Prediction of transport properties of wood below the fiber saturation point – A multiscale homogenization approach and its experimental validation. Part II: Steady state moisture diffusion coefficient

2011 ◽  
Vol 71 (2) ◽  
pp. 145-151 ◽  
Author(s):  
J. Eitelberger ◽  
K. Hofstetter
Keyword(s):  
Diffusion Coefficient ◽  
Steady State ◽  
Transport Properties ◽  
Experimental Validation ◽  
Moisture Diffusion ◽  
Fiber Saturation Point ◽  
Saturation Point ◽  
Moisture Diffusion Coefficient ◽  
Homogenization Approach ◽  
Multiscale Homogenization

Modeling of Transient Moisture Diffusion in Wood below the Fiber Saturation Point

2011 ◽  
Vol 312-315 ◽  
pp. 455-459
Author(s):  
Johannes Eitelberger ◽  
Karin Hofstetter
Keyword(s):  
Steady State ◽  
Moisture Diffusion ◽  
Transport Processes ◽  
Fiber Saturation Point ◽  
Saturation Point ◽  
Transient Transport ◽  
Fiber Saturation ◽  
Physical Background ◽  
The Difference ◽  
Near Future

During the last two decades the macroscopic formulation of moisture transport in wood below the fiber saturation point has motivated many research efforts. From experiments the difference in steady-state and transient transport processes is well known, but could not be explained in a fully physically motivated manner. In the following article, first the microstructure of wood is depicted, followed by a description of the physical background of steady-state and transient transport processes in wood, and thereon based mathematical formulations. For a correct macroscopic description of transient transport processes, three coupled differential equations have to be solved in parallel, which is done using the finite element method. The validation of the whole model by comparison of model predictions with experimentally derived values is currently in progress and will be published in near future.

scholarly journals Evaluation of the Mass Diffusion Coefficient and Mass Biot Number Using a Nondominated Sorting Genetic Algorithm

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 260 ◽  
Author(s):  
Radosław Winiczenko ◽  
Krzysztof Górnicki ◽  
Agnieszka Kaleta
Keyword(s):  
Genetic Algorithm ◽  
Diffusion Coefficient ◽  
Biot Number ◽  
Moisture Diffusion ◽  
Absolute Error ◽  
Mass Diffusion ◽  
Precise Determination ◽  
Nsga Ii ◽  
Moisture Diffusion Coefficient ◽  
Nondominated Sorting

A precise determination of the mass diffusion coefficient and the mass Biot number is indispensable for deeper mass transfer analysis that can enable finding optimum conditions for conducting a considered process. The aim of the article is to estimate the mass diffusion coefficient and the mass Biot number by applying nondominated sorting genetic algorithm (NSGA) II genetic algorithms. The method is used in drying. The maximization of coefficient of correlation (R) and simultaneous minimization of mean absolute error (MAE) and root mean square error (RMSE) between the model and experimental data were taken into account. The Biot number and moisture diffusion coefficient can be determined using the following equations: Bi = 0.7647141 + 10.1689977s − 0.003400086T + 948.715758s2 + 0.000024316T2 − 0.12478256sT, D = 1.27547936∙10−7 − 2.3808∙10−5s − 5.08365633∙10−9T + 0.0030005179s2 + 4.266495∙10−11T2 + 8.33633∙10−7sT or Bi = 0.764714 + 10.1689091s − 0.003400089T + 948.715738s2 + 0.000024316T2 − 0.12478252sT, D = 1.27547948∙10−7 − 2.3806∙10−5s − 5.08365753∙10−9T + 0.0030005175s2 + 4.266493∙10−11T2 + 8.336334∙10−7sT. The results of statistical analysis for the Biot number and moisture diffusion coefficient equations were as follows: R = 0.9905672, MAE = 0.0406375, RMSE = 0.050252 and R = 0.9905611, MAE = 0.0406403 and RMSE = 0.050273, respectively.

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