Séminaire Equations aux dérivées partielles
organisé par l'équipe Modélisation et contrôle
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Romane Helie
Equivalent equation analysis of a kinetic relaxation model
18 janvier 2022 - 14:00Salle de conférences IRMA
Kinetic relaxation schemes are efficient numerical methods to solve an hyperbolic system. The method consists in solving a kinetic model with n_v velocities corresponding to n_v kinetic variables. However, kinetic schemes can be difficult to analyze. To do that, we propose to study the equivalent equation on n_v variables. The study of this equivalent equation allows then to obtain a simple stability analysis. We will also talk about the construction of adapted boundary conditions. -
Pierre Mollo
Modélisation d'écoulements sanguins veineux cérébraux
25 janvier 2022 - 14:00Salle de conférences IRMA
Plusieurs facteurs font que les écoulements sanguins veineux sont beaucoup moins étudiés que leurs équivalents artériels. Par exemple, l'arborescence veineuse présente de grande variation d'un individu à l'autre : prépondérance de certaines structures, asymétrie, absence d'autres structures. Cela rend une étude générique très complexe.
Cependant nous verrons dans cette présentation qu'en nous limitant aux écoulements sanguins cérébraux, nous arrivons à dégager empiriquement des groupes d'individus. De plus la restriction au compartiment intra-crânien nous permet d'utiliser l'hypothèse d'incompressibilité des vaisseaux sanguins veineux.
Ainsi nous verrons et comparerons plusieurs modèles pour ces écoulements mais aussi leurs possibles extensions. Nous aborderons finalement la possibilité d'utiliser des modèles réduits et les applications qui y sont associées. -
Raphaël Loubère
A 3D cell-centered ADER MOOD Finite Volume method for solving updated Lagrangian hyperelasticity on unstructured grids
1 février 2022 - 14:00Salle de conférences IRMA
In this communication, we present a conservative cell-centered Lagrangian finite volume scheme for the solution of the hyper-elasticity model equations on unstructured multidimensional grids. The method is derived from the Eucclhyd scheme discussed in [3,1,2], and is second-order accurate in space and is combined with the a posteriori Multidimensional Optimal Order Detection (MOOD) limiting strategy to ensure robustness and stability at shock waves. Second-order of accuracy in time is achieved via the ADER (Arbitrary high order schemes using DERivatives) approach. This method has been tested in an hydrodynamics context in [4] and the present work aims at extending it to the case of hyper-elasticity models. Such models are derived in a first part in a Lagrangian framework. The dedicated Lagrangian numerical scheme is derived in terms of nodal solver, GCL compliance, subcell forces and compatible discretization. The Lagrangian numerical method has been implemented in 3D under MPI parallelisation framework allowing to handle genuinely large meshes. A relative large set of numerical test cases is presented to assess the ability of the method to achieve effective second order of accuracy on smooth flows, maintaining an essentially non-oscillatory behavior, general robustness ensuring at least physical admissibility where appropriate. Pure elastic neo-Hookean and non-linear materials are considered for our benchmark test problems in 2D and 3D. These test cases feature material bending, impact, compression, non-linear deformation and further bouncing/detaching motions. This is joint work with Walter Boscheri and Pierre-Henri Maire. [1] P.-H. Maire. A unified sub-cell force-based discretization for cell-centered Lagrangian hydrodynamics on polygonal grids. International Journal for Numerical Methods in Fluids, 65:1281–1294, 2011. [2] P.-H. Maire. A high-order one-step sub-cell force-based discretization for cell-centered lagrangian hydrodynamics on polygonal grids. Computers and Fluids, 46(1):341–347, 2011. [3] P.-H. Maire, R. Abgrall, J. Breil, and J. Ovadia. A cell-centered Lagrangian scheme for two- dimensional compressible flow problems. SIAM Journal on Scientific Computing, 29:1781–1824, 2007. [4] R. Loubère W. Boscheri, M. Dumbser and P.-H. Maire. A second-order cell-centered lagrangian ADER-MOOD finite volume scheme on multidimensional unstructured meshes for hydrodynamics. Journal of Computational Physics, 358:103 – 129, 2018. -
Stéphane Clain
Séminaire exceptionnel - The structural method
2 février 2022 - 11:00Salle de conférences IRMA
