Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry
The objective of this work was to perform sensitivity analysis and uncertainty quantification for afterbody radiative heating predictions of the Stardust capsule during Earth entry at peak afterbody radiation conditions. The radiation environment in the afterbody region poses significant challenges for accurate uncertainty quantification and sensitivity analysis due to the complexity of the flow physics, computational cost, and large number of uncertain variables. In this study, first a sparse collocation nonintrusive polynomial chaos approach along with global nonlinear sensitivity analysis was used to identify the most significant uncertain variables and reduce the dimensions of the stochastic problem. Then, a total-order stochastic expansion was constructed over only the important parameters for an efficient and accurate estimate of the uncertainty in radiation. Based on previous work, 388 uncertain parameters were considered in the radiation model, which came from the thermodynamics, flowfield chemistry, and radiation modeling. The sensitivity analysis showed that only four of these variables contributed significantly to afterbody radiation uncertainty, accounting for almost 95% of the uncertainty. These included the electronic-impact excitation rate for N between level 2 and level 5 and rates of three chemical reactions influencing N, N +, O, and O + number densities in the flowfield.
T. K. West et al., "Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry," Journal of Thermophysics and Heat Transfer, American Institute of Aeronautics and Astronautics (AIAA), Jan 2016.
The definitive version is available at https://doi.org/10.2514/1.T4948
Mechanical and Aerospace Engineering
Center for High Performance Computing Research
International Standard Serial Number (ISSN)
Article - Journal
© 2016 American Institute of Aeronautics and Astronautics (AIAA), All rights reserved.
01 Jan 2016