations.

The Forschungs-Neutronenquelle Heinz Meier-Leibnitz (FRM II) is actively contributing to global efforts to reduce the use of Highly Enriched Uranium (HEU) in civilian nuclear applications. A key step in this initiative is converting the current fuel system to a high-density Low Enriched Uranium (LEU) fuel. In 2023, a feasibility study demonstrated the scientific viability of converting the FRM II to U-10Mo LEU, while maintaining FRM II scientific performance. Due to the changed plate design, many LEU designs exhibit lower pressure drops through the fuel element. To minimize the impact to the FRM II reactor, we aim to have a similar pressure drop across the fuel element in the forward flow direction than for today’s HEU core and a lower pressure drop required in reverse to mitigate impacts during transient scenarios. To meet these demands, the previously published design incorporated a flow restrictor downstream of the fuel element to increase the pressure drop. In the current study, an alternative approach is explored by thickening the cladding at the end of the fuel plates. Various cladding thicknesses are evaluated, and the resulting pressure drops are computed using Computational Fluid Dynamics (CFD). Additionally, the influence of rounded fuel plate caps is quantified.

The artery alkali-metal heat pipes in reactors are essential for energy transfer, with dynamic thermal performance, such as two-phase circulation startup and capillary heat transfer limits, posing challenges to overall reactor performance. Investigating the capillary dynamics behind the transient thermal load is crucial for understanding the operational characteristics of artery heat pipes. This work aims to investigate the complex heat and mass transfer phenomenon of the capillary limit, which is characterized by dynamic non-equilibrium and multi-scale and multi-physical coupling, by conducting this research from the three dimensions of micro-mesoscopic mechanism, macro heat transfer characteristics, and reactor system operating patterns. By developing a theoretical framework for dynamic capillary heat transfer, a dynamic thermal analysis model for the artery heat pipes has been established and validated through experiments. The average error of the capillary dynamics model compared to experiments is 3%, while the dynamic heat transfer model shows less than 10% error against CFD simulations and under 20℃ error compared to steady-state and transient experimental results, confirming the model's accuracy. Additionally, the study investigates the correlation between capillary dynamics and dynamic heat transfer phenomena, identifying three startup phases of free molecular flow, continuous flow expansion, and continuous flow. It categorizes capillary limits into gas-phase and liquid resistance-dominated types based on two-phase countercurrent circulation. By combining the weak feedback characteristics of fast reactors with the dynamic heat transfer of artery heat pipes, the study proposes operational strategies for typical heat pipe reactors, examining system behavior during startup and under transient thermal loads.

The focus is on a 10 MW thermal Advanced High Temperature gas-cooled Micro Reactor (AMR) currently being designed. The reactor will employ prismatic graphite blocks for structural and moderator material. There will be 420 fuel assemblies in the core using low enriched TRISO fuel contained in borings within the fuel graphite blocks that allow annuli for cooling. The thermal-hydraulic behaviour of the reactor under steady-state conditions and during a Depressurized Loss of Forced Cooling (DLOFC) event has been simulated employing an axi-symmetric systems network model using Flownex SE. Under steady-state conditions the helium coolant enters the reactor at 320 C and exits at 750 C. It is found that the bottom of the core is 403 C hotter than the top of the core and in the radial temperature gradient is distorted due amongst others to an average drop in temperature of 220 C between the last fuel ring and the outer reflector (OR). The OR transfers 618 kW to the coolant flowing up the risers placed in the OR, preheating the coolant 346.8 C. The reactor cavity cooling system (RCCS) rejects 86.1 kW. During the first 5 seconds of the DLOFC the mass flow rate through the initially increases due to the blowdown effect, and the heat transfer to the also fluid increases initially. Subsequently the heat rejected by the RCCS reach a maximum of 109 kW. It found that the heat released by the solids can constitute up to 45.5% of the heat rejected by the RCCS.

The eVinci™ Microreactor which is under development by Westinghouse Electric Company could bring a cost-competitive and reliable nuclear energy source to the world. The small size of the eVinci microreactor allows for transportability and rapid, on-site deployment.

Instead of a fluid-based primary coolant system normally seen in nuclear power plants, eVinci Microreactor adopts heat pipes to transfer heat from the reactor to the Primary Heat Exchanger (PHX). The heat pipe design enables passive core heat removal which eliminates numerous components needed in active coolant systems and makes the eVinci microreactor a pseudo “solid-state” reactor with minimal moving parts.

The eVinci Nuclear Test Reactor (NTR) is a nuclear test facility dedicated for eVinci microreactor’s development. The NTR will provide critical engineering information for analysis code validation to support commercial licensing. A CFD model has been developed to support NTR PHX design optimization. A two-step method was employed for the NTR PHX CFD modelling. Step 1: A series of cases for single heat pipe finned-sleeve tube were simulated with the finned channel simplified as a porous media. The expressions for resistance and heat transfer coefficient were derived for porous media. The results were benchmarked to the test data. Step 2: Applied the derived expressions for porous media parameters from Step 1 to a full PHX CFD model. The results from Step 2 were used to help PHX design optimization. In this paper the two steps of the NTR PHX CFD model development were presented.

In this paper a multiphysics integrated full-core 3D model and the analysis results of the Westinghouse Nuclear Test Reactor (NTR) are presented, coupling the neutronic and thermal analysis in the reactor core and the heat transfer in the primary heat exchangers. The NTR reactor is an advanced 2~3 MWt transportable heat pipe cooled microreactor currently developed by Westinghouse. It is an epithermal reactor with prismatic solid core using TRISO particle fuel embedded in cylindrical fuel compacts.

The software tools used are finite element (FE) solvers developed in the framework of the Multiphysics Object Oriented Simulation Environment (MOOSE) under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program sponsored by the US Department of Energy (DoE). MOOSE-based multiphysics modules of neutronics and thermal-hydraulics are coupled in solving the 3-D fission power and temperature distributions in the full core NTR reactor model. Furthermore, the reactor core model is coupled with 1-D flow models of the cooling air channels over the condenser sections of heat pipe, simulating the heat transfer in the Primary Heat Exchanger (PHX). Non-uniform flow and inlet temperature among air flow channels are informed by detailed computational fluid dynamics (CFD) calculation of the PHX. Using this integrated model, several Design Basis Accidents (DBAs) identified for the NTR design are simulated, including the accidents initiated from inadvertent control drum rotation (reactivity insertion), total loss of PHX, and single heat pipe failure.

The Single Primary Heat Extraction and Removal Emulator (SPHERE) facility at Idaho National Laboratory (INL) has been instrumental in advancing the development and validation of heat pipe technologies for microreactor applications. As a part of these efforts, long-duration heat pipe tests are required to assess long-term reliability concerns related to wick degradation, corrosion, manufacturing methods, and compatibility of materials. This paper presents the findings of a long-duration test conducted at the SPHERE facility, focusing on the performance and reliability of a high-performance, defined as over 2kW, heat pipe under sustained operational conditions. The tests emulated the anticipated common thermal characteristics of microreactor concepts. The results show the robustness of heat pipes, with a significant amount of data collected on the ratio of heat losses to heat transported and degradation rates over an extended period. Key data and performance metrics, including time series of temperatures, axial temperature profiles, thermal response times, and heat transfer capabilities, the thermal output over thermal input, were reported and discussed. These findings provide critical insights into the design and optimization of heat pipes, underscoring their potential to enhance the safety and efficiency of next-generation reactor concepts.

Heat pipes are two-phase heat transfer devices that enable passive removal of heat from the reactor core to the power conversion system in heat pipe-cooled microreactor designs. Experimental investigations of heat pipe transients are needed for technology demonstration, verification and validation of numerical codes, and the establishment of regulatory requirements. The Single Primary Heat Extraction and Removal Emulator (SPHERE) facility at Idaho National Laboratory (INL) serves as a platform for evaluating the dynamic response of high-temperature heat pipes under a variety of operating conditions. The present work details the experimental investigation of a high-performance, defined as over 2kW sodium heat pipe subjected to rapid input power fluctuations induced by sudden changes in the evaporator temperature setpoint. In addition, the heat pipe was subjected to an asymmetrical heat load where a subset of heaters operated at 30% and 70% below their nominal power. These experimental conditions were chosen to simulate thermal and operational stresses expected to be encountered in microreactors to provide data on heat pipe behavior during such important transient events. Key data and performance metrics, including time series of temperatures and strains, axial temperature profiles, thermal response times, and heat transfer capabilities, the thermal output over thermal input, were reported and discussed. The results highlight the resilience of heat pipes, revealing their potential to maintain thermal stability and efficiency under varying power loads. Lastly, the paper concludes with a discussion on the significance of the results and their implications for future research.

Small Modular Reactors (SMRs) are a promising solution for carbon-free energy. With advanced passive systems SMRs show reduced possibility of transition to severe accidents (SA) compared to large reactors. Nevertheless, SA in extreme conditions is ineliminable due to inherent characteristics of fuel assemblies in pressurized water reactors (PWRs), necessitating a comprehensive SA analysis. Limitations in acquiring SA data and uncertainties in physical models require that uncertainty analysis be conducted to understand potential outcomes.

This study investigates the thermal-hydraulic behavior of SA progression in the reactor and metal containment vessel (MCV) integrity under SA conditions. i-SMR, an SMR under development in the Republic of Korea, is adopted as a reactor type. Using CINEMA, a system code developed in Korea, SA scenario was simulated. With the initial event set as a Loss of Coolant Accident (LOCA), a common SA sequence. Parameters, including minimum and maximum oxidation temperatures and steam heat transfer coefficients, were varied within specified ranges using Latin Hypercube Sampling. Key Figures of Merit (FOMs) related to MCV integrity, including core uncover timing, corium mass, and hydrogen production were analyzed. Results indicate that MCV integrity is maintained across these variations, supporting i-SMR’s ability to protect containment under extreme conditions.

In case of a severe accident in a PWR-type nuclear power plant, maintaining the structural integrity of the containment building – representing the last barrier against the release of radioactive material into the surrounding environment – is of utmost importance. Therefore, addressing the various challenges that the containment may be facing during an accident is a crucial part of reactor safety research. Reliable prediction of thermal hydraulic processes and phenomena inside the containment are key to optimizing accident management measures, such as e.g., the hydrogen mitigation strategy or filtered venting systems.

In a collaborative effort of Ruhr-Universität Bochum (RUB) and Forschungszentrum Jülich GmbH (FZJ), multiple simulations of postulated accident transients in a generic Konvoi-type PWR (1300 MW_el / 70.000 m³ free containment volume) with a simplified nodalization and junction structure were carried out using the lumped parameter Containment Code System (COCOSYS) developed by GRS gGmbH. Both a medium break loss-of-coolant accident (MBLOCA) and a station blackout (SBO) scenario were investigated. Unmitigated reference calculations are used for comparative assessment with the respective mitigated cases putting special emphasis on the development of the gas composition inside the containment aiming at enhancing the general understanding of the H₂/CO combustion risk, particularly in the late phase of a severe accident.

Consequently, this paper gives a detailed overview of the simulations performed and includes a comprehensive discussion of the results. The work presented here was conducted within the framework of the European AMHYCO project (Euratom 20192020, GA No 945057).

