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Inference methods for gas/surface interaction models: from deterministic approaches to Bayesian techniques

Abstract : In this work we review selected experiments and inference methods for the determination of atmospheric entry gas/surface interaction models for air catalysis and nitrogen ablation. Accurate prediction of the gas/surface interaction during spacecraft reentry remains a challenging problem for thermal protection system design. Attempts to model the surface chemistry of catalytic and ablative materials must account for experimental and model uncertainties. We review two sets of experiments and models adopted in the relevant literature for the rebuilding of catalytic properties and nitridation reaction efficiencies. The review is enriched with new perspectives to these problems by using dedicated Bayesian methods.
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https://hal.inria.fr/hal-03081323
Contributor : Anabel del Val Connect in order to contact the contributor
Submitted on : Friday, December 18, 2020 - 10:11:12 AM
Last modification on : Thursday, January 20, 2022 - 5:30:08 PM
Long-term archiving on: : Friday, March 19, 2021 - 8:15:54 PM

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  • HAL Id : hal-03081323, version 1

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Anabel del Val, Olivier Le Maitre, Olivier Chazot, Pietro Marco Congedo, Thierry E. Magin. Inference methods for gas/surface interaction models: from deterministic approaches to Bayesian techniques. UQOP 2020 - International Conference on Uncertainty Quantification & Optimisation, UTOPIAE, Nov 2020, Brussels, Belgium. ⟨hal-03081323⟩

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