Numerical Analysis of Condensation On The Surface of Air Handling Unit
1Western University, Canada; 2XNRGY Climate Systems ULC
Condensation on the surface of an Air Handling Unit (AHU) can interfere with energy efficiency, air quality and cause damage to the mechanical equipment and building. The fundamental calculation of condensation is complex due to the intricate interaction between the AHU surface and its environment. Realistic modeling of conduction through the AHU walls or roof and convective heat transfer distribution over the surface of the AHU is crucial to assess to avoid condensation occurrence. The present study investigates thermal bridging effects across the walls or roof of panel joints and condensation occurrence on the surface of the AHU, considering the effect of thermal insulation, temperature difference, and air velocity. The momentum and heat transfer in the AHU are evaluated using high-resolution 3D steady Reynolds-Averaged Navier-Stokes (RANS) computational heat transfer and fluid dynamics simulations. The airflow inside the unit is considered turbulent forced convection, and the external airflow is assumed natural and forced convection. The conditions for the condensation occurrence are assessed, and a correlation between the thermal and physical properties of the AHU construction and the surface temperature distribution will be developed.
Can 0.3 Micrometer be Commonly Assumed as MPPS for Mechanical Filters Used in General Ventilation?
1Concordia University, Canada; 2Institut Robert-Sauvé en Santé et Sécurité du Travail, Canada
ISO 16890 (2016) and ASHRAE 52.2 (2017) standards, referring to the ventilation filter requirements, test the filtration efficiency of ventilation filters at the minimum size of 0.3 micrometers. These two recent standards assume that this particle size corresponds to the Most Particle Penetration Size (MPPS) of mechanical filters. However, studies on mechanical media have shown that MPPS could shift to smaller particles when operational conditions change (in particular filtration velocity) and when the medium’ s characteristics vary (as the fiber diameter). The literature then mentions rather a size range from 100 nanometers to 300 nanometers.
A laboratory test bench dedicated to the filtration performance of ventilation filters allowed to obtain experimental data for the MPPS study according to different conditions of use (filter’s MERV, filtration velocity). This bench was validated to obtain reproducible efficiency measurements as a function of polydispersed NaCl particles with a diameter ranging from 20 nm to 500 nm.
The results show that MPPS is still observable, and greater than 100 nm. Measurements are consistent with previous studies on ventilation filters and allow to complete their information on the filters’ MPPS. Indeed, the results show that the range of 150 – 500 nm is a better MPPS estimation, unlike the fixed diameter of 300 nm, in the conditions used in this study.
An Integrated Model for Ventilation, Energy Efficiency with Noise Characterization and Measurement in the Smart Building
Monarchy of Concordia, Wellstar Beacon Labs, India
An environmental stressor such as noise and air pollutants may have detrimental effects on various aspects of health, especially in the built space. The unwanted intensity of a wave is the propagation of noise due to the transmission of energy source waves (viz. physical agents) such as sun, light, sound, heat, electricity, fluid, and fire. The noise scales/charts are developed from the newly devised noise measurement equations and their units by the author. Indoor air pollutants of carbon dioxide concentration inside buildings have been related to general ventilation adequacy and are commonly monitored by DDC control systems as a measure of indoor air quality and ventilation adequacy. The objective of this paper is to develop the internet of things (IoT) model based on an energy-efficient ventilation system in the smart building targeting energy savings through identifying the unwanted energy intensity. The model also achieves a reduction of the concentration of indoor pollutants such as carbon monoxide, carbon dioxide, and refrigerant gas through an energy-efficient and safe ventilation system. The model records data points and preprocess to check ventilation and identify noise and energy intensity in BMS integrated smart buildings. An IoT scheme is developed for noise characterization and an energy-efficient ventilation system for integration with existing smart buildings. The proposed system achieves significant energy savings in a healthy air-conditioning environment.