Conference Agenda

Maldistribution in heat exchangers has a significant effect on heat exchanger performance, leading to the reduction of system performance. Maldistribution can be reduced by optimizing manifold design to evenly distribute the flow in the manifold. Recently, manufacturing of complicated distribution manifolds becomes feasible due to the development of additive manufacturing techniques which can fabricate products rapidly without using mold or tool. On the other hand, there are advantages of polymer materials, including low manufacturing cost, low weight, electrical insulators, and anticorrosion. In present work, a novel polymer distribution manifold is developed to reduce maldistribution in the heat exchanger. Then, the maldistribution reduction of the new designed heat exchangers is evaluated by a numerical model which leads to an optimal design.

Heat pumps provide an efficient path towards decarbonizing HVAC systems. There is a strong need to develop heat pumps (HP) that can operate on low-GWP refrigerants, have a low-power requirement and are compact, and can be efficient under challenging conditions. Microchannel condensers can be utilized for heat transfer and cooling for extremely high heat flux, and have applications in HVAC, heat pumps, and micro-refrigeration systems. Replacing the condenser in the heat pumps with microchannel condensers is a potential pathway to make the heat pumps more compact. For these devices, the flow patterns that determine the condensation heat transfer rate differ from conventional macro-channels, which presents unique modeling challenges. Opportunities exist to utilize high-fidelity computational fluid dynamical (CFD) simulations to accurately capture and model the flow pattern development for refrigerants key to global decarbonization goals (low -GWP refrigerants such as R-1234yf) and for operation in extreme weather conditions (i.e. extreme cold). This work aims to close the gap on the modeling front by incorporating device simulations including all the key physics leading to more predictive simulations aiding in the development of efficient microchannel condensers for HPs. Microchannel heat exchanger technology takes advantage of the high surface-area to volume ratio to provide efficient heat transfer; however, accurately modeling the multi-phase flow aspects of these problems can be challenging. We performed CFD simulations of a simplified parallel square microchannel geometry. Validation with experimental measurements was performed for the refrigerant Fluorinert FC-72. Good agreement is observed with experiments in capturing the liquid mass fraction as measured at the outlet for a range of operating conditions corresponding to varying the mass flowrate at the inlet and the spatial heat flux on the sides of the condenser. Qualitative flow map regimes, as well as quantitative data in the form of pressure-drop and heat-transfer coefficients, are utilized from the experimental results for validation of the model setup. The validated CFD setup is utilized to investigate the effect of microchannel geometry, orientation, and refrigerant properties on the pressure drop and heat transfer characteristics. Results are also shown for the effect of the refrigerant properties on the condenser performance. This work utilizes high performance computing (HPC) resources to accelerate CFD simulations of microchannel condensers and heat pump components and develop fast-running low-order models that the industry can leverage.

Fin-tube heat exchangers (FTHX) are a key component in heating, ventilation, and air conditioning systems, and enhancing their performance is essential for improving energy efficiency. While numerous studies have explored methods to improve FTHXs performance, the impact of splitter placement appears to not have been thoroughly investigated in open literature. Splitters may provide a more favorable balance between local heat transfer and pressure drop by eliminating the need for a fixed mass flux per tube. Instead, mass flux can be adjusted to optimize the tradeoff between refrigerant pressure drop and heat transfer. This study investigates the effects of applying splitter on the performance of a FTHX evaporator coil with three rows and 48 tubes. The coil is simulated in both wet and dry configurations, with airflow speeds ranging from 0.5 m/s to 2 m/s and a superheat of 11 K. The optimal placement of the splitter for using a near azeotrope, R410A, as the working fluid is determined by comparing several heat exchanger configurations using a validated segment-by-segment heat exchanger model. The FTHX performance is characterized using the model predicted capacity, pressure drop, and the ratio of the capacity to pressure drop. The model predictions suggest that placing the splitter at the beginning of each circuit of the coil will lead to a ratio of capacity to pressure drop about three times higher than that of the baseline heat exchanger.

In this study, three of the most traditional finned-tube heat exchanger configurations were numerically evaluated using an extensive range of air-side core design parameter combinations. The main objective is to understand the impact of each design parameter on the heat exchangers performance, to investigate the typical and optimal results of each heat exchanger concept, and to conduct a comparative analysis between them. The Chilton-Colburn j-factor analogy, the Fanning friction f-factor, and the ratio of 𝑗/𝑓 were chosen as the dimensionless performance indicators. Utilizing correlations numerically regressed from Wang et al.’s (1997, 1999, 2000) wind tunnel experiments, the plain, the wavy and the louvered finned-tube heat exchangers were analytically investigated. To guarantee the full exploration of the mean and the best performance of the heat exchangers cores, their design parameters were widely combined in a full-factorial Design of Experiments (DOE) evaluation. Depending on the number of design parameters of the heat exchanger type, an order of magnitude of 10,000 to 100,000 combinations were analyzed for each core configuration. The core design parameters were varied between dimension limits experimentally assessed by Wang et al. (1997, 1999, 2000). Python and Engineering Equation Solver (EES) scripts were employed to model the heat exchangers correlations, their heat transfer and discharge loss performance, and to determine all DOE combinations and postprocessing. A sensitivity analysis was first conducted to indicate which heat exchangers’ design parameters contribute the most to the core performance increase. Afterwards, all heat exchangers combinations were plotted in j- to f-factor point cloud charts to compare their performance range between each other. Both indexes give a dimensionless approach of all core combination possibilities among the heat exchangers, resulting in a fairer comparison criterion within the proposed universe of combinations. Statistical filtering was also conducted to remove possible numerical outliers, delivering the performance boundaries for the plain, the wavy and the louvered finned-tube heat exchangers. Ultimately, the louvered heat exchanger exhibited the highest mean 𝑗/𝑓 factor of 0.3634, among all heat exchangers, followed by the wavy and the plain finned-tube core, with -44.0% and -52.4% less performance, respectively. Therefore, the extensive DOE study results, with the performance charts and indicators, corroborate with different past references showing a greater advantage of the louvered heat exchanger compared to the wavy and the plain configurations, which are both closer to each other. Additionally, among all DOE combinations, this study provides the highest performing design parameters setup for each heat exchanger type that delivers the greatest 𝑗/𝑓 factor results. The louver configuration achieved an optimal 𝑗/𝑓 of 3.2510, followed by the plain and the wavy concepts, which exhibited peak performance reductions of -40.9% and -86.1%, respectively.

Microchannel heat exchangers are widely used in the automotive industry and are becoming increasingly popular in the air-conditioning and refrigeration applications. The heat transfer performance perdition of microchannel heat exchangers is of great interest. However, the complexity of the heat transfer processes in these exchangers presents a significant challenge in accurately predicting their performance. Traditional methods often lead to excessive computational resource consumption due to their computational complexity. Machine learning models as a data-driven method can handle complex, non-linear data, and present a promising solution. In this study, we compared various machine learning algorithms to predict heat exchanger performance. We employed Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and Random Forest (RF) as prediction models. The training data are generated from Computational Fluid Dynamics (CFD) models. The inputs for these algorithms are the mass flow rates and inlet conditions of the fluids, while the output variables include the outlet conditions, capacity and pressure drops. Furthermore, we evaluated different fin structures and incorporated dimensionless parameters such as Reynolds number (Re), and Nusselt number (Nu) into our machine learning models. This method integrates dimensionless numbers into machine learning algorithms, enhancing the interpretability of the prediction results. The validation and evaluation of these algorithms have demonstrated that machine learning models which incorporate dimensionless parameters as inputs possess higher predictive accuracy. This approach significantly enhances the capability to forecast the thermohydraulic efficiency of heat exchangers across various fin geometries, proving their utility in advanced thermal system design.

The primary aim of this study is to simulate a heat exchanger employed in transient cyclic processes, specifically one comprising a coiled tube integrated into an accumulation tank. The tube allows for an efficient heat exchange, while the tank is able to dampen the oscillations of the cycle.

While existing research predominantly focuses on heat exchangers in steady-state configurations, this work addresses the unique challenges posed by cyclic behaviors inherent in certain industrial processes.

In many manufacturing scenarios, heat exchangers exhibit cyclic behaviors due to the intermittent nature of the processes they support. For instance, in processes like injection molding for plastics, cooling is required during one phase while the system remains idle in subsequent steps. Our study focuses on the simulation of a heat exchanger under such transient conditions.

To achieve a comprehensive understanding, we employ a dual approach using both 1D transient models and 3D Computational Fluid Dynamics (CFD) transient models. The utilization of a 3D CFD model offers a deeper insight into the intricacies of the system, providing more accurate results under specific cases and operational conditions. In contrast, the 1D model doesn’t provide as accurate results and details, but is computationally much less expensive, facilitating multiple parametric simulations to explore diverse working conditions and assess the impact of design changes.