(Georgia Institute of Technology, 2010-09-27)
Mahzari, Milad
There are substantial uncertainties in the computational models currently used to predict
a spacecraft’s heating environment and the Thermal Protection System (TPS) material
response during Mars entry. Flight data will help reduce these uncertainties and improve
the current computational tools. The Mars Science Laboratory (MSL) Entry, Descent and
Landing Instrumentation (MEDLI) suite will provide more aeroheating data than all the
previous Mars missions combined. Motivated by this future data, a comprehensive inverse
parameter estimation methodology is presented in this paper for the analysis of aeroheating
and TPS experimental data. The proposed methodology is applied to an MSL relevant
Arcjet test dataset to investigate the feasibility of the proposed approach. The first step is the
Nominal Analysis where the quality of the experimental data is examined and a comparison
to the nominal predictions is presented. The second step is the Monte Carlo Analysis where a
Monte Carlo study is performed to identify the model input parameters that contribute the
most to the measurement uncertainty. The third step is the Sensitivity Analysis where the
correlation between the different input parameters is investigated in order to determine
what parameters can be estimated simultaneously. Finally the last step is the Inverse
Analysis where an inverse parameter estimation code is developed to estimate heating and
material parameters from the Arcjet data. Solution existence, uniqueness and stability were
identified as the main challenges faced in the inverse analysis. Some strategies were
suggested in order to deal with these challenges. Finally, in order to show how the different
steps of this methodology come together a test problem was solved.