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Bayesian Estimation of Temperature-Dependent Thermophysical Properties and Transient Boundary Heat Flux

2009; Taylor & Francis; Volume: 31; Issue: 7 Linguagem: Inglês

10.1080/01457630903425635

1521-0537

Carlos Mota, Helcio R. B. Orlande, Mario Olavo Magno de Carvalho, Ville Kolehmainen, Jari P. Kaipio,

Radiative Heat Transfer Studies

Abstract In this article, we apply a Bayesian approach for the simultaneous identification of volumetric heat capacity, thermal conductivity, and boundary heat flux, in a one-dimensional nonlinear heat conduction problem. The Markov chain Monte Carlo sampling approach, implemented in the form of the Metropolis–Hastings algorithm, was used for the solution of the inverse problem. Simulated temperature measurements were used in the inverse analysis in order to examine the accuracy and stability of the overall approach. Independent measurement data were used to construct the prior model for the coefficients to be estimated. The approach is also applied to experiments involving the heating of a reference material with an oxyacetylene torch. Acknowledgments Useful discussions with Professor Renato M. Cotta (PEM/COPPE/UFRJ), Dr. José Bezerra, and Dr. Luis Loures (Brazilian Space Institute), as well as with Professor Gligor Kanevce and Professor Lubjica Kanevce (St. Kliment University, Macedonia), are greatly appreciated. This work was mainly supported by the Brazilian Space Agency–AEB. Partial support from CNPq and FAPERJ, agencies for the fostering of science from the Brazilian federal government and from the government of the state of Rio de Janeiro, respectively, are sincerely appreciated. The authors are thankful to the Brazilian Space Institute for providing the material for the specimen. The work was also supported by the Academy of Finland (projects 119270 and 213476).