Spray systems represent a critical safety feature of nuclear power plants. The performance and efficiency of such spray systems depend upon various parameters and boundary conditions. During a severe accident, the spray systems interact with the containment atmosphere, which may contain aerosols and iodine, thereby influencing the radiological source term. To assess thermohydraulic conditions, spray was injected into the THAI vessel, which was equipped with various measurement systems depending on the test objective. The cooling efficiency was investigated by injecting spray via both a nozzle and boreholes. The depletion of cesium iodide aerosol concentration was investigated using a spray system with a polydisperse droplet size spectrum. The removal of molecular iodine was examined with fresh and recirculating water spray at varying pH and iodine contents. The nozzle and boreholes tests revealed that the cooling efficiency is enhanced with an increase in drop height and a reduction in droplet size. The efficiency of the reduction of aerosol concentration by spray was found to be higher for larger particles than for smaller ones, as indicated by a shift in the particle size distribution towards smaller particle sizes. The efficiency of iodine removal by spraying deionized water is significantly higher than that of iodine-containing water from the sump at higher pH levels. In conclusion, this work presents a comprehensive set of experimental data that enhances the understanding and knowledge of the behavior of spray systems and its interaction with the containment atmosphere under accident conditions and can be used for code validation.

Small modular reactors (SMRs) present unique safety challenges and opportunities due to their compact, integral designs and reliance on passive safety systems. This study investigates the impact of containment and reactor pool modeling on the progression of severe accidents (SAs) in a SMR using ASTEC 3.1. The ASTEC code, recognized as the European reference tool for SA analysis, was applied to model a SMR featuring a thermal power of 160 MW, a submerged containment design, and fully passive cooling systems. However, the lumped-parameter approach and simplified subcooling models in ASTEC present challenges in accurately reproducing key phenomena in this SMR. The code must effectively capture passive heat transfer mechanisms under subcooling conditions, the intricate dynamics of natural circulation flows within large-pool volumes, and the in-vessel retention (IVR) process to ensure a consistent representation of SA evolution.

The study emphasizes the influence of modeling approaches for the containment and reactor pool on ASTEC results, specifically in terms of containment pressure, core degradation progression, hydrogen production, and fission product release. It discusses efforts to mitigate these limitations, highlighting the need for refined nodalization and validation through experimental data or comparison with best-estimate codes.

This work contributes to the broader effort to enhance the predictive capabilities of SA codes in replicating the behavior of passive safety systems, thereby ensuring the robustness of safety assessments for next-generation nuclear technologies.

The aim of this work is to investigate the behavior of the spray system within nuclear reactor containments. This mitigation system is often modeled at the system scale using 0-D modules, which provide conservative estimates of the gaseous environment conditions in the containment. The purpose of the WISDOM spray model within the CATHARE system code is to offer a more precise representation of the droplet phenomenology during accidental scenarios. To evaluate the impact of the various input parameters on the spray phenomenology in containment, sensitivity analyses on the WISDOM model are conducted. The objective is to assess the main parameters of interest related to the containment spray system, and to identify which parameters have the greatest influence on thermal exchanges between the droplets and the containment's gaseous environment. A comparison between the code predictions and experimental data is also presented, along with discussions of data from the CARAIDAS, TOSQAN and MISTRA experimental facilities.

The release of hydrogen into the containment during a severe accident in a nuclear power plant can lead to undesirable consequences, such as the deflagration or detonation of a combustible hydrogen-air mixture, posing a risk to containment integrity. During a severe accident, such as a Loss of Coolant Accident (LOCA), hydrogen production arises not only from the strong exothermic metal-steam oxidation in the fuel cladding but also from additional sources, including molten corium-concrete interactions and carbon monoxide release due to the reduction of carbonates in the concrete.

Pressurized Water Reactors (PWR) are designed with a large internal volume to mix and dilute the combustible gases that may be produced during a severe accident, intended to keep the gas concentrations below the combustion limit. Atmospheric stratification can, however, result in poor mixing of the combustible gases released, and regions with a combustible gas mixture. To understand and assess the hydrogen risk in a PWR containment, it is important to accurately model the process of atmospheric mixing with accident simulation codes.

System thermal hydraulic (STH) or lumped parameter codes are known to have inherent limitations in representing 3-dimensional mixing phenomena compared to CFD codes. Therefore, a comparison is made between the STH code SPECTRA and the CFD code FLUENT for the atmospheric mixing in the dome of a generic PWR containment during a LOCA. This work has been performed within the framework of the AMHYCO project (Euratom 2019-2020, GA-No-945057).

The growing demand for flexible power generation, particularly with small-scale advanced nuclear reactors integrated with other energy systems, requires load-following capabilities. These reactors must adjust to frequent power fluctuations, making advanced autonomous control systems essential for maintaining efficiency and safety. In this paper, we present a novel integrated hardware/software testbed designed to develop and evaluate advanced autonomous control strategies for small-scale advanced nuclear reactors. The testbed represents a shift from traditional nuclear power plant operations by incorporating machine learning-based digital twin technology. This allows nuclear systems to dynamically adjust their output, allowing load-following operation or integration with other renewable energy sources. The testbed comprises three main components. The first is a thermal-fluid facility with three loops and a control rod drive mechanism, simulating the operational characteristics of advanced nuclear reactors under various scenarios. The second component is the Control Process Automation (COPA) system based on the Open Process Automation Standard (O-PAS), providing a flexible control architecture using OPC-UA communications for seamless signal integration and access. The third component is a customizable control algorithm platform employing machine learning techniques such as Bayesian optimization and AI-Agent. This platform communicates with the thermal-fluid facility through the COPA system, enabling autonomous, real-time control adjustments based on varying power loads and operational conditions. Our results show that advanced autonomous control systems enhance load-following capabilities, improving adaptability and integration with renewable energy systems. This work paves the way for more resilient, efficient, and safer nuclear plant operations in an evolving energy landscape.

The eVinci™ Microreactor which is under development by Westinghouse Electric Company could bring a cost-competitive and reliable nuclear energy source to the world. The small size of the eVinci microreactor allows for transportability and rapid, on-site deployment.

Instead of a fluid-based primary coolant system normally seen in nuclear power plants, eVinci Microreactor adopts heat pipes to transfer heat from the reactor to the Primary Heat Exchanger (PHX). The heat pipe design enables passive core heat removal which eliminates numerous components needed in active coolant systems and makes the eVinci microreactor a pseudo “solid-state” reactor with minimal moving parts.

The eVinci Nuclear Test Reactor (NTR) is a nuclear test facility dedicated for eVinci microreactor’s development. The NTR will provide critical engineering information for analysis code validation to support commercial licensing. The NTR is a highly integrated design involving strong interactions among various systems and components. It can test the multidisciplinary physics governing how the nuclear power is generated, controlled, and converted to thermal energy. To support the NTR development timeline, a first-of-its-kind thermal analysis has been performed which created a full scale and integrated CFD model of fully coupled, multiple NTR thermal systems.

The high-fidelity CFD analysis notably improves the inputs being used for design completion of the NTR and helps to expediate the design progression of various NTR systems and components.

In this paper the development of the NTR integrated CFD model is presented. Results of the analysis are introduced. The potential applications of the model will be also discussed.

In advanced U.S. molten salt reactor (MSR) designs, inert gas, such as helium, can be introduced to remove fission products, but can also induce reactivity fluctuations by increasing the core void fraction. This challenge was first identified in the Molten Salt Reactor Experiment (MSRE) at Oak Ridge National Laboratory, where gas entrainment affected reactor physics. Gas-induced fluctuations remain a concern for MSR operation, necessitating accurate predictive modeling. The drift-flux model has been used extensively in thermal-hydraulic codes to predict two-phase flow dynamics, including void fraction, but rely on constitutive terms that are typically estimated using empirical correlations. These correlations are generally developed for vertical upward pipe flows in water–air systems, limiting their applicability to alternative fluids and flow orientations. This paper presents a machine learning (ML) methodology using a supervised learning approach to predict constitutive terms in the drift-flux model. Two supervised ML models were trained on computational fluid dynamics (CFD) data to predict the distribution parameter and mean local drift velocity. These models were combined to compute the mean drift velocity. The methodology was applied to vertical pipe flow simulations under varying thermal conditions. The ML predictions showed good agreement with CFD data, with most results falling within the expected time-dependent fluctuation bounds. The largest errors were observed near the gas injection region. Overall, this study demonstrates the feasibility of ML-based modeling for constitutive terms in two-phase flow and highlights the need for broader datasets and experimental validation.

Small Modular Reactors (SMRs) are garnering global attention as a transformative solution for sustainable and clean energy production. Compared to traditional large-scale nuclear power plants, SMRs face challenges such as potentially higher generation costs and limited construction and operation experience. The virtual small modular reactor (VSMR) platform has emerged as a groundbreaking approach to innovating nuclear reactor design and optimizing safety through advanced simulation and analysis. Recognizing its significance, the Korean government designated the VSMR platform project as one of the Global Top Strategic Research Working Group in June 2024, A key enabler for VSMR implementation is the acceleration of computational fluid dynamics (CFD) simulations. While state-of-the-art machine learning (ML) models have shown promise in accelerating unsteady CFD, critical gaps remain, including (1) applicability to complex geometries, (2) suitability for long-term simulations, and (3) the lack of benchmark studies targeting nuclear reactor applications. This study aims to address these gaps by constructing CFD datasets for helical coil steam generators, developing state-of-the-art ML models fitted to CFD simulations, and benchmarking their performance under the same conditions. To ensure scalability to complex geometries, three base ML algorithms were selected: deep neural operator (DeepONet), graph neural networks (GNN), and implicit neural representations (INR). Preliminary results confirm the successful training of these models within their respective algorithms and provide a comprehensive performance comparison. These benchmark studies are expected to inform future ML model development strategies and significantly advance its application in VSMR.

One of the preliminary steps in the design and safety analysis of nuclear reactor systems is the formulation of the Phenomena Identification and Ranking Table (PIRT). PIRT was introduced by the United States Nuclear Regulatory Commission as part of the Code Scaling Applicability and Uncertainty methodology. PIRT depends on experts’ inputs and insight, and its formulation is based on the joint consensus and agreement of a panel of experts. The outcome of the PIRT is significantly affected by the domain knowledge of the participating experts. Moreover, oratory skills, thinking patterns, and biases (such as confirmation bias and psychological biases) can also affect the outcome of the PIRT process.

PIRT requires systematic strategy and knowledge abstraction at different levels. Counterfactual reasoning and knowledge transfer from different disciplines are also needed depending on the application. In this work, we aim to leverage the recent developments in the area of multimodal Large Language Models (LLMs) to build an AI-driven multi-agent framework for the implementation of PIRT. Foundation models based on frontier LLMs, customized and adapted by finetuning, retrieval augmented generation and prompt engineering, are used as proxy experts to support knowledge abstraction, reasoning and information retrieval for PIRT formulation. As PIRT results are impacted by the thinking patterns and inherent biases of the participating experts, theory of mind perspective in LLM under different configurations of multi-agent collaborations are also tested and explored. The demonstration of the framework is presented using a case study on an advanced reactor application.

Nuclear reactor system involves multiple physical processes which are coupled. In general, the traditional design process depends on the linear iteration and the manual trial calculations, which faces the challenge of the “combinatorial explosion” issue caused by vast and complex problem space. In recent years, the rapid development of Artificial Intelligence (AI) technology has brought new insight into the paradigm innovation of nuclear reactor system design, which includes the following four fields: model construction and knowledge discovery, reduced-order accelerated solution, design parameter optimization, and generative AI-assisted design. Moreover, the optimization-driven design method can be considered as the key of intelligent design, which can support the realization of intelligent design at three levels: characteristic parameter, shape variations, and topological relationship. Also,the relevant application has been conducted in the reactor thermal-hydraulic field. The AI-integrated optimization design technology is expected to shift the nuclear reactor design concept towards “function-led design”, which can be extended or inherited in many fields and finally support the realization of generative and heuristic reactor design.

