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Predictive numerical simulations for rebuilding freestream conditions in atmospheric entry flows

Abstract : Accurate prediction of hypersonic high-enthalpy flows is of main relevance for atmospheric entry missions. However, uncertainties are inevitable on freestream conditions and other parameters of the physico-chemical models. For this reason, a rigorous quantification of the effect of uncertainties is mandatory to assess the robustness and predictivity of numerical simulations. Furthermore, a proper reconstruction of uncertain parameters from in-flight measurements can help reducing the level of uncertainties of the output. In this work, we will use a statistical framework for direct propagation of uncertainties and inverse freestream reconstruction applied to atmospheric entry flows. We propose an assessment of the possibility of exploiting forebody heat flux measurements for the reconstruction of freestream variables and uncertain parameters of the model for hypersonic entry flows. This reconstruction is performed in a Bayesian framework, allowing to account for sources of uncertainties and measurement errors. Different techniques are introduced to enhance the capabilities of the statistical framework for quantification of uncertainties. First, an improved surrogate modeling technique is proposed, based on Kriging and Sparse Polynomial Dimensional Decomposition. Then a method is proposed to adaptively add new training points to an existing experimental design to improve the accuracy of the trained surrogate model. A way to exploit active subspaces in Markov Chain Monte Carlo algorithms for Bayesian inverse problems is also proposed.
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Submitted on : Thursday, April 12, 2018 - 2:24:06 PM
Last modification on : Tuesday, October 20, 2020 - 11:33:22 AM


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  • HAL Id : tel-01764898, version 1



Andrea Francesco Cortesi. Predictive numerical simulations for rebuilding freestream conditions in atmospheric entry flows. Numerical Analysis [math.NA]. Université de Bordeaux, 2018. English. ⟨NNT : 2018BORD0021⟩. ⟨tel-01764898⟩



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