Quantification of uncertainty on the catalytic property of reusable thermal protection materials from high enthalpy experiments
SANSON, Francois
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
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Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
SANSON, Francois
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
CONGEDO, Pietro Marco
Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
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Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts [CARDAMOM]
Langue
en
Article de revue
Ce document a été publié dans
Experimental Thermal and Fluid Science. 2017-01-01, vol. 82, p. 414-423
Elsevier
Résumé en anglais
An accurate determination of the catalytic property of thermal protection materi- als is crucial to design reusable atmospheric entry vehicles. This property is deter- mined by combining experimental measurements and ...Lire la suite >
An accurate determination of the catalytic property of thermal protection materi- als is crucial to design reusable atmospheric entry vehicles. This property is deter- mined by combining experimental measurements and simulations of the reactive boundary layer near the material surface. The inductively-driven Plasmatron fa- cility at the von Karman Institute for Fluid Dynamics provides a test environment to analyze gas-surface interactions under effective hypersonic conditions. In this study, we develop an uncertainty quantification methodology to rebuild values of the gas enthalpy and material catalytic property from Plasmatron experiments. A non-intrusive spectral projection method is coupled with an in-house boundary- layer solver, to propagate uncertainties and provide error bars on the rebuilt gas enthalpy and material catalytic property, as well as to determine which uncer- tainties have the largest contribution to the outputs of the experiments. We show that the uncertainties computed with the methodology developed are significantly reduced compared to those determined using a more conservative engineering ap- proach adopted in the analysis of previous experimental campaigns.< Réduire
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