The conductive and radiative properties of participating medium can be estimated by solving an inverse problem that combines transient temperature measurements and a forward model to predict the coupled conductive and radiative heat transfer. The procedure, as well as the estimates of parameters, are not only affected by the measurement noise that intrinsically exists in the experiment, but are also influenced by the known model parameters that are used as necessary inputs to solve the forward problem. In the present study, a stochastic Cramér–Rao bound (sCRB)-based error analysis method was employed for estimation of the errors of the retrieved conductive and radiative properties in an inverse identification process. The method took into account both the uncertainties of the experimental noise and the uncertain model parameter errors. Moreover, we applied the method to design the optimal location of the temperature probe, and to predict the relative error contribution of different error sources for combined conductive and radiative inverse problems. The results show that the proposed methodology is able to determine, a priori, the errors of the retrieved parameters, and that the accuracy of the retrieved parameters can be improved by setting the temperature probe at an optimal sensor position.

This paper presents a modified inverse method for retrieving the spectral absorption and transport scattering coefficients of participating medium, the method combines (i) several analytical expressions obtained from the modified two-flux (TF) approximation, (ii) the Monte Carlo (MC) method for predicting normal-hemispherical transmittance Tnh and reflectance Rnh generally obtained from experiments, as well as (iii) an optimization method employing the genetic algorithm (GA). Three types of typical participating medium, the green glass, the low-iron glass, and the silica aerogel with known radiative properties taken form the literatures, were used to illustrate the accuracy and robustness of the modified method by retrieving the input properties from the inverse identification in which the Tnh and Rnh ‘experimental data’ were obtained from the MC predictions. The results show that the modified inverse method was able to retrieve accurately the absorption and transport scattering coefficients of participating medium.