12 research outputs found

    Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)

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    In this paper, we are interested in the acceleration of numerical simulations. We focus on a hypersonic planetary reentry problem whose simulation involves coupling fluid dynamics and chemical reactions. Simulating chemical reactions takes most of the computational time but, on the other hand, cannot be avoided to obtain accurate predictions. We face a trade-off between cost-efficiency and accuracy: the simulation code has to be sufficiently efficient to be used in an operational context but accurate enough to predict the phenomenon faithfully. To tackle this trade-off, we design a hybrid simulation code coupling a traditional fluid dynamic solver with a neural network approximating the chemical reactions. We rely on their power in terms of accuracy and dimension reduction when applied in a big data context and on their efficiency stemming from their matrix-vector structure to achieve important acceleration factors (Ă—10\times 10 to Ă—18.6\times 18.6). This paper aims to explain how we design such cost-effective hybrid simulation codes in practice. Above all, we describe methodologies to ensure accuracy guarantees, allowing us to go beyond traditional surrogate modeling and to use these codes as references.Comment: Under revie

    Approximation numérique et modélisation de l'ablation liquide

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    During atmospheric re-entry phase, a spacecraft undergoes a sudden increase of the temperature due to the friction of atmospheric gases. This rise drives to a physical-chemical degradation of the thermal protective system of the object made of composite material. A composite is made of several materials with ablates differently. In this thesis, we mainly focus on the melting of an object during its re-entry phase. Therefore there are three phases: solid, liquid and gas phases. In order to simulate this phenomenon, robust numerical methods have been developed to compute a compressible multiphase flow. The coupling strategy between the solid and the fluid have also been studied. Solvers developed in the present work are based on Finite Volume Method. A splitting strategy is used to compute compressible two-phase flows using the five-equation model with viscous and heat conduction effects. The main idea of the splitting is to separate the acoustic and dissipative phenomena from the transport one. An implicit treatment of the acoustic step is performed while the transport step is solved explicitly. The overall scheme resulting from this splitting operator strategy is very robust, conservative, and preserves contact discontinuities. The boundary interface condition between the solid and the multiphase flow is enforced by mass and energy balances at the wall. The melting front is tracked explicitly using an ALE formulation of the equations. The robustness of the approach and the interest of the semi-implicit formulation are demonstrated through numerical simulations in one and two dimensions on moving curvilinear grids.Lors de sa rentrée dans l’atmosphère d’une planète, un engin spatial subit un échauffement important dû aux frottements des gaz atmosphériques sur la paroi. Cette élévation de température conduit à une dégradation physico-chimique du bouclier thermique de l’objet constitué de matériaux composites. Un composite est constitué de divers matériaux qui s’ablatent différemment. Dans cette thèse, nous nous intéressons essentiellement à la fusion d’un matériau durant sa phase de rentrée atmosphérique. Nous sommes donc en présence de trois phases : solide, liquide et gaz. Pour simuler ce phénomène, des méthodes numériques robustes ont été mises au point pour calculer l’écoulement diphasique compressible autour de l’objet. Le couplage entre le solide et l’écoulement fluide a aussi été étudié. Les méthodes numériques développées durant cette thèse sont basées sur une approche volumes finis. Une stratégie de décomposition d’opérateurs est utilisée pour résoudre le modèle diphasique à cinq équations avec les termes de dissipation modélisant l’écoulement fluide. L’idée principale de cette décomposition d’opérateurs est de séparer les phénomènes acoustiques et dissipatifs des phénomènes de transport. Un traitement implicite de l’étape acoustique est réalisé tandis que l’étape de transport est résolue explicitement. Le schéma semi-implicite global est alors très robuste, conservatif et préserve les discontinuités de contact. Les conditions d’interface entre les domaines fluide et solide sont déduites des bilans de masse et d’énergie à la paroi. Le front de fusion est suivi explicitement grâce à une formulation ALE des équations. La robustesse de l’approche et l’apport de la formulation semi-implicite sont finalement démontrés grâce à des expériences numériques mono et bidimensionnelles sur maillages curvilignes mobiles

