Abstract:

   Aiming at the ill-posed of the inverse problem of textile material design(IPTMD), a new approach based on Bayesian Markov Chain Monte Carlo(Bayesian-MCMC) method was proposed for solving the problem of single and multiple parameter determination. Since the heat and moisture transfer model is non-linear and the IPTMD is ill-posed, it proves an effective method to derive posterior distribution for the model parameters such as the heat conductivity, thickness and porosity of the material. This method describes prior information of parameters as prior probability density, constructing numerical algorithms of the IPTMD. The numerical results show that Bayesian inference method which agrees with Markov chain Monte Carlo sampling algorithm can be applied to solve the IPTMD.