The interaction between cooling fluid and solid structures (rods, tubes) in nuclear power plants leads to flow-induced vibrations (FIV). These may cause material fatigue, fretting wear, and in worst case, loss of component integrity. The consequence of this might be high standstill costs due to longer or unplanned outages or safety issues like Steam Generator Tube Rupture accidents. Within the European GO-VIKING (Gathering expertise On Vibration ImpaKt In Nuclear power Generation) project, experimental and numerical efforts are performed to improve the understanding and analysis of FIV in nuclear power plants, as well as to develop and validate advanced numerical approaches for their prediction. Within the fifth work package of the project, activities to analyze the tube vibration behavior in the CEA’s AMOVI experiment were carried out at GRS. AMOVI deals with FIV occurring in tube configurations, exposed to a cross-flow. In this work, the FIV are investigated with a fluid-structure interaction (FSI) approach, based on a structural reduced-order model. Such models are of particular interest due to the excessive computational time necessary for the FIV evaluations. The reduced-order model for the structural domain MOR was coupled to ANSYS CFX for the FSI calculations presented in this paper. This FSI approach was validated against AMOVI data for a single flexible tube positioned in the center of a bundle of rigid tubes.

Fluid-induced vibrations (FIV) are a major cause of component failure in nuclear reactors and are of significant concern when extending operating reactor lifespans. The Go-Viking project aims to ensure that the licensed operating lifetime of aging nuclear reactors in Europe can be safely extended by improving understanding of FIV phenomena within steam generator tube bundles. To achieve this, the GOKSTAD experimental tube bundle has been created to collect FIV data for an inline cross-flow tube bundle operating at a higher Reynolds number than previously documented in the literature. In this presented work, we present results from high-resolution direct numerical simulations (DNS) of the GOKSTAD bundle for comparison with experimental data. Due to the computational cost of DNS, a reduced domain of the GOKSTAD bundle is used in these simulations, consisting of three rows with seven columns (five regular columns and two half-tube columns). The mass flow rate within the tube bundle is 15 m³/s, and the pitch-to-diameter ratio within the bundle is 1.44. The DNS is done using the Department of Energy code, NekRS, while the structural responses are simulated using the Multiphysics Object-Oriented Simulation Environment (MOOSE). Results include velocity fields, pressure fields and displacement data of the center tube, allowing direct comparison with measurements collected within the GOKSTAD bundle. The DNS FIV model generated from these results will support creation of fast-running FIV tools, including reduced-order models.

Key Nuclear Steam Supply System (NSSS) components, such as fuel rods and steam generator tubes, are highly susceptible to Flow-Induced Vibrations (FIV) as a result of the turbulent coolant flow. This can cause known failures of these components, such as Grid-To-Rod-Fretting (GTRF) wear and Steam-Generator Tube Rupture (SGTR), possibly leading to costly reactor outages. Historically, analytical and semi-empirical approaches were used to assess the impact of FIV on the components’ structural integrity. However, these are generally only able to give an order of magnitude estimate of the structure’s displacement. With the increase in computational power though, Fluid-Structure Interaction (FSI) simulations, two-way coupling detailed Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) codes, are being used more and more. Such FSI simulations are able to give increasingly better predictions, matching reference experimental data quite well, in particular in terms of vibration frequency and displacement amplitude. These simulations generally only consider cylinders undergoing relatively small displacements, avoiding contact. To capture GTRF or SGTR resulting from FIV, generally larger displacements are needed, along with contact between neighboring cylinders or between a cylinder and surrounding fixed structural components. The current work shows results of an initial investigation of performing FIV simulations involving structural contact. It considers a cylinder placed inside a channel and subjected to turbulent cross-flow. Different numerical and modeling techniques have been used to try to successfully resolve the large displacements and structural contact. These are presented, along with results of a first FIV simulation involving contact between the cylinder and the channel walls.

Understanding the behavior of flow-induced vibrations (FIV) is crucial for maintaining the safety of steam generators in nuclear power plants. If left unaddressed, vibrations can lead to tube wear, fatigue, and even failure, which can have profound safety consequences. In U-tube designs where two-phase cross-flow dominates, vibration-related issues are further exacerbated. Fluid-elastic instability is the primary mechanism underlying flow-induced vibration that may damage steam generator tubes. Although fluid-elastic instability in single-phase cross-flow has been extensively studied, its behavior in two-phase flows is less understood. The Horizon Europe project GO-VIKING addresses these challenges through experimental facilities designed to study two-phase cross-flow-induced vibrations. These setups focus on the fluid-structure interaction (FSI) between tube bundles and air-water cross-flows.

This paper presents numerical simulations of FIV in two-phase cross-flows. Simulations cover two-phase flows over single tubes and tube bundles. On the fluid side, we use a two-fluid model coupled with a population balance model to account for bubble poly-dispersity, coalescence, and break-up. The structure motion is modeled using a six-degree-of-freedom rigid body motion solver. The numerical results are validated against experimental data on bubble size distributions, void fractions, fluid-structure forces, and displacement spectra. The findings of this work advance the understanding of two-phase FIV, providing insights critical to the safe and reliable performance of steam generators.

In this work, the vibration characteristics of a propeller rotating in lead-bismuth eutectic (LBE) are studied using fluid-structure interaction (FSI) simulations, which are developed in parallel with an experiment performed at the Belgian Nuclear Research Center (SCK CEN). Both the simulations and the experiment are part of a larger campaign to develop a methodology for characterizing the vibrations in primary pumps of nuclear reactors using heavy liquid metal coolants. These coolants are of interest due to their use in Generation IV nuclear facilities such as MYRRHA , using LBE as a coolant, and LFR, using lead. The high density of this liquid can significantly alter the vibration characteristics compared to when used in air and water, and introduce mode coupling, a phenomenon that is not yet sufficiently understood in the context of heavy liquid metals. The simulations allow for an extensive analysis of the different vibration modes. The investigated propeller consists of three symmetrical blades and is operated at different rotational speeds. First, the structural eigenmodes are calculated in vacuum, using the finite element method (FEM). Afterwards, the fluid and propeller are combined in a two-way coupled FSI simulation. For each mode a particular excitation force is applied to the structure to facilitate the extraction of vibration characteristics by analyzing the free response of the system. The result is the eigenfrequency and damping ratio of that mode in LBE. The results show that this methodology allows for an accurate prediction of the measured vibration response in the test setup.

To improve the long-term operation of NPP, dedicated tools are needed to understand and predict the interaction between cooling fluid and solid structures that may lead to flow-induced vibrations. The paper focuses on a validation test case representative of a steam generator configuration.

In the GO-VIKING project, supported by Horizon Europe research and innovation funding, a new water loop named GOKSTAD has been designed and constructed at the von Karman Institute to characterize a single-phase flow field and study the fluid-structure interaction inside a 7*7 square lattice in cross-flow configuration. The facility is designed to operate up to a remarkable gap Reynolds number of 90,000; a significant leap beyond what is currently available in literature.

The paper will first present the facility's flow field characterization based on PIV measurements at the inlet of the test section, between the cylindrical rods of the lattice, and at the outlet of the bundle. The second part will present the mechanical design and characterization of the moving rigid cylindrical tube developed for the Fluid-Structure-Interaction study. The configuration studied consists of two vibrating tubes inline or side by side inside the square lattice, with a vibration of roughly maximum of 10% of the cylinder diameter.

The results presented are precious data for the numerical team in charge of fluid-structure interaction studies, providing high-resolution boundary conditions and flow field data. The final objective is to have medium-resolution numerical tools to assess structural vibrations in Steam Generators under single-phase cross-flow conditions.

The unexplored potential of compact heat exchangers for use in light water small modular reactors offers a promising area for improving nuclear technology. Micro-channel heat exchangers provide high thermal efficiency and compact designs, making them suitable for integral designs. However, there is a significant gap in understanding their performance under liquid-boiling conditions, and no comprehensive database currently exists. This highlights the need for more research.

This study focuses on a pre-test analysis of a microchannel heat exchanger from the E-SMR database, developed within the ELSMOR project for a light water small modular reactor. Two models are used to simulate the performance of the heat exchanger: one with RELAP5 and the other with computational fluid dynamics (CFD) using STAR-CCM+. The comparison between the two codes addresses the limitations of thermal-hydraulic system codes like RELAP5 in accurately modeling microchannel heat exchangers, prompting the need for CFD to improve confidence in the simulations.
The pre-test analysis shows good agreement between the models. These will be validated against experimental data from a facility being built at Politecnico Milano to test compact heat exchangers.

The coupling of neutronic and thermal-hydraulic phenomena is important for the multiphysics modelling of the transient behaviour of nuclear reactors (e.g., design basis accidents). In this study, we analyse the behaviour of soluble-boron-free (SBF) water-cooled small modular reactors (SMRs) using coupled neutronic and thermal-hydraulic models. These models are developed using the Serpent Monte Carlo neutron transport and the Sub-channel CFD (SubChCFD) coarse-mesh CFD (computational fluid dynamics) codes. Typical industrial nuclear thermal performance software utilise nodal neutron kinetics and sub-channel nuclear thermal-hydraulic methods to simulate transient behaviour, but these methods oversimplify the geometry and 3D behaviour of coolant flow.

Although CFD models offer a high-fidelity alternative, it is computationally demanding to perform reactor transients. This is due to the fine computational meshes required and the modelling of complex turbulent and multiphase flows. Recently, coarse-mesh computational fluid dynamics (CM-CFD) models have been developed to mitigate this issue. These models utilise a sub-channel-based “filtering” mesh upon which empirical frictional and heat transfer thermal-hydraulic correlations are computed. In addition, the CM-CFD models also solve the Reynolds-Averaged Navier-Stokes (RANS) equations on a coarse computational mesh. However, unlike other CM-CFD approaches, SubChCFD also integrates and utilises experimental data.

This paper uses the coupled model to perform a full-core steady-state simulation of an SBF small modular reactor nuclear fuel assembly design developed by Alzaben et al.

In a pressurized water reactor (PWR), unwanted boron dilution transients can be caused by a large safety or regulating valve opening. When diluted coolant flows into the reactor pressure vessel, the cross-flow of two coolants of unequal boron concentration locally decreases in the core, possibly inducing a prompt change of reactor reactivity with a high impact on safety.

Concerns have focused on the behavior of pressurized water reactors (PWR) operating with soluble boron fluid in the reactor coolant. For the current analysis, a comprehensive understanding of factors influencing flow mixing patterns and boron diffusion in the reactor core is pursued through numerical investigations utilizing 3D computational fluid dynamics (CFD) simulations. These simulations play a crucial role in enhancing reactor operation safety.

A scaled PWR reactor pressure vessel, simulating a one-loop with different initial conditions of flow rates and Reynolds numbers for both the coolant and the safety injection flow into the cold leg. The simulation utilizes a customized solver implemented in OpenFOAM that considers the boron transport model using a transient flow algorithm coupled with a standard k-epsilon turbulence model. Given the magnitude of these simulations. The results provide a 3D mixing pattern under boron dilution transient and agree with experimental data regarding the optimal conditions for the best mixing and diffusion behavior of boron distribution entering the reactor core. This occurs at a specific ratio of injection to Reynolds number in the cold leg.