We present a general new compact scheme method to achieve very high-order approximation named structural method. The main idea is to definitively separated the physics (the physical equations, including the boundary conditions) to the discretization (the structural equations). The first part is dedicated to the design of such schemes, where we show that the discretization equations are obtained from the kernel of a matrix. The second part is dedicated to one-dimensional problems in space such as convection diffusion, Burger, Euler system and the construction of fourth- or sixth-order schemes in space. The last part concerns a new class of very high order scheme in time (4th,6th), unconditionally stable and demonstrate the high efficiency and nice spectral properties of our schemes. Simulations of non-stationary problems: heat equation, wave equation, burger, Euler and Schrödinger equation, highlight the advantages of structural time-scheme regarded to traditional 4th or 6th order RK method. -
Je présenterai et analyserai dans cet exposé un modèle mathématique pour les écoulements compressibles sous une contrainte de densité maximale. Il s’agit de modéliser pour des mélanges biphasiques des phénomènes de saturation (congestion) correspondant à la disparition d’une des deux phases du mélange. Étant donnée une contrainte de densité maximale fixée, les solutions couplent une dynamique compressible dans les zones où la densité est inférieure à cette densité maximale, avec une dynamique incompressible dans les zones où la valeur critique est atteinte, i.e. dans les zones saturées. L'exposé portera plus particulièrement sur la discrétisation et la simulation numérique de ces équations au moyen de schémas mixtes volumes finis / éléments finis.
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Andrea Natale
Lagrangian discretizations of compressible fluids and porous media flow with semi-discrete optimal transport
1 mars 2022 - 14:00Salle de conférences IRMA
The equations of motion for compressible (barotropic) fluids have the structure of a simple conservative dynamical system when expressed in Lagrangian variables. This can be exposed interpreting the Lagrangian flow as a curve of vector-valued L2 functions, and the internal energy of the fluid as a functional on the same space. Particle methods are a natural discretization strategy in this setting, since in this case the flow is discretized using piecewise constant functions on a given partition of the domain, but they require some form of regularization to define the internal energy of the fluid. In this talk I will describe a particle method in which the internal energy is replaced by its Moreau-Yosida regularization in the L2 space, which can be efficiently computed as a semi-discrete optimal transport problem. I will also show how the convexity of the energy in the Eulerian variables can be exploited in the non-convex Lagrangian setting to prove quantitative convergence estimates towards smooth solution of this problem, and how this result generalizes to dissipative porous media flow. -
Florian Blachère
Schémas numériques d'ordre élevé et préservant l'asymptotique
8 mars 2022 - 14:00Salle de conférences IRMA
Dans cet exposé, on présente le développement de deux schémas volumes finis explicites d'ordre élevé pour des systèmes de lois de conservation avec terme source qui peuvent dégénérer vers des équations de diffusion. La construction se fait un choisissant le schéma limite ou en limitant la diffusion numérique. L'extension à l'ordre élevé s'effectue avec des reconstructions polynomiales et la méthode MOOD comme principe de limitation. On présente différents résultats sur maillage 2D non structuré. Ceci un travail en collaboration avec Christophe Chalons et Rodolphe Turpault. -
Agnès Chan
Entropy stable and positivity preserving Godunov-type schemes for multidimensional hyperbolic systems on unstructured grid
15 mars 2022 - 14:00Salle de conférences IRMA
A class of cell centered Finite Volume schemes has been introduced to discretize the equations of Lagrangian hydrodynamics on moving grid [Loubère, Maire, Rebourcet, 2016]. In this framework, the numerical fluxes are evaluated by means of an approximate Riemann solver located at the grid nodes, which provides the nodal velocity required to move the grid in a compatible manner. In this presentation, we describe the generalization of this type of discretization to hyperbolic systems of conservation laws written in Eulerian representation. The evaluation of the numerical fluxes relies on a nodal solver resulting from a node-based conservation condition. The construction of this nodal solver utilizes the Lagrange-to-Euler transformation introduced by Gallice [Gallice, 2003] and revisited in [Chan, Gallice, Loubère, Maire, 2021] to build positive and entropic Eulerian Riemann solvers from their Lagrangian counterparts. The application of this formalism to the case of gas dynamics provides a multidimensional Finite Volume scheme which is positive and entropic under an explicit condition on the time step. Moreover, this study allows us to rigorously recover the original scheme described in [Shen, Yan, Yuan, 2014] for the Euler equations while correcting its defects. An associated Finite Volume simulation code has been built in multi-dimensions for unstructured meshes. Parallelization has been accomplished using the MPI library embedded in PETSc. A large set of 2D/3D numerical experiments show that the proposed solver is less sensitive to spurious instabilities such as the infamous carbuncle, compared to the classical one. To further improve accuracy, the current scheme has been extended to second-order in time and space. The numerical assessment of this new method by means of representative test cases is very promising in terms of robustness. -
Quentin Denoyelle
Résolution de problèmes inverses linéaires parcimonieux par approches variationnelles basées sur la norme de la variation totale
22 mars 2022 - 14:00Salle de conférences IRMA
De nombreux problèmes pratiques en traitement du signal et d’images, comme les problèmes de déconvolution, consistent à essayer de reconstruire à partir d’observations altérées, bruitées et dépendant linéairement d'un signal source, ce même signal. Cette tâche étant mal posée, une famille de techniques consiste à reformuler la reconstruction à travers la résolution d’un problème d’optimisation. On cherche alors en général à reconstruire un signal dont les observations ne s’éloignent pas trop des données. Parfois, il apparaît également que le signal d'intérêt est parcimonieux dans un certain sens : par exemple s’il est composé de sources ponctuelles. Il est alors possible d’incorporer cet a priori dans le problème d’optimisation grâce à une régularisation favorisant ce genre de solutions. Dans cet exposé, nous verrons quelques garanties théoriques de reconstruction dans l’étude de tels problèmes faisant intervenir la norme de la variation totale définie sur l’espace des mesures de Radon. Nous verrons que cette régularisation favorise l’émergence de solutions parcimonieuses composées de sommes de masses de Dirac. Une originalité de cette approche réside dans son absence de discrétisation du domaine sur lequel sont définis les signaux considérés. Ceci permet notamment d’améliorer la simplicité des solutions en évitant les soucis liés aux grilles mal adaptées. Même si l’espace de recherche est de dimension infinie, nous verrons qu’il est possible de construire des méthodes de résolution, avec des garanties de convergence, basées sur l’algorithme de Frank-Wolfe. Enfin ces outils seront illustrés sur un problème de localisation de protéines sur des structures filamentaires en microscopie par fluorescence. -
Paul Novello
Combining supervised deep learning and scientific computing: some contributions and application to computational fluid dynamics
29 mars 2022 - 14:00Salle de conférences IRMA
This work settles in the high-stakes emerging field of Scientific Machine Learning which studies the application of machine learning to scientific computing. More specifically, we consider the use of deep learning to accelerate numerical simulations. We focus on approximating some components of Partial Differential Equation (PDE) based simulation software by a neural network. This idea boils down to constructing a data set, selecting and training a neural network, and embedding it into the original code, resulting in a hybrid numerical simulation. Although this approach may seem trivial at first glance, the context of numerical simulations comes with several challenges stemming from an accuracy-performances trade-off. To tackle these challenges, we thoroughly study each step of the deep learning methodology while considering the aforementioned constraints. By doing so, we emphasize interplays between numerical simulations and machine learning that can benefit each of these fields. We identify the main steps of the deep learning methodology as the construction of the training data set, the choice of the hyperparameters of the neural network, its training, and the implementation of the neural network for the final use case (here, numerical simulations). In this talk, we will go through the contributions related to the third step (training) and the last step (design of a hybrid simulation code). For the third step, we formally define an analogy between stochastic resolution of PDEs and the optimization process at play when training a neural network. This analogy leads to a PDE-based framework for training neural networks that opens up possibilities for improving existing optimization algorithms. Finally, we apply these contributions to a computational fluid dynamics simulation coupled with a multi-species chemical equilibrium library. The obtained deep-learning-based hybrid code achieves an acceleration factor of 18.7 with controlled to no degradation from the prediction of the original simulation code. -
Erwan Deriaz
Poisson Solvers, State of the Art
5 avril 2022 - 14:00Salle de conférences IRMA
Solving Poisson equation is ubiquitous in Physics simulation. All numