Hygric characterization of wood fiber insulation under uncertainty with dynamic measurements and Markov Chain Monte-Carlo algorithm

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• 作者：Simon Rouchier^a ; ^{simon.rouchier@univ-smb.fr} ; ; Thomas Busser^a ; ^b ; Mickaë ; l Pailha^a ; Amandine Piot^b ; Monika Woloszyn^a
• 关键词：HAM ; Characterization ; MCMC ; Identifiability
• 刊名：Building and Environment
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：114
• 期：Complete
• 页码：129-139
• 全文大小：1592 K
• 卷排序：114

文摘

Bayesian inference is applied to the hygric characterization of wood fibre under uncertainty. The use of dynamic measurements allows a fast and joint estimation of moisture permeability and sorption isotherm. The sorption isotherm matches with conventional characterization methods. A simplified identifiability study evaluates the reliability of results. A validation step confirms that results could be extrapolated to different conditions.