Small Modular Reactors (SMRs) are gaining importance in addressing energy challenges. To facilitate the wider adoption of these energy systems, it is essential to develop simulation tools that accurately represent the SMR phenomena. In this context, multi-physics and multi-scale analyses provide deeper understanding of SMR behavior under accident conditions. In this study, the US-NRC neutronic core simulator code PARCS, the KIT in-house thermal-hydraulic code TWOPORFLOW, and the US-NRC system thermal-hydraulic code TRACE were utilized. The TRACE/PARCS/TWOPORFLOW coupling code was developed following the ICoCo methodology, which involves exchanging data fields through mesh interpolation. An explicit temporal coupling is implemented, on one hand PARCS and TPF solve the reactor core using a domain-overlapping approach. On the other hand, TRACE solves the rest of the primary circuit and the selected auxiliary systems using a domain-decomposition approach. The NuScale plant has been analyzed using this multi-scale, multi-physics tool, showing good agreement with the reference data. Future work may explore a semi-implicit temporal coupling to enhance simulation stability.

Small modular reactors (SMR) have emerged as next-generation nuclear power systems, offering enhanced safety, efficiency, and economic advantages. Among their critical components, helical coil steam generators (HCSG) have been extensively studied for their effective heat exchange capabilities. However, primary-side cross flow within HCSG could induce vortices and turbulent structures between tubes, resulting in non-uniform heat transfer and flow instabilities that negatively impact overall system stability. Large eddy simulation (LES) based computational fluid dynamics (CFD) can accurately capture this complex behavior but requires fine meshes and short time steps, leading to high computational costs. In this study, a deep learning-based reduced-order modeling (ROM) strategy is proposed to maintain both accuracy and computational efficiency in analyzing local flow regions between HCSG tube layers. Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD), and a nonlinear autoencoder are employed to reduce data dimensionality, followed by a Long Short-Term Memory (LSTM) network for predicting flow evolution. These ROM frameworks (POD-LSTM, DMD-LSTM, and Autoencoder-LSTM) are compared to identify the most effective approach for significantly reducing simulation overhead while preserving CFD-level predictive accuracy. The results indicate that linear methods effectively capture dominant features such as large-scale vortex formation and dissipation, whereas the nonlinear autoencoder emphasizes random flow diffusion and chaotic behavior. Notably, the POD-LSTM model demonstrates superior performance in predicting flow field dynamics, achieving higher coefficients of determination (R^2) compared to the other models.

The LUT Heating Experimental Reactor (LUTHER) is a Small Modular Reactor (SMR) concept designed for safe district heating. The project has a heat capacity of 24 MWth, which is sufficient for heating small communities and businesses. To improve the efficiency of heat distribution, it is crucial to locate the plant in close proximity to consumers. As a result, a primary design criterion is to maintain the highest standards of safety.

Many severe accidents in nuclear reactors, such as rapid reactivity injection and core meltdown, are largely prevented by the reactor core's design. To transfer decay heat to the ultimate heat sink after potential accidents, a fully passive system has been developed to transfer heat from the core to the environment through boiling, free convection, condensation and wall conduction, using bedrock as an intermediate heat sink. The presence of non-condensable gases significantly influences heat transfer and steam condensation, making the calculations more complex and design more challenging.

In this paper, heat fluxes in the heat exchanger from containment to bedrock were calculated and visualized using the TRACE version 5 system code software. The effectiveness of employing bedrock as a heat sink was evaluated, and essential design parameters for the heat exchanger were established. These parameters include optimal pipe spacing, the appropriate pipe depth for maintaining a low surface temperature, the pipe length and inclination angle to facilitate efficient condensate flow.

The objective of this study was to evaluate condensation heat flux q_c from steam and air mixture on a vertical flat plate, which is one of boundary conditions in CFD (computational fluid dynamics) analysis for thermal hydraulic behavior in a containment vessel during accident conditions. In our previous study, we carried out numerical simulation of wall condensation from saturated steam and air mixture on a vertical flat plate with the cooling height of 6 m by using the CFD code FLUENT, and evaluated effects of mixture velocity u_in on q_c. In this paper, we evaluated effects of steam mass fraction Y_s,in on q_c from saturated steam and air mixture on the vertical flat plate with the conditions of u_in = 0.53-3.2 m/s and Y_s,in = 0.226-0.68 by using the FLUENT code. The boundary condition for q_c, which was defined in the viscous sublayer, was used, and the size of the computational cell was 0.1 mm for the cells in contact with the condensation wall (where the dimensionless distance was y⁺ = 0.12-0.56). The q_c,CFD values computed with FLUENT were well expressed by an existing q_c correlation for forced convection (FC) condensation, but was a little larger than the q_c,cal values computed with an existing q_c correlation for natural convection (FC) condensation. The u_in value at the transition from FC to NC condensation became large for large Y_s,in due to large density difference.

The condenser is an important component in the secondary circuit of a nuclear power system. In marine applications, vibration and noise reduction are critical design goals of the condenser, with the heat transfer tube—its central element—playing a vital role in ensuring the reliability and longevity of the equipment. Two key physical phenomena occur within the condenser heat transfer tubes: condensation heat transfer and fluid-induced vibration. These phenomena are interdependent and continuously coupled. To investigate the vibration characteristics of heat transfer tubes during the condensation phase change, a visual experimental setup was designed. This setup allows for the observation of vibration behaviors and the analysis of how various parameters influence heat transfer performance. Modal tests revealed that temperature significantly impacts the natural frequency of the heat transfer tube, with the natural frequency decreasing as temperature increases. Dynamic tests demonstrated that the changes in volume and pressure due to condensation phase change are particularly significant at low steam flow rates. As steam velocity increases, the effect of condensation diminishes, and fluid shock becomes the dominant factor. Regarding heat transfer, an increase in the heat transfer rate leads to a higher vibration amplitude, while the vibration frequency decreases. These findings provide experimental and theoretical basis for optimizing condenser performance.

The application of a two-phase loop thermosiphon is evident in Passive Containment Cooling Systems designed to remove core decay heat following a Loss-of-Coolant Accident. It is characterized by two dominant effects, which are boiling and condensation. The phenomenon in practical applications usually includes the effects of noncondensable gas, however, only pure vapor cases are considered in the present study for simplicity.

The two fluid model (TFM) is widely applied in various code to analyze two-phase flow behavior in nuclear field. For the implementation of subcooled nucleate boiling, we use the RPI heat flux partitioning model in near wall region because it has been well described in literature and favoured in many modern CFD codes. Meanwhile, condensation rate in subcooled bulk is calculated by assuming zero resistance in vapor side via specifying an infinite value of vapor heat transfer coefficient. On the contrary to boiling model, only a limited number of film condensation models in TFM approach are present, especially for large-scale volume like the containment structure. Instead of resolving the thin film thickness, a subgrid liquid film model is implemented in wall-adjacent cells. Phase change rate at the cooling wall is computed by solving governing equations coupled with an additional mechanistic liquid momentum equation. In bulk region, a same approach as in boiling model is applied as we consider zero resistance condition for liquid side. Subsequently, the subcooled flow boiling and film condensation models are incorporated and specified in the corresponding domains to model a two-phase thermosiphon.

During a severe accident, the potential leaking of fission products (FPs) from a nuclear facility to the atmosphere represents a significant nuclear safety challenge. Accurate estimation of these releases is important to conduct an appropriate risk assessment and implement the necessary measures. To achieve this, IRSN conducts research dealing with the mitigation of FPs transported in a carrier gas injected through a liquid pool. This process, referred as 'pool scrubbing', can occur in several accident scenarios in light water reactors (PWRs, BWRs), including Filtered Containment Venting Systems (FCVS) or with the Steam Generator Tube Rupture (SGTR), as well as in nuclear-powered submarines or in new Small Modular Reactors (SMRs) using pressurised water.

Thus, experiments are currently being conducted to characterize bubble hydrodynamics and trapping of iodine compounds (decontamination factor measurements) on dedicated facilities, involving demineralized water and saline solution for different carrier gas injection flowrates at ambient conditions. In this context, advances results have been previously obtained on the hydrodynamics that occur along the pool [1] and on the retention of CsI aerosols [2] and volatile I₂. Building on this, a new study has been initiated to investigate the impact of a saline solution on these phenomena and to develop a more sophisticated bubble plume model.

First results suggest that saltwater generates smaller bubbles (except near the nozzle) and improves the retention of I₂ compared to clear water. Ultimately, these works will be used to enhance the pool scrubbing modelling implemented in the ASTEC integral code, developed by IRSN.

With the recent research on the miniaturization of nuclear power plants, it has become important to also miniaturize and modularize components, such as heat exchangers. Particularly, the steam generators used in newly developed SMRs (Small Modular Reactors) have adopted helical tubes instead of conventional U-tube designs to achieve compactness and enhance thermal efficiency. In PWRs (Pressurized Water Reactors), a loss of coolant accident (LOCA) leads to decrease the pressure and temperature of the primary side, causing the pressurized water to transform into two-phase steam. This steam flows downward from the upper shell side of the steam generator and condenses through the interaction with feedwater on the tube side. This study was conducted to evaluate the condensation heat transfer performance on the shell side under these conditions and to investigate the condensation heat transfer mechanisms. For this purpose, a test section was developed to assess the condensation heat transfer on the helical tube, and visualization experiments were performed to evaluate the behavior and thickness of the condensate film formed on the helical tube. Additionally, qualitative analysis of the condensation heat transfer mechanisms occurring on the helical tube was conducted based on the observed condensate film thickness from the visualization experiments and the measured heat transfer performance

Modern nuclear power plants often rely on passive systems, especially during severe accident scenarios. Systems like that utilize natural circulation and convection, which can challenge the capabilities of existing safety analysis codes. The forces governing the natural circulation phenomena are usually weak, and thereby, the natural circulation patterns can be easily disturbed. In accident analyses this may happen by physical phenomena or modeling/numerical issues. Therefore, the verification and validation (V&V) of these system codes are crucial for credible safety analysis to ensure the safety of current reactors and for licensing new designs, including Small Modular Reactors.

In this study, the authors analyze containment thermal-hydraulic phenomena using the MELCOR 2.2 code, drawing on selected experiments conducted at the Paul Scherrer Institute's PANDA facility. The focus is investigating natural convection and fluid circulation in containment-like geometries under accident conditions. As part of the preliminary analysis, the HYMERES HP6 experiments were chosen. In the tests, steam and He (to mimic H2) are injected into one of four PANDA vessels, to analyze circulation patterns between vessels, as well as atmosphere stratifications. The HP6 tests allow to explore various phenomena, including stratification, circulation, condensation, and the influence of non-condensable gases.

The results, which include sensitivity analyses, help identify containment phenomena that are well-represented by the MELCOR 2.2 code, as well as those that present challenges for accurate modeling. This work aims to contribute to potential future recommendations for improving the modeling of these complex phenomena.

