Numerical inverse estimation of the thermal diffusivity and the adiabatic limit temperature of three types of unfired clay bricks using flash method and global minimization algorithm

2018 3rd International Conference on Energy Materials and Applications

能源学;材料科学

Chihab, Yassine^1 ; Raefat, Saad^1 ; Garoum, Mohammed^1 ; Laaroussi, Najma^1 ; Bouferra, Rachid^2

Mohammed v University in Rabat, EST de Salé, Materials, Energy and Acoustics TEAM, Morocco^1

Cadi Ayyad University, Marrakech, Morocco^2

关键词: Ecological building materials;    Gaver-Stehfest methods;    Global minimization;    Numerical inversion of Laplace transform;    Sensitivity coefficient;    Simultaneous estimation;    Theoretical modeling;    Unfired clay bricks;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/446/1/012008/pdf
DOI  :  10.1088/1757-899X/446/1/012008

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Clay is an ecological building material used widely in constructions especially in rural areas. In this work an experimental study has been carried out to estimate the apparent thermal diffusivity and adiabatic limit temperature of three types of unfired clay brick using flash method. The three samples were prepared with the same water proportion (picked between the plasticity and the liquidity limits) and exposed to the same drying conditions. The thermal diffusivity and adiabatic limit temperature were estimated using numerical global minimization procedures of the quadratic distance between the theoretical model and the experimental thermogram. The theoretical model is derived from a numerical inversion of Laplace transform using Gaver-Stehfest method. An approach based on the independence between the sensitivity coefficients and the magnitude of these coefficients(Beck criterion)is presented in order to examine the simultaneous estimation of the different parameters related to the theoretical model from the experimental data. For all samples tested, the results show that the estimated parameters give a good agreement between the experimental data and the theoretical model.