Inverse Identification of Temperature-Dependent Thermal Conductivity for Charring Ablators

Abstract

Estimation of thermal conductivity of charring composite is a key issue for both design and optimization of an ablative thermal protection system. This paper presents a method for predicting temperature-dependent thermal conductivity of charring ablator using genetic algorithm and cubic spline interpolation, and a special ablative material composed of phenolic resin, glass fibers and quartz fibers is concerned. In this study, by considering the effects of pyrolysis, carbon–silica reaction, and the convective heat transfer between pyrolysis gas and charred layer, the ablative heat transfer model is developed to simulate the ablation process first. Then based on the measured temperature profiles and built model, the temperature-dependent thermal conductivity without prior information on the functional form is predicted which is parameterized by cubic spline. The predicted thermal conductivity curve is continuous and smooth everywhere, and the changes of the curve can reveal the ablation characteristic of the concerned material precisely. Consequently, the calculated temperature profiles using the predicted results show good agreement with experimental data. Also, the reliability of the prediction is discussed through analyzing the iterative process and the number of interpolation nodes. It is concluded that the improvement is limited through adding nodes when the thermal conductivity is already well defined by existing nodes.