An Inverse Parameter Estimation Methodology for the Analysis of Aeroheating and Thermal Protection System Experimental Data

There are substantial uncertainties in the computational models currently used to predict the heating environment of a spacecraft and the Thermal Protection System (TPS) material response during Mars entry. Flight data will help with a better quantification and possible reduction of such uncertainties as well as with the improvement of the current computational tools. The Mars Science Laboratory (MSL) entry, Descent and Landing Instrumentation (MEDLI) suite will provide a comprehensive set of flight data. The Inverse Parameter Estimation (IPE) methodology presented in this work targets the reconstruction of the boundary conditions experienced by the spacecraft during the entry in the Mars atmosphere, in particular the heating to which the TPS is exposed. To investigate the feasibility of the IPE method, Arc Jet test conditions relevant to MSL entry environments are selected. The Nominal Analysis is performed first to examine the quality of the experimental data and to compare to the nominal model predictions. Next, a Monte Carlo study is performed to provide a hierarchy for the model input parameters based on their overall contribution to the measurement uncertainty. A Sensitivity Analysis is then performed where the correlation between the different input parameters is investigated to determine whether they can be simultaneously estimated. Finally, an IPE code is developed and tested on the ArcJet dataset. This code uses in depth temperature information and recession data to back calculate heating and material properties. Solution uniqueness, existence and stability are discussed in detail and are being identified as the main challenges of the inverse analysis