Reconstruction of thermal conductivity and heat capacity using a tomographic approach

We consider the estimation of the volumetric heat capacity and the thermal conductivity as distributed parameters. The measurement scheme consists of sequentially heating the boundary of the object in different source locations and measuring the induced temperature evolutions in different measurement locations on the boundary. The estimation of the distributions of volumetric heat capacity and thermal conductivity based on these boundary data is an ill-posed inverse boundary value problem. We propose an approach which is based on transient data on the boundary and the modeling of the unknown coefficients as Markov random fields. The intended applications are non-destructive retrieval of defects as well as the estimation of macroscopic characteristics of novel materials. We evaluate the proposed approach by a numerical simulation.