CFD Modelling With Buoyancy Effects for a Heat and Moisture Transfer Ceiling Panel

2011 ◽  
Author(s):  
Melanie Fauchoux ◽  
Carey Simonson ◽  
David Torvi ◽  
Prabal Talukdar
Keyword(s):  
Flow Field ◽  
Moisture Transfer ◽  
Cfd Model ◽  
Heat And Moisture Transfer ◽  
Cfd Modelling ◽  
Flow Field Characteristics ◽  
Computational Fluid Dynamics Cfd ◽  
The University ◽  
Heat And Moisture ◽  
Insight Into

A heat and moisture transfer panel (HAMP) capable of simultaneously transferring heat and moisture to/from a space to improve indoor air conditions is being developed at the University of Saskatchewan. Experiments have been performed for different air conditions to simulate heating, cooling, humidification and dehumidification of the air by the HAMP. A latent effectiveness value is calculated for each test to show the performance of the HAMP. The HAMP has the highest effectiveness (∼45%) when used to cool the airflow. When used to heat the airflow, the effectiveness is much lower (∼25%). This difference can be attributed to the presence of large buoyancy forces during cooling in comparison to heating. To observe the flow field characteristics under the varying test conditions, a computational fluid dynamics (CFD) model is developed. The CFD model is able to provide a better insight into the features of the flow field. The presented streamlines and isotherms exhibit the effect of buoyancy for various conditions and help in understanding the experimentally determined effectivenesses.

scholarly journals Application Method of a Simplified Heat and Moisture Transfer Model of Building Construction in Residential Buildings

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4180
Author(s):  
Joowook Kim ◽  
Michael Brandemuehl
Keyword(s):  
Latent Heat ◽  
Moisture Transfer ◽  
Residential Buildings ◽  
Building Energy ◽  
The United States ◽  
Building Envelope ◽  
Outdoor Environment ◽  
Transfer Model ◽  
Heat And Moisture Transfer ◽  
Heat And Moisture

Several building energy simulation programs have been developed to evaluate the indoor conditions and energy performance of buildings. As a fundamental component of heating, ventilating, and air conditioning loads, each building energy modeling tool calculates the heat and moisture exchange among the outdoor environment, building envelope, and indoor environments. This paper presents a simplified heat and moisture transfer model of the building envelope, and case studies for building performance obtained by different heat and moisture transfer models are conducted to investigate the contribution of the proposed steady-state moisture flux (SSMF) method. For the analysis, three representative humid locations in the United States are considered: Miami, Atlanta, and Chicago. The results show that the SSMF model effectively complements the latent heat transfer calculation in conduction transfer function (CTF) and effective moisture penetration depth (EMPD) models during the cooling season. In addition, it is found that the ceiling part of a building largely constitutes the latent heat generated by the SSMF model.

Simultaneous determination of thickness, thermal conductivity and porosity in textile material design

2016 ◽  
Vol 24 (1) ◽  
Author(s):  
Dinghua Xu ◽  
Peng Cui
Keyword(s):  
Thermal Conductivity ◽  
Human Body ◽  
Moisture Transfer ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Optimal Solution ◽  
Comfort Level ◽  
Textile Material ◽  
Heat And Moisture Transfer ◽  
Heat And Moisture

AbstractThe thickness, thermal conductivity and porosity of textile material are three key factors which determine the heat-moisture comfort level of the human body to a large extent based on the heat and moisture transfer process in the human body-clothing-environment system. This paper puts forward an Inverse Problem of Textile Thickness-Heat conductivity-Porosity Determination (IPT(THP)D) based on the steady-state model of heat and moisture transfer and the heat-moisture comfort indexes. Adopting the idea of the weighted least-squares method, we formulate IPT(THP)D into a function minimization problem. We employ the Particle Swarm Optimization (PSO) method to stochastically search the optimal solution of the objective function. We put the optimal solution into the corresponding direct problem to verify the effectiveness of the proposed numerical algorithms and the validity of the IPT(THP)D.

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