ANALYTICAL EXPRESSIONS FOR A SOLUTION OF CONVECTIVE HEAT AND MOISTURE TRANSFER EQUATIONS IN THE FREQUENCY DOMAIN FOR LAYERED MEDIA

Author(s):  
A.L. Karchevsky ◽  
B.R. Rysbayuly
Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4180
Author(s):  
Joowook Kim ◽  
Michael Brandemuehl

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.


Author(s):  
Dinghua Xu ◽  
Peng Cui

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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