Critical heat flux (CHF) can potentially cause catastrophic incidents in numerous thermal industries. At low-pressure conditions, due to high surface tension, the vapour bubbles grow in bigger sizes compared to the high-pressure conditions and may locally accumulate on the heated wall. Due to this, a local dry patch is formed on the heated wall causing a sharp rise in the wall temperature which is referred as DNB-type CHF. Therefore, CHF occurrence is the most crucial factor for ensuring the safe operation of thermal systems that experience coolant phase change. The present work predicts the subcooled flow boiling characteristics and CHF under low-pressure conditions in hexagonal fuel sub-assembly with plate-type spacer. In fuel assembly, spacer grids support fuel rods, reduce flow-induced vibrations, and increase coolant mixing. A WHFP model is employed with the EMF model to simulate low-pressure conditions. The Tolubinsky and Kostanchuk correlation for bubble departure diameter is modified to incorporate the bigger vapor bubble sizes that occur in low-pressure conditions. The current methodology demonstrates strong consistency when validated against the experimental data available for low-pressure conditions. The numerical analysis is further extended to investigate the influence of the spacer on subcooled flow boiling characteristics and the occurrence of CHF. The results show that the spacer acts as blockage, resulting in an increased pressure drop in the spacer's region and inducing a secondary flow within subchannels. In fuel sub-assembly with spacer, coolant velocity was found to be maximum at the spacer's position.

Accurate prediction of two-phase parameters in pressurized water reactors (PWRs) is crucial for the safety analysis of nuclear reactor cores. The refined subchannel model can enhance the spatial resolution of traditional subchannel codes by a factor of four. The ATHAS-H subchannel code, based on the refined subchannel model, has already completed the development of a single-phase flow and heat transfer calculation model. This study represents a continuation of previous work, developing a two-phase flow and heat transfer model for ATHAS-H based on a homogeneous flow model with slip ratio. The code was validated using experimental data from two different types of mixing grid crossflow experiments, the CE5×5 subcooled boiling experiment, and the PSBT bundle void fraction experiment. The validation included directional crossflow, subchannel outlet temperature, rod wall temperature, and void fraction. The results indicate that the ATHAS-H calculations are in good agreement with the experimental data. ATHAS-H can accurately reflect the non-uniformity of local parameters within subchannels caused by mixing grids and non-uniform power distribution in the rod bundle. This study demonstrates the advantages of high-precision subchannel code ATHAS-H in improving the accuracy of two-phase parameter predictions in PWRs. This capability lays a solid foundation for high-precision analysis of critical heat flux (CHF).

In LOCA, there are various uncertain variables that must be considered. These uncertainties determination have been developed by using simple random sampling method. Here, fuel burn-up must be considered and also thermal conductivity and random variables must be considered to derive staistic evaluation results. In this study, the developed SUPER code was used to perform SRS evaluation considering LODA optimization and uncertainty due to fuel burn-up. While considering how to apply the fuel burn up effect and thermal conductivity using the FRAPCON correlation, we introduce a method of fully automated evaluation using SUPER code for uncertainty calculation and optimization.

In this study, variables that should be considered fuel burn up condition, thermal conductivity, and uncertainty were selected to compare and review the PCT evaluation according to fuel burn up and the uncertainty distribution according to fuel burn up, and the most conservative evaluation results were derived. The evaluation results confirmed that the thermal conductivity and SRS statistical distribution results were limited aroung fuel burn up 30 MWD/kgU.In this study, 124 SRS(Simple Random Sampling) calculation is carred out by SUPER code.

However, the different burn up 7 cases between 0 MWD/kgU and 60 MWD/kgU are estimated.

Throught the sensitivity study, some conclusions are introduced as below:

1) Under various fuel burn up condition, in each case, 124 SRS calculations are carried out and PCT statistical distribution and 95/95 percent/accuracy results are introduced.

2) In high burn up conditions, PCT results are decreased by FQ burn down.

It is crucial to understand the behaviour of non-condensable gases (NCGs) in light water reactors (LWR) coolant systems, as their presence could exacerbate accidents and transients by interfering with heat transfer and flow paths, especially during long-term post-accident reactor cooling. The potential sources of NCGs in the reactor coolant system have been thoroughly investigated. However, despite the significant role that NCGs play in the reactor coolant system, there is a relative scarcity of published works addressing the details of the release and dissolution of NCGs. This paper presents previous research efforts on the release and dissolution of NCGs, covering experiments and modelling.

The release and dissolution of NCGs is an intricate phenomenon. When simulating the dissolution and release of NCGs, it is crucial to consider various physical aspects. These include the transport equation for dissolved gas content, release and dissolution rates, conservation equations for the gas phase, and the equations of state for a mixture of two components, where one component is water that may exist in liquid and vapour forms. This paper discusses the gaps in modelling NCG release and dissolution.

Additionally, the paper provides insights into the ongoing NCGDENSE project of LUT University of Finland which is funded by SAFER2028 (National Nuclear Safety and Waste Management Research Programme 2023-2028), which focuses on studying the release and dissolution of NCGs through analytical, experimental, and numerical methods. A separate-effect-test (SET) facility will be constructed to serve as a platform for direct NCG release and dissolution measurements.

A Loss of Coolant Accident (LOCA) might occur if there is a rupture in any of the piping systems linked to the reactor vessel. This rupture may lead to the continuous and uncontrolled loss of reactor coolant into containment. In the absence of an adequate emergency cooling water source, the subsequent increase in fuel temperature could cause damage to the fuel and the release of fission products. The use of best estimate codes and methodologies for simulating LOCA can offer detailed insights into the actual plant response, essential for evaluating the effectiveness of an emergency core cooling system. The TRACE thermal-hydraulics code was specifically developed to simulate transient scenarios in LWRs, including LOCA. This code was applied to simulate the full spectrum LOCA in several locations for BWR-6. The analysis was done using the actual plant configuration and operating conditions available from the core follow simulator. An advanced hot channel methodology was specially developed for these simulations. LOCA analysis for a specific BWR-6 proves the plant compliance to the applicable safety criteria and confirm the TRACE BWR-6 LOCA methodology applicability for the full spectrum LOCA analysis. In addition, this study helps to understand better the LOCA phenomenology as well as the plant response to LOCA transient.

When exposed to extreme conditions accompanied by loss of coolant accident (LOCA), the fuel rods experience swelling or, in severe cases, burst of fuel clad, in accordance with the heat up due to the loss of cooling performance during the accident. In such extreme conditions, the multiple deformation of fuel rods impairs coolable geometry, imposing further degradation of cooling performance with flow blockage. Nevertheless, the system code analysis has conventionally focused on the behavior of single hot pin, by which the details of its surroundings were lumped as averaged assembly-scale conditions. Thus, using the conventional modeling scheme, it is difficult to consider the effect of flow blockage accompanied by the deformation of individual fuel rods surrounding the hot pin of interest. Therefore, in this study, LBLOCA analysis has been performed on APR1400 plant using different modeling scheme for the reactor core by additionally modeling the individual fuel rods surrounding the hot pin in the subchannel-scale level. The effect of flow restriction with multiple deformation of fuel rods has been evaluated, using the thermal-hydraulic system code, MARS-KS. As a result, the clad expansion resulted in about 14% volume reduction in maximum within the subchannel where the hot pin was located. Despite of small deformation as such, the PCT of hot pin increased about 36K during reflood.

Natrium® reactor vessel design utilizes the multi-dimensional computational fluid dynamics (CFD) to investigate the various flow phenomena and heat transfer mechanisms to predict the temperature distribution and flow velocity of the sodium. CFD is one of the many tools utilized during the design phase to inform various engineering teams including but not limited to transient and safety analysis, structural design and analysis etc. As part of the validation and investigation of the prediction capability of the CFD, multiple legacy data is being investigated. MONJU reactor trip benchmark by IAEA-CRP is one of them as it is investigated within the present paper. It investigates specifically thermal stratification behavior in the upper plenum of sodium cooled reactor. Previous studies investigated uncertainties on the flow hole geometry and turbulence modeling. Present paper investigates a more recent second-generation URANS closure (STRUCT−ε) model. The approach aims at advancing the robustness of hybrid turbulence models by relying on the efficiency of an extensively validated anisotropic k−ε method, while locally including the optimum resolution of complex unsteady flow structures.

In Sodium-cooled Fast Reactors (SFRs), the sensitivity of neutron cross-sections is essential for understanding the complex relationship between core neutronics, thermal hydraulics, and reactor safety. SFRs utilize fast neutrons and liquid sodium as a coolant, which introduces specific challenges in heat transfer and neutron interaction. Sensitivity analysis of neutron cross-sections in these systems quantifies the effects of uncertainties in nuclear data on parameters like reactivity, neutron flux distribution, and power peaking factors. These parameters significantly impact the core’s thermal hydraulic behavior.

The interplay between neutronics and thermal hydraulics in SFRs is crucial due to the fast neutron spectrum and sodium’s high thermal conductivity. Variations in neutron flux and cross-section values influence localized heat generation, while changes in coolant temperature and flow affect cross-sections through feedback mechanisms. Proper modeling of these interactions ensures effective heat removal from the core, preventing excessive fuel temperatures and avoiding material degradation or fuel failure, especially during transients and accident scenarios.

In safety analysis, sensitivity calculations are vital for predicting the reactor’s behavior under normal and off-normal conditions, including critical events like Loss of Flow (LOF) or sodium boiling accidents. These analyses assess how cross-section uncertainties affect thermal hydraulic margins, guiding the development of design strategies to ensure safe reactor shutdown and decay heat removal. Sensitivity analysis thus plays a key role in optimizing SFR performance and safety by offering insights into how nuclear data uncertainties impact overall system behavior, leading to more robust safety measures.

Liquid Metal Fast Reactors (LMFR) are a promising technology for expanding nuclear energy to reduce carbon emissions from the energy sector. The ultimate goal of the project is to provide validation data for the Clad Damage Propagation (CDAP) module of SAS4S/SASSYS-1, a reactor safety code system. The Experiment on Pin Failure for LMFRs (ExPL) project at Oregon State University (OSU) aims to provide data on the heat transfer impingement due to fission gas ejection from an initial cladding failure event. The experiments in liquid sodium will consist of a 19-pin assembly with electrically heated surrogate pins in a liquid sodium flow loop. The test section will be instrumented with High-Definition Fiber Optic Temperature Sensors, placed inside capillaries in place of a solid wire wrap consistent with the simulated fuel assembly geometry. The temperature within the capillaries, determined by the heat transfer through the capillary, will necessarily be different from the heater rod surface. This paper details experiments in water and air that investigate the presence and magnitude of both spatial and temporal discrepancies and potential modes for mitigating observed error. These alternative, low-risk fluids, were utilized to establish a baseline understanding of this application of fiber optic sensors and to inform future experiments in liquid sodium.

The primary cooling loop in sodium-cooled fast nuclear reactors is achieved using a centrifugal pump immersed in liquid sodium. Under certain conditions, fluid vortices can be generated and develop into bubbles of the cover gas present on the sodium coolant free surface. This phenomenon, known as Gas Entrainment (GE), may have an impact on the reactor vessel design and on the core reactivity. The GE is difficult to predict and parameters influencing its occurrence are still poorly known. Simulations using Computational Fluid Dynamics (CFD) could help to better understand such phenomenon and identify the parameters that govern its occurrence. In this work, free surface flow simulations based on the Large-Eddy Simulations (LES) for flow hydrodynamics prediction combined with the Front-tracking method for interface modeling, were performed. It figured out that predictions of the interface dynamics is greatly influenced by the the element mesh size, on which depends the accuracy of the flow hydrodynamics prediction. Finer meshes allowed to better capture the instantaneous small eddies and local velocities, which enhanced the generation of the vortices. The coarse simulation predicted less intense pressure variations near the vortices, and smoother pressure distribution throughout the domain. On the contrary, the fine simulation exhibited more distinct clusters of high positive and negative vorticity, associated with more distinct low-pressure cores. This enhanced the development of large vortices moving along the free surface.

