In the calculation of transport coefficients from experimental data precise knowledge of the source is usually assumed, while the identification of the coefficients focuses on specific geometries and one spatial variable. This paper presents a method for the simultaneous estimation of both the distributions of transport coefficients as well as the source profile. A convex solution of the inverse problem is retained which makes the calculations highly computational efficient. Moreover, this allows for the estimation of multi-dimensional transport coefficients, source terms, and the analysis of the effect of regularization on experimental data and transport coefficient distributions.
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