THERMAL SCIENCE

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Authors of this Paper

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Jun-Feng Lai

,

Zai-Zai Yan

,

Ji-Huan He

BAYESIAN INFERENCE FOR SOLVING A CLASS OF HEAT CONDUCTION PROBLEMS

ABSTRACT
This paper considers a heat conduction problem of a common continuum-type stochastic mathematical model in an engineering field. The approximate solution is calculated with the Markov chain Monte-Carlo algorithm for the heat conduction problem. Three examples are given to illustrate the solution process of the method.
KEYWORDS
Bayesian inference, heat conduction problem, Markov Chain Monte Carlo
PAPER SUBMITTED: 2019-12-26
PAPER REVISED: 2020-05-10
PAPER ACCEPTED: 2020-05-10
PUBLISHED ONLINE: 2021-03-27
DOI REFERENCE: https://doi.org/10.2298/TSCI191226098L
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Issue 3, PAGES [2135 - 2142]
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Bayesian inference for solving a class of heat conduction problems

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence