Combining Molecular Beam and Plasmatron Data for Robust Calibration of Nitridation Mechanism

The modeling of gas–surface interaction phenomena is crucial for accurately predicting the heat flux and the mass loss experienced by hypersonic vehicles. Gas–surface interactions refer to the phenomena occurring between the reacting gas and the thermal protection material. An important part of the modeling concerns the description of the surface chemical reactions. In this regard, we propose a novel methodology to infer the parameters underlying such surface chemistry models. It combines uncertainty quantification techniques with state-of-the-art modeling and different types of experiments. The methodology is used to calibrate, in a Bayesian sense, the rates of the elementary reactions between a nitrogen gas and a carbon surface. We rely on both molecular beam and plasma wind tunnel observations. The former provides detailed data on the chemical mechanisms but is characterized by pressures nonrepresentative of atmospheric entries. By contrast, plasma wind tunnel experiments are conducted at representative pressures but contain only macroscopic information. The parameters’ posterior distributions are then propagated through the models representing the two experiments. The calibrated model is able to satisfactorily explain both experiments, highlighting the robustness of the proposed methodology.