The Liquid Metal Cooled Fast Reactors (LMFRs) are one of the technologies being considered by the Generation IV International Forum (GIF). The unique geometric design of the rod bundle channels causes an uneven circumferential temperature distribution on fuel rod surfaces, further intensified by liquid metal's high thermal conductivity. This temperature variation may induce thermal fatigue damage to the cladding, threatening reactor safety. It is identified that the subchannel heat transfer characteristics in liquid metal reactors are predominantly influenced by the Peclet number (Pe) and the pitch-to-diameter ratio (P/D). Usually, Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) with turbulent models are employed to study heat transfer in liquid metal rod bundles, which fail to capture the anisotropic thermal transfer in liquid metal rod bundles, ignoring circumferential temperature differences. Conversely, Large Eddy Simulation (LES) offers detailed insights into flow and heat transfer phenomena. Accordingly, this study conducts a numerical investigation on hexagonally arranged fuel bundles using LES to explore the circumferential temperature distribution under varying Pe and P/D conditions. The LES results show that Pe and P/D can affect circumferential temperature non-uniformity. Moreover, considering the experimental costs, smaller hexagonally arranged fuel bundles with a non-prototypical cold wall are selected. Due to the cold wall effect, the central fuel rods exhibit smaller circumferential temperature differences compared to the outer rods. These findings highlight the critical impact of Pe and P/D on the circumferential temperature distribution of fuel rods, providing valuable theoretical guidance for the optimized design of liquid metal-cooled fast reactors.

Nuclear thermal hydraulic analyses generally employ system and subchannel codes to examine the safety and performance characteristics of a given reactor system. More recently, 3D CFD modelling has been widely used to produce higher fidelity analysis but such methods can mainly be used for local phenomena. This research seeks to develop a coarse-grid CFD model using a subchannel approach to compute wall effects so as to create a computationally cost-effective model for the two-phase flow dynamics within the nuclear reactor core. The subchannel CFD (SubChCFD) technique previously developed for single-phase flow at the University of Sheffield is first implemented in OpenFOAM^TM CFD solver. The 5X5 bare rod bundle case from the NESTOR experiment is used for validation. Model predictions are compared well against experimental data. This single phase model has then been extended to the homogeneous equilibrium two-phase flow model concept and models for the wall effects (including wall boiling) and phase crossflows are being developed. In the full paper, the OpenFOAM^TM implementation and validation for both single and two-phase boiling flows will be discussed and evaluated.

The presence of spacer grids and mixing vanes in a typical Pressurized Water Reactor Fuel Assembly leads to significant turbulence in the coolant sub-channels, which plays a very important role to enhance the heat transfer performance of the fuel assembly. In this preliminary work, OpenFOAM is used to build a single coolant channel model with fuel rods, spacer grid, and mixing vanes, with periodic boundary conditions, to study the complex fluid flow behaviour induced by the mixing vanes and spacer grid. The flow field results obtained from OpenFOAM with the Reynolds Averaged Navier-Stokes (RANS) turbulence models are found to match well with experimental results from the MATIS-H benchmark. In addition, multiple hyperparameters are varied to study their effects on computational resources required and stability, and accuracy of results.

The CFD task group of the OECD Nuclear Energy Agency (NEA) Working Group on Analysis and Management of Accidents (WGAMA) drives collaborative activities in Computational Fluid Dynamics for Nuclear safety studies since the early 2000s. This paper presents recent achievements and the current major objectives of the group, illustrated by examples of code benchmarks and reviews of reference documents such as the updated Best Practice Guidelines.

A recently published Technical Opinion Paper identifies main challenges towards the perspective use of CFD in safety studies. Several ongoing and future activities identified and initiated will be discussed. In the qualification process of scientific computational tools , the quantification of uncertainties (UQ) plays a major role in the estimation of the trust of a given evaluation. As far as CFD is concerned, several specificities, mostly induced by the computational cost have been recently analyzed within an expert group composed of CFD, UQ and data science specialists. This paper shares the outcomes and potential future activities on the topic.

In the context of the qualification process, identification of suitable application-oriented validation data is an important step. WGAMA is currently considering an important task concerning the update and extension of the CSNI Code Validation Matrix (CCVM) for reactor coolant system and containment thermal-hydraulic phenomena of current and advanced water-cooled reactor including SMR. In the field of CFD, a connected activity is foreseen on the identification and analysis of validation data for specific safety applications. The needs and way forward will be discussed within this paper.

To meet the requirements of three-dimensional numerical simulations for the flow
and heat transfer phenomena in nuclear reactors, this article introduces WINGS-CFD （Workbench of Intelligent Nuclear reactor desiGn and Simulation-Computational Fluid Dynamics）, an Computational Fluid Dynamics (CFD) code for nuclear reactors developed by Nuclear Power Institute of China, which is designed based on the object-oriented and hierarchical architecture principles with a high degree of extension. This article comprehensively outlines the overall design concepts of WINGS-CFD, covering aspects such as theoretical models, numerical discretization methods, and code architecture. Several numerical calculations for typical reactor scenarios involving flow and heat transfer conditions are conducted using WINGS-CFD and the commercial CFD software Fluent, and the results demonstrate that the computational accuracy of both codes is comparable. Furthermore, WINGS-CFD is capable of supporting large-scale numerical simulations of neutron transport and flow heat transfer with billions of cells and it exhibits superior parallel performance. This WINGS-CFD code provides an autonomous numerical technique for the fluid dynamics and heat transfer analysis of reactor systems.

In the present work, a novel methodology for the numerical simulation of single-phase flow in rod bundles, within a coarse-mesh context, is presented. The proposed approach aims to fill the gap between standard CFD and subchannel modeling, targeting a stronger balance between the accuracy of the numerical solutions and a reduced computational effort. For this purpose, different numerical techniques were designed and combined in custom applications within the OpenFOAM framework. In the first place, wall models for the turbulent quantities that rely on the use of empirical correlations were implemented. The use of these models reduces the traditional restrictions on the mesh refinement at the walls and consequently introduces significant gains in computational efficiency for a similar level of accuracy when compared to standard simulations. On the other hand, special numerical schemes were implemented to include the capability of handling piecewise linear pressure distributions in a finite volume context, i.e., discrete changes in pressure across selected locations that mimic the behavior of unresolved, localized geometrical scales. This approximation is used to model spacer grid effects without explicitly including the spacer grid in the geometry. Additionally, new numerical techniques that allow the use of different meshes for each equation are explored. The combination of the proposed coarse-mesh approximations is validated against high-resolution numerical simulations and experimental data.

With the advancement of nuclear technology, the demand for precise simulation of flow fields in reactor rod bundles has significantly increased. Traditional low-order eddy viscosity models often lack the accuracy needed for complex subchannel flow fields, while high-order numerical methods like Large Eddy Simulation (LES) provide high-fidelity flow structures but are computationally expensive, limiting their practical application. To address the challenge, this study introduces a Condition Adaptive Eddy Viscosity Turbulent Model (CAEVTM) tailored for specific subchannel conditions in rod bundle with Mixing Vane Grids(MVGs). The goal is to achieve a balance between high accuracy and low computational cost by integrating high-order numerical simulations with machine learning techniques. The research begins with performing scale-resolving simulation to obtain high-fidelity flow structures. Key physical quantities sensitive to subtle flow changes are then selected to ensure the model's responsiveness. Subsequently, gradient-based techniques are employed to calculate the sensitivity of each grid point, and a optimization method is used to optimize the correction coefficients, enhancing the model's accuracy. A neural network is then trained to map the operational conditions to the correction coefficients efficiently. Finally, the trained neural network is incorporated into the secondary eddy viscosity model to construct the CAEVTM. Results demonstrate that CAEVTM significantly improves the accuracy of flow field predictions in specific subchannels while greatly reducing computational costs. The proposed CAEVTM successfully combines high-order numerical simulations with machine learning techniques to achieve efficient and accurate simulations of flow fields in specific grid subchannels.

This study enhances the understanding of thermal effects on energy distribution in the near-wake region of flow over a heated sphere by analyzing time-resolved particle image velocimetry (TR-PIV) experimental data at elevated pressures (3 MPa). The experiment spans a wide range of Reynolds numbers (19,000–29,000) and Richardson numbers (0.5–2.0), conditions characteristic of opposed flow mixed convection. Key parameters, including mean and fluctuating velocities, were calculated from the acquired velocity vector fields, with uncertainties quantified. The unique contribution of this work lies in examining the lateral and streamwise expansion of the recirculation region as heating increases, and in comparing these results with isothermal conditions. Additionally, this study isolates the effects of natural convection by comparing time-resolved turbulent kinetic energy (TKE) at the streamwise center of the recirculating region for both heated and unheated cases. Spectral analysis was conducted on the Reynolds-decomposed streamwise and spanwise velocity components using Power Spectral Density (PSD), providing insights into the turbulence characteristics within and outside the wake region. These findings are particularly relevant to the design and safety of Pebble Bed Gas-Cooled Reactors (PB-GCRs) due to the similarity in geometry and operating conditions. This work contributes to advancing the understanding of mixed convection in nuclear reactor cooling systems, offering insights into thermal-hydraulic performance under elevated pressures and varied thermal conditions.

Pronghorn is a thermal-hydraulics computational tool developed using the Idaho National Laboratory's Multiphysics Object-Oriented Simulation Environment (MOOSE). It is designed to support Computational Fluid Dynamics (CFD) modeling, ranging from subchannel and porous media analysis to Reynolds Averaged Navier-Stokes (RANS) turbulence modeling. As an integral part of the MOOSE-based suite of tools, Pronghorn seamlessly couples with other MOOSE-based applications to simulate a variety of physical phenomena. This article highlights recent significant enhancements to Pronghorn's CFD modeling capabilities and demonstrates their application to advanced nuclear reactor designs.

The recent improvements in Pronghorn primarily focus on modifications to its turbulence modeling capabilities, near-wall corrections and numerical schemes. In terms of turbulence modeling, the two-equation k-ϵ and k-ω-SST models have been implemented and validated with both equilibrium and non-equilibrium wall treatments. Regarding numerical schemes, a second-order hybrid method for gradient computation has been developed, resolving issues related to solution artifacts on skewed computational meshes commonly found in the complex advanced reactor designs. Additionally, corrections for wall roughness, and curvature, and wall-channeling in pebble beds have been introduced in the near-wall modeling.

These developments enable more accurate simulations of advanced nuclear reactors. Two case studies are presented in this work: a pool-type Molten Chloride Reactor and a salt-cooled Pebble-Bed High Temperature Reactor. In both cases, the previous models in Pronghorn are compared with the new implementations, demonstrating the improved accuracy achieved with the updated models.

OECD-NEA has launched thermal hydraulic code validation benchmark for high temperature gas-cooled reactors using the High Temperature Test Facility (HTTF) data. KAERI has joined as a participant to compare the calculated results by GAMMA+ code with the experimental data and code-to-code. Based on full power operation assumption, the steady state temperature profiles by the different codes were compared. During the initial comparison process, it showed that the calculated results of each participant were slightly different. It was thought that it could be from different nodalization and modelling approaches. The feature of the real HTTF test has prismatic blocks with fuel compact holes and coolant holes. But, the computational nodes by the each system code were simplified due to limitation of system codes as equivalent cylindrical domain. Several modelling methods to the each radial node has attempted to get more close data. Steady, PCC and DCC events were analyzed with the best acceptable method in this benchmark.