    Numerical approximation and modelling of liquid ablation

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    Lors de sa rentrée dans l’atmosphère d’une planète, un engin spatial subit un échauffement important dû aux frottements des gaz atmosphériques sur la paroi. Cette élévation de température conduit à une dégradation physico-chimique du bouclier thermique de l’objet constitué de matériaux composites. Un composite est constitué de divers matériaux qui s’ablatent différemment. Dans cette thèse, nous nous intéressons essentiellement à la fusion d’un matériau durant sa phase de rentrée atmosphérique. Nous sommes donc en présence de trois phases : solide, liquide et gaz. Pour simuler ce phénomène, des méthodes numériques robustes ont été mises au point pour calculer l’écoulement diphasique compressible autour de l’objet. Le couplage entre le solide et l’écoulement fluide a aussi été étudié. Les méthodes numériques développées durant cette thèse sont basées sur une approche volumes finis. Une stratégie de décomposition d’opérateurs est utilisée pour résoudre le modèle diphasique à cinq équations avec les termes de dissipation modélisant l’écoulement fluide. L’idée principale de cette décomposition d’opérateurs est de séparer les phénomènes acoustiques et dissipatifs des phénomènes de transport. Un traitement implicite de l’étape acoustique est réalisé tandis que l’étape de transport est résolue explicitement. Le schéma semi-implicite global est alors très robuste, conservatif et préserve les discontinuités de contact. Les conditions d’interface entre les domaines fluide et solide sont déduites des bilans de masse et d’énergie à la paroi. Le front de fusion est suivi explicitement grâce à une formulation ALE des équations. La robustesse de l’approche et l’apport de la formulation semi-implicite sont finalement démontrés grâce à des expériences numériques mono et bidimensionnelles sur maillages curvilignes mobiles.During atmospheric re-entry phase, a spacecraft undergoes a sudden increase of the temperature due to the friction of atmospheric gases. This rise drives to a physical-chemical degradation of the thermal protective system of the object made of composite material. A composite is made of several materials with ablates differently. In this thesis, we mainly focus on the melting of an object during its re-entry phase. Therefore there are three phases: solid, liquid and gas phases. In order to simulate this phenomenon, robust numerical methods have been developed to compute a compressible multiphase flow. The coupling strategy between the solid and the fluid have also been studied. Solvers developed in the present work are based on Finite Volume Method. A splitting strategy is used to compute compressible two-phase flows using the five-equation model with viscous and heat conduction effects. The main idea of the splitting is to separate the acoustic and dissipative phenomena from the transport one. An implicit treatment of the acoustic step is performed while the transport step is solved explicitly. The overall scheme resulting from this splitting operator strategy is very robust, conservative, and preserves contact discontinuities. The boundary interface condition between the solid and the multiphase flow is enforced by mass and energy balances at the wall. The melting front is tracked explicitly using an ALE formulation of the equations. The robustness of the approach and the interest of the semi-implicit formulation are demonstrated through numerical simulations in one and two dimensions on moving curvilinear grids

    A second-order extension of a robust implicit-explicit acoustic-transport splitting scheme for two-phase flows

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    International audienceDiffuse interface methods have proven their ability to simulate complex two-phase flows. A number of robust numerical schemes have been developed to simulate such flows involving large density and pressure ratios. Diffusion induced by these methods, however, makes it difficult to localize the interface between the two fluids. To overcome this issue, while retaining the advantages of diffuse interface methods, a second-order extension using a Monotonic Upstream-centered Scheme for Conservation Laws-type (MUSCL-type) method of the implicit-explicit acoustic-transport splitting scheme introduced in [40] is presented. A specific compressive limiter is used for the volume fraction in order to limit the diffusion of the interface between the two fluids. Numerical simulations are presented to illustrate the capability of the proposed new method to simulate highly complex compressible two-phase flows

    Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)

    No full text
    In this paper, we are interested in the acceleration of numerical simulations. We focus on a hypersonic planetary reentry problem whose simulation involves coupling fluid dynamics and chemical reactions. Simulating chemical reactions takes most of the computational time but, on the other hand, cannot be avoided to obtain accurate predictions. We face a trade-off between cost-efficiency and accuracy: the simulation code has to be sufficiently efficient to be used in an operational context but accurate enough to predict the phenomenon faithfully. To tackle this trade-off, we design a hybrid simulation code coupling a traditional fluid dynamic solver with a neural network approximating the chemical reactions. We rely on their power in terms of accuracy and dimension reduction when applied in a big data context and on their efficiency stemming from their matrixvector structure to achieve important acceleration factors (Ă—10 to Ă—18.6). This paper aims to explain how we design such cost-effective hybrid simulation codes in practice. Above all, we describe methodologies to ensure accuracy guarantees, allowing us to go beyond traditional surrogate modeling and to use these codes as references
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