Mesoscopic Modelling of Unsaturated Moisture Transfer in Hetrogeneous Limestone

2009 ◽  
Author(s):  
S. Roels ◽  
J. Carmeliet ◽  
H. Hens
Keyword(s):  
Moisture Transfer ◽  
Mesoscopic Modelling

Mathematical Models of Papermaking

2001 ◽  
Vol 6 (1) ◽  
pp. 9-19 ◽  
Author(s):  
A. Buikis ◽  
J. Cepitis ◽  
H. Kalis ◽  
A. Reinfelds ◽  
A. Ancitis ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Initial Value Problems ◽  
Moisture Transfer ◽  
Bound Water ◽  
Drying Process ◽  
Initial Value ◽  
First Order ◽  
Heat And Moisture ◽  
The Mathematical Model ◽  
The Web

The mathematical model of wood drying based on detailed transport phenomena considering both heat and moisture transfer have been offered in article. The adjustment of this model to the drying process of papermaking is carried out for the range of moisture content corresponding to the period of drying in which vapour movement and bound water diffusion in the web are possible. By averaging as the desired models are obtained sequence of the initial value problems for systems of two nonlinear first order ordinary differential equations. 

A model for non-Fickian moisture transfer in wood

10.1617/14036 ◽  
2004 ◽  
Vol 37 (273) ◽  
pp. 615-622 ◽  
Author(s):  
K. Krabbenhoft
Keyword(s):  
Moisture Transfer

Mesoscopic modelling of concrete material under static and dynamic loadings: A review

2021 ◽  
Vol 278 ◽  
pp. 122419
Author(s):  
Zhangyu Wu ◽  
Jinhua Zhang ◽  
Qin Fang ◽  
Hongfa Yu ◽  
Ma Haiyan
Keyword(s):  
Concrete Material ◽  
Dynamic Loadings ◽  
Mesoscopic Modelling

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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