The impact of optical errors from physical sources was studied to assess their influence on PIV (Particle Image Velocimetry) measurements and 3D photogrammetry reconstructions of pebble beds. This investigation provides guidelines for optimizing these physical parameters to ensure successful optical measurements in "large" pebble beds. In this context, a large pebble bed refers to one containing more than 1,000 pebbles, with a length of at least 10 pebble diameters in each direction. Previously published studies that use similar techniques have pebble beds up to 1000 pebbles in size, but with a depth of around 7 pebbles in the narrowest direction.

Alongside the error analysis results, preliminary PIV measurements are presented, including details on calibration methods and other aspects crucial for generating CFD-grade experimental data. This data is essential for validating CFD tools like NEK-RS, which are progressively improving toward fully resolving the flow dynamics within full-scale PBR (Pebble Bed Reactor) pebble beds. Finally, results from creating a 3D reconstruction of the experimental pebble bed will be discussed. This reconstruction is both as challenging as the optical flow measurements and equally important for generating high-resolution data relevant to simulation validation.

In the reactor core of HTR-PM, due to the structural materials such as graphite blocks and carbon bricks arranged in bulk, the coolant flow paths are complicated. A part of the coolant flows through narrow gaps between the structural materials without cooling the pebble bed, which affects the temperature distribution in the reactor core. Therefore, the accurate simulation of bypass flow is a key issue related to reactor safety. The vertical gaps between side reflectors are the main bypass flow paths.In this paper, the thermal hydraulic system code was employed to simulate flows in the pebble bed and vertical gaps, analyze the flow path of coolant under different bypass flows ratio, and explored the influence on the temperature distribution of the pebble bed and the side reflectors.The numerical results are proven to be in good agreement with experimental data and results by CFD. The model reasonably simulates the bypass flow of core coolant and the temperature distribution in the core. The results also shows that there are some flow paths different from the previous researches and there is the flow direction turning point of bypass flow in vertical gaps.This method solves the problem of high computational cost when using the CFD method to study bypass flows. It is able to calculate accurately while greatly reducing computing costs, which lays a good foundation for further safety analysis under accidents.

This study conducts multiphysics modeling of graphite prismatic blocks used in High Temperature Gas- cooled Reactors (HTGRs) by analyzing the mechanical and thermal property changes induced by neutron irradiation. Graphite conducts a critical role as a moderator, reflector, and structural material in HTGRs, and these properties are significantly dependent on the level of radiation exposure in high temperature and neutron irradiation environments. The radiation-induced creep and dimensional changes have a substantial impact on the structural stability of graphite components, making their assessment essential.

Through 3D structural simulations, insights into the mechanisms of creep stress and dimensional changes occurring at elevated temperatures are provided, enhancing the understanding of how these changes affect the structural stability of graphite. The stress analysis results including this creep phenomenon are expected to be fundamental for evaluating the failure probability of the graphite prismatic block designs.

Accurate prediction and assessment of core bypass flow are vital, as they affect the heat transfer and cooling efficiency of the reactor. To address this, coupled CFD and mechanical studies considering neutron irradiation and thermal expansion have been conducted. The volume expansion with neutron irradiation dose decreases the width of the bypass gap, which increases the pressure drop but increases the heat transfer efficiency by the coolant hole.

This research is expected to contribute to the reliability evaluation of graphite components in HTGRs and provide insights for future reactor core designs and operation, enhancing the stability and efficiency of helium cooling under radiation.

Severe accidents (SA) in nuclear power plants (NPPs) pose critical safety challenges due to the potential release of radioactive aerosols, particularly various iodine species. This study aims to develop advanced filtration technology to reduce the release of fission particles into the atmosphere during SA. Experimental tests were performed to measure the electrostatic precipitator’s (ESP) reduction efficiencies using caesium iodide (CsI, 5 g/l) particles, generated via the droplet-to-particle method. Varying electric voltages were applied across the ESP electrodes depending on the total flow rate to optimize the reduction efficiency. After optimising the operating parameters, the ESP achieved a mass and number filtration efficiency of ~90% for CsI particles, effectively capturing particles in the size range of 0.04–0.5 µm. These findings demonstrate the potential of optimised ESP technology in significantly enhancing NPP safety by effectively capturing radioactive aerosols during SA scenarios.

Estimates from the measurements after Fukushima accidents suggest that substantial part of the
total radioiodine release to environment was formed by volatile compounds, I2 and organic iodides.
The computational efforts to guess on the iodine behavior at an accident are very difficult to carry
out. For example, serious attempts to do such calculations integrally -like those performed in the
OECD BSAF-2 Project for Fukushima- were all limited to modeling of just aerosol forms of iodine.
As “almost anything” can influence the volatile iodine behavior at an accident, we now would like to
know which processes and parameters are really crucial and what might be possibly abandoned. This
cannot be resolved through thousands of runs of one particular containment iodine code (with a
different code, the results will be different). In this work we use engineering estimates, iodine codes,
and methods from the PRA.
We try to identify the processes and circumstances which do matter at the prototypical conditions.
We employ some dedicated Fukushima analyses, both the already published ones and also our own,
new calculations. Secondly, selected experiments and their simulations are analyzed, including
PHEBUS FTP-1 test which is an illustrative example of how the huge uncertainties in the iodine
modeling can influence the interpretation of an experiment.
The findings clearly indicate that the modeling of the volatile iodine formation and behavior is
needed for the basic understanding of what is happening with iodine. However, the focus on really
relevant processes and parameters is necessary. Otherwise we are lost in the plethora of
phenomena, the effects of many are easily smeared out given the significant uncertainties linked to
the iodine analysis.

During nuclear power plant accidents, substantial radioactive materials accumulated in the reactor core may release into the containment or environment, posing radiological hazards. Notably, 60–70% of the core-accumulated iodine inventory is released, with iodine-based aerosols and vapor representing dominant forms of fission products during such events. As a critical severe accident mitigation measure, nuclear power plants employ containment spray systems to depressurize the containment atmosphere and remove suspended radioactive fission products. Investigating the removal characteristics during spray processes is of significant importance for understanding the elimination mechanisms of radioactive iodine-based fission products under accident conditions. This study conducted a series of spray removal experiments using independently developed aerosol and iodine behavior experimental platforms. Results demonstrate that the removal processes of aerosols and iodine vapor generally follow an exponential decay pattern. The spray system rapidly removes aerosols and iodine vapor, with aerosol removal efficiency increasing proportionally to spray flow rate. Smaller droplet sizes resulted in higher removal efficiencies. Additionally, this work analyzed the iodine removal dynamics during spray processes and the speciation of iodine within the containment sump.

As the deployment of Small Modular Reactors (SMRs), particularly integral Pressurized Water Reactors (iPWRs) advances, understanding the behavior of radioactive releases under severe accident (SA) conditions is critical to ensure safety. This study investigates the source term during a selected set of SA scenarios, involving LOCA and non-LOCA type events, occurring in a submerged containment type of iPWR and evaluates the implications for Emergency Planning Zones (EPZs). Unlike traditional reactors, iPWR SMRs feature integrated primary systems, reduced reactor size, and passive safety mechanisms, which impact source term behavior and, subsequently, EPZ requirements. MELCOR is used in this study to develop conservative source terms estimates and MACCS is used to calculate radiological consequences. This research examines potential release pathways, the performance of passive safety systems, and containment responses. The study quantifies key parameters such as fission product release rates, containment retention effectiveness, and potential environmental impact, focusing on how these factors influence EPZ size and scope. It is observed that, with the Swedish dose criterion of the current regulatory framework, iPWRs do not necessitate a precautionary action zone (PAZ), but an urgent protective action planning zone (UPZ). Even in the most severe accident scenario, the UPZ is around 16.1km. Comparative analysis with conventional reactors identifies enhanced containment capabilities of iPWR SMRs, suggesting the potential for smaller EPZs.

Accurate assessment of radioactive source terms following severe accidents of nuclear power plant is critical for off-site consequence analysis and calculation of radioactive release frequencies. Currently, worldwide research institutions have conducted plenty of studies on uncertainty and sensitivities of nuclear power plant radioactive source terms based on Best Estimate Plus Uncertainty (BEPU) analysis method; however, studies on the impacts caused by actions from the Severe Accident Management Guidelines (SAMG) are limited. This paper first develops a procedure for uncertainty and sensitivity analysis of radioactive source terms for nuclear power plant (NPP) based on BEPU method, especially considering inclusion of SAMG actions. Secondly, integrated severe accident analysis code MAAP was used to build a model of China typical two-loop nuclear power plant and 200 MAAP input cases using Latin hypercube sampling method were generated through own developed sampling code. Then 200 cases were run by MAAP and statistical evaluated by self written code, and uncertainty and sensitivity analysis was performed. Uncertainty analysis results indicate that all selected parameters have certain influences on release source terms in containment intact release category; and sensitivity analysis shows that the impact of SAMG actions may far larger than those from severe accident phenomena or model uncertainties. This study highlights the importance of selecting accident sequences for release categories with particular attention to SAMG action uncertainties during source term calculation. The research provides valuable references for selecting representative accident sequences and conducting uncertainty/sensitivity analysis of radioactive releases following severe accidents of nuclear power plants.

Conventional analysis methods for nuclear reactors are inadequate for fulfilling high-fidelity computational demands, and many of them face challenges in achieving compatibility with a variety of distinct models. Furthermore, cross-platform computational approaches may encounter problems such as low computational efficiency, data transfer distortion, and incompatibility in analysis scales. In recent years, physics-informed neural networks (PINNs) and operator learning have emerged as an effective tool for solving partial differential equations (PDEs) governing physical fields. Their potential for application in multi-physics coupling computations within nuclear reactors is particularly noteworthy. This paper introduces deep reactor multi-physics network (DeepRMNet), a novel nuclear reactor multi-physics coupling computational framework combining operator learning and other deep learning methods. DeepRMNet decreases the computational deficiencies inherent in traditional numerical calculation programs, facilitating independent, coupled, and rapid predictions of physical fields such as material temperature field, neutron flux field and coolant flow field based on their physical constraints. The framework addresses challenges including variable material parameters, integral calculations, boundary conditions, eigenvalue functions and so on. In our test model, DeepRMNet has demonstrated favorable computational outcomes and coupling efficiency compared to conventional multi-physics coupling calculations. We argue that DeepRMNet offers a promising tool for reactor multi-physics coupling calculations and digital twin construction, with advantages over numerical calculation-based digital twins.

Introducing new parameters into neural networks often requires significant time, even when existing networks based on experimental data are available. This study proposes a novel approach for the reliability assessment of the Emergency Heat Removal System (EHRS), utilizing Physics-Informed Neural Networks (PINNs), which integrate new parameters into the neural network structure. By encoding new parameters directly into an existing network, this approach avoids the need to rebuild the network from scratch, significantly improving computational efficiency. As a result, PINNs deliver faster response times and enhanced accuracy, demonstrating superior performance compared to conventional neural networks. The method was validated through practical simulations under accident conditions, showing that PINNs outperform traditional models in terms of accuracy and computational efficiency.

