MCMC Parameters Estimation in the Inverse Problem of Spontaneous Combustion

Article Preview

Abstract:

Spontaneous combustion is a complicated process and its control function is a partial differential equation (PDE) of heat conduction. To solve the problem of spontaneous combustion, we should specify some parameters first, such as the heat source, thermal conductivity, convective heat transfer coefficient, and so on. Some parameters can be got easily and accurately, but some are not. So there could be a great gap between the result of numerical simulation and the result of experiment. For this inverse problem, we can estimate these parameters with the MCMC (Markov Chain Monte Carlo) method. Then, we could get more accuracy and reliable numerical result.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1440-1445

Citation:

Online since:

October 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Larry Wasserman, All of Statistics, Science Press, Beijng , China, 2008. pp.317-331.

Google Scholar

[2] Mark Steyvers, Computational Statistics with Matlab, 2011. pp.15-38.

Google Scholar

[3] CHEN Ping, XU Ruo-xi, Metropolis-hastings adaptive algorithm and its application, Systems Engineering-Theory & Practice, 2008(01). pp.100-108.

Google Scholar

[4] CHEN Hai-yang, TENG Yan-guo et al, Event Source Identification of Water Pollution Based on Bayesian-MCMC, Journal of Hunan University(Natural Sciences), 2012(06). P. 74-78.

Google Scholar

[5] YANG Chen, GAO Siyun, Inverse Analysis to Estimate Thermal Conductivity Components of Orthotropic Medium, Journal of Chemical Industry and Engineering(China), 2007(06). pp.1378-1384.

Google Scholar