The aim of this paper is to provide researchers dealing with inverse heat transfer problems a review of the Bayesian approach to inverse problems, the related modeling issues, and the methods that are used to carry out inference. In Bayesian inversion, the aim is not only to obtain a single point estimate for the unknown, but rather to characterize uncertainties in estimates, or predictions. Before any measurements are available, we have some uncertainty in the unknown. After carrying out measurements, the uncertainty has been reduced, and the task is to quantify this uncertainty, and in addition to give plausible suggestions for answers to questions of interest. The focus of this review is on the modeling-related topics in inverse problems in general, and the methods that are used to compute answers to questions. In particular, we build a scene of how to handle and model the unavoidable uncertainties that arise with real physical measurements. In addition to giving a brief review of existing Bayesian tre...

The Bayesian Framework for Inverse Problems in Heat Transfer

Systematic methods for the solution of inverse problems have developed significantly during the past two decades and have become a powerful tool for analysis and design in engineering. Inverse analysis is nowadays a common practice in which teams involved with experiments and numerical simulation synergistically collaborate throughout the research work, in order to obtain the maximum of information regarding the physical problem under study. In this paper, we briefly review various approaches for the solution of inverse problems, including those based on classical regularization techniques and those based on the Bayesian statistics. Applications of inverse problems are then presented for cases of practical interest, such as the characterization of nonhomogeneous materials and the prediction of the temperature field in oil pipelines.

Inverse Problems in Heat Transfer: New Trends on Solution Methodologies and Applications

A comprehensive survey of the literature in the area of numerical heat transfer (NHT) published between 2000 and 2009 has been conducted Due to the immenseness of the literature volume, the survey

Literature Survey of Numerical Heat Transfer (2000–2009): Part II

A Bayesian approach for the simultaneous estimation of surface heat transfer coefficient and thermal conductivity from steady state experiments on fins

https://www.repository.cam.ac.uk/bitstream/1810/271798/2/APEN-D-17-04563R1_2.pdf

Siddharth Parthasarathy

Papers

Estimation of parameters in multi-mode heat transfer problems using Bayesian inference : Effect of noise and a priori