The main coolant pump (MCP) is a critical component in transferring the liquid metal in the primary system and removing the decay heat of the core of lead-cooled fast reactors (LFRs), suffering a corrosion possibility from the liquid metal especially in the high-temperature and high-velocity working conditions. Accordingly, the flow field in MCP should be paid more attention in the optimal designing process besides the head and efficiency which are concerned by the traditional design approach. The present study addresses the complexities of multiple, interdependent design parameters for MCPs in LFRs, aiming to develop a surrogate model to obtain real-time solutions of the flow field in the MCPs under various structural and operation conditions. Firstly, numerical simulations were carried out to simulate the flow field structure of MCP under different design parameters, as well as provide some training data. Subsequently, a surrogate model was developed based on the physics-based modeling and the small-sample data from simulations, to enable real-time internal flow field obtaining under varying operating conditions. The model employs proper orthogonal decomposition to identify the primary modes of the flow field within MCP and utilizes a physics-informed neural network to compute the modal coefficients under specific parameters, thereby achieving order reduction and reconstruction of the flow field. Future work will primarily focus on the validation of the surrogate model using the experimental platform of the LFR main pump. Based on this model, a digital twin of the MCP will be constructed to facilitate rapid intelligent design and operational control.

This study addresses the inverse problem of identifying a sharp, two-dimensional heat source within a conjugate forced convection system. The problem is formulated as a linear under-determined matrix equation, which requires a strong sparsity-promoting regularization. A deterministic-Bayesian hybrid solution framework was employed. The deterministic solution process utilized an iterative reweighted norm (IRN) algorithm to solve the Lp-Lq minimization problem. The enhanced sparsity-promoting capability is obtained through a small q value. An adaptive hyperparameter selection strategy is used to ensure solution convergence and minimize the user influence on the solution process. As a next step, Bayesian inference, with a discontinuity-adaptive Markov random field (DAMRF) prior, quantified solution uncertainty by providing a statistical distribution on the identified heat source magnitude. While the deterministic approach effectively reconstructed coarse geometries, resolving fine features was limited by sensor spacing and noise magnitude. The Bayesian method added uncertainty information on heat source strength but did not modify the (non-perfect) reconstruction shape. The combined features of automated hyperparameter tuning and uncertainty quantification enhance the robustness and reliability of the methodology, offering the potential for application in monitoring thermal-hydraulic systems.

The high-fidelity, high-order spectral element code NekRS developed at Argonne National Laboratory is designed to take full advantage of modern high-performance GPU computing architectures. It has been actively used during the past decade to perform low-to-high fidelity Computational Fluid Dynamics (CFD) simulations in both simple and complex geometries. However, due to its open-source nature and the focus on flexibility and performance over user-friendliness, the case set up in nekRS is not as intuitive or accessible as commercial CFD codes. This complexity often results in a steep learning curve for new users, and setting up cases can consume a significant amount of time. Users must manually define various simulation parameters, which can be error-prone and challenging. This work introduces a specialized chatbot designed to assist users in setting up and managing simulation cases in NekRS. By leveraging a curated database of sample cases, the chatbot guides users through problem domain definition, boundary condition setup, and solver parameter configuration. Leveraging machine learning and natural language processing techniques, the chatbot is designed to interpret user queries, deliver context-aware responses, and recommend relevant case examples customized to individual requirements. Additionally, it can troubleshoot common setup errors and recommend optimization strategies for high-performance computing platforms. The chatbot’s integration into the NekRS workflow aims to improve efficiency, reduce setup errors, and enhance accessibility, ultimately accelerating case preparation and enabling broader adoption of NekRS.

Developing a digital twin model for the reactor upper plenum and hot leg is critical for accurate and real-time monitoring of flow and temperature distributions. However, the complex internal structures and flow fields make traditional CFD methods unsuitable for real-time computation. Furthermore, the significant three-dimensional transient mixing effects cause the flow field to be highly sensitive to inlet boundary changes, while models based on limited CFD data fail to respond effectively to transient dynamics. This study proposes an efficient and high-fidelity transient digital twin modeling method combining non-intrusive model reduction with Fourier transform. CFD simulations generate full-order transient flow data under varing inlet temperature distributions. Fourier transform is used to extract mean flow fields, spatially averaged amplitudes and frequencies as key descriptors for the model. Proper orthogonal decomposition (POD) and artificial neural networks (ANNs) construct a rapid prediction model, and genetic algorithms enable inversion of inlet temperature distributions and high-fidelity reconstruction of spatial flow fields using measurement data. The results show that the digital twin model can rapidly predict the full mean flow field, average amplitude, and frequency under given inlet temperature distributions, capturing complex transient flow behaviors. It also enables inversion of inlet temperature distributions and high-fidelity reconstruction of full spatial flow fields, providing a novel pathway for reactor digitalization.

Heat pipe reactors have broad application prospects in deep space power, military bases, marine power and so on. For system level analysis of heat pipe cooled microreactors(HP MicroRx), the coupling between neutronics analysis and thermal-hydraulics analysis was usually solved iteratively. This study aims at establishing a multi-physics coupled simulation framework for performing transient safety analysis of HP MicroRx. This simulation framework is based on the system analysis software RETA. RETA is a multi-physics solver framework for advanced nuclear reactors based on C++ and object-oriented design methods. This work includes the following subtasks: 1) developing the heat pipe modeling capability with a fully-implicit solution method; 2) deforming the geometry of the reactor core so that it’s convenient for the finite volume method(FVM); 3) using the Preconditioned Jacobian-Free Newton-Krylov(PJFNK) method to uniformly solve the heat pipe reactor. In the modeling of heat pipes, a one-dimensional compressible flow model was used to model the vapor core, a two-dimensional axisymmetric heat conduction model was used to model the heat pipe wall and wick region, and the heat pipe wick and vapor core were coupled through a conjugate heat transfer interface. The KRUSTY reactor was selected and analyzed using the above simulation framework. Simulation results match the experimental data produced by Los Almos National Lab well. To conclude, this work provides an accurate and reliable tool for safety analysis of heat pipe microreactors.

High-parameter pressurized water reactors (HP-PWRs) with plate-type fuel operate at a higher power density than conventional pressurized water reactors (PWRs). This is accompanied by higher void fractions and the potential presence of slug flow, which can significantly affect reactor neutronic behavior. However, most neutronics and thermohydraulics analyses for PWRs rely on subchannel codes, and the impact of subchannel homogenization remains uncertain for HP-PWRs. This study models slug flow and bubbly flow in both the XY and XZ planes to investigate the effects of void distribution resolution on neutronic behavior using RMC. For slug flow, subchannel homogenization results in a noticeable overestimation of keff in the XY plane. The maximum relative power deviation (MRPD) between the homogenized and reference schemes reaches 3.70% in the XY plane and 5.38% in the XZ plane. MRPD increases with increasing overall void fraction and gas slug void fraction, as well as decreasing gas slug width and length, while it shows limited sensitivity to variations in small bubble radius in slug flow. For bubbly flow, although void distribution resolution has only a marginal influence on keff, its impact on power distribution is non-negligible—especially as the bubble radius increases, the void distribution becomes more non-uniform, and the overall void fraction rises. The MRPD between the homogenized and reference schemes exceeds 2%. These findings highlight the potential inaccuracies introduced by subchannel homogenization in high-void, non-uniform flow environments. Fine-resolution void modeling is essential for accurate N/TH coupling in HP-PWRs, particularly in reactor safety analysis.

To analyze the startup process and load tracking operation characteristics of a heat pipe reactor with Brayton cycle for thermoelectric conversion, this study employs a hierarchical component model to establish simulation software for the heat pipe reactor system. The study analyzes the impact of key parameters in the Brayton cycle on power generation efficiency. By utilizing the control method of the PID model, the simulation of the heat pipe reactor startup is conducted through the control of Brayton’s rotor speed. The control of the rotor speed under normal operating conditions is achieved by controlling the filling amount of the secondary loop working fluid, thereby exploring the inherent safety characteristics and load tracking operation characteristics of the heat pipe reactor under controlled and uncontrolled rotor speed conditions. The results show that pressure ratio, degree of superheat, and the temperature at the inlet and outlet of the unit significantly affect power generation efficiency; the PID control model can simulate the startup process of the heat pipe reactor, and the rotor speed can be well controlled; compared to uncontrolled rotor speed, the controllable rotor speed results in smaller changes in power and thermal parameters such as fuel temperature during the system’s load increase and decrease processes, which is more conducive to the safety of the reactor core.

High-temperature heat pipes are promising devices for advanced microreactor technologies in terrestrial and space applications. Understanding their performance and safety characteristics is critical to the successful deployment of heat pipe microreactor systems. One key safety consideration influencing the design and operational limitations of heat pipes is the occurrence of dryout in the liquid-wick region. This study investigates the effects of temporary dryout conditions induced by pulsed heat inputs to the evaporator that exceed the capillary limitation. Using water as the working fluid, experiments were conducted to examine the transient response of the heat pipe’s external wall temperatures, internal liquid and vapor temperatures, and vapor pressure under pulsed heat input conditions. Pulse lengths were varied to control the duration and severity of the pulsed dryout conditions and study rewetting and the long-term effects on heat transfer performance. Spatial temperature profiles during transients were obtained using an optical fiber temperature sensor in the vapor core. Thermal resistance and hysteresis were evaluated under steady state conditions before and after pulses to assess their impact on overall heat pipe performance. This study provides valuable insights into the internal two-phase flow behavior during dryout and rewetting of the wick. The experimental data set can be used to benchmark numerical codes and validate computational models. Future work will investigate the effect of pulsed dryout conditions with alternative wick designs, varying filling ratios, and liquid metal high-temperature heat pipes to optimize their design and enhance resilience.

Advanced reactor designs will use sodium heat pipes as the primary means of heat transfer from the core block to the heat exchanger system. Such devices provide an efficient and reliable method for transferring heat over a small temperature gradient and at near-atmospheric pressures. However, robust experimental data is needed to better characterize these devices and provide validation metrics for the Sockeye simulation code. To meet these needs, several heat pipes will be manufactured and tested at high powers (~10 kW) to explore manufacturing repeatability, test operating limits, and measure the properties of the working fluid. This work summarizes the heat pipe design and optimization process used to determine the dimensions of the heat pipes that will be manufactured. Analytical expressions from a variety of sources were used to calculate a theoretical ideal design to meet multiple experimental goals. The wick geometry and properties were tuned to potentially encounter four power limits over the range of operation supported by the experimental facilities. To employ the analytical expressions, a simple yet novel averaging scheme was proposed to account for an annular gap surrounding the wick structure. This averaging scheme was applied to limiting experiments in the literature to evaluate its accuracy. Finally, numerical and analytical methods were applied to evaluate the heat pipe operating conditions to ensure the experimental facilities will be able to test the power limits.

High-temperature heat pipes are critical components in the core of solid-state reactor heat pipe cooled reactors, serving as the exclusive and essential means of heat transfer from the core to the energy conversion system. The Geyser Boiling Phenomena (GBP) of high-temperature heat pipes has a significant impact on the safety and stability of solid reactors. This investigation encompasses the design, fabrication, and testing of sodium heat pipes with varying filling ratios, ranging from 33.3% to 100.1%. An extensive array of experimental studies has been carried out to evaluate the heat transfer properties of these sodium heat pipes under diverse conditions, including different heat transfer rates and inclination angles. The results indicate that the design parameters and operational settings, such as filling ratio, heat transfer rate, and inclination angle, significantly affect the GBP of high-temperature heat pipes. This research combines experimental data with relevant theoretical analysis to establish a semi-empirical relationship for predicting the temperature fluctuation period caused by the GBP of high-temperature heat pipes. Furthermore, based on the improved network thermal resistance model, a GBP analysis model is proposed, providing valuable reference for the design and engineering application of heat pipe-cooled reactors.