Uncertainty Analysis of Radiative Heating Predictions for Titan Entry


The objective of this study was to investigate the uncertainty in shock layer radiative heating predictions on the surface of a hypersonic inflatable aerodynamic decelerator during Titan entry at peak radiative heating conditions. Computational fluid dynamics simulations of planetary entry flows and radiative heating predictions possess a significant amount of uncertainty due to the complexity of the flow physics and the difficulty in obtaining accurate experimental results ofmolecular-level phenomena. Sources ofuncertainty considered include flowfield chemical ratemodels, molecular band emission, and the excitation/deexcitation rates ofmoleculesmodeledwith a non-Boltzmann approach.Because of the computational cost of the numerical models, uncertainty quantification was performed with a surrogate modeling approach based on a sparse approximation of the point-collocation nonintrusive polynomial chaos expansion. Accurate uncertainty results were obtained with only 500 evaluations of the computational model. Results showed that epistemic uncertainty intervals of surface radiative heating predictions were as wide as 150 W/cm2 during Titan entry, indicating the significant effect of uncertainty. A global nonlinear sensitivity analysis showed that the top uncertainty source contributing to the uncertainty in radiative heating was the flowfield chemistry modeling throughout the shock layer.


Mechanical and Aerospace Engineering

Research Center/Lab(s)

Center for High Performance Computing Research

Keywords and Phrases

Chemical Analysis; Computational Fluid Dynamics; Flow Fields; Forecasting; Heat Radiation; Heating; Polynomial Approximation; Radiant Heating; Sensitivity Analysis; Aerodynamic Decelerators; Computational Fluid Dynamics Simulations; Computational Model; Epistemic Uncertainties; Nonlinear Sensitivity Analysis; Polynomial Chaos Expansion; Sparse Approximations; Uncertainty Quantifications; Uncertainty Analysis

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


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© 2015 Thomas K. West IV, Andrew J. Brune, Serhat Hosder, and Christopher O. Johnston, All rights reserved.