A Bayesian Approach for the Solution of Inverse Problems to Estimate Radiative Properties

Abstract

The main objective of the present work is related to the formulation and solutionof inverse problems in radiative heat transfer phenomena. The analysis consists in estimating parameters and functions of a participanting medium, such as optical thickness, single scattering albedo, diffusive reflectivities and phase function coefficients. It is performed with the numerical application of a Bayesian framework, which includes “Maximum a Posteriori” (MAP) and "Markov Chains Monte Carlo"(MCMC), within the Metropolis-Hastings procedure. These methodologiesproved to be effective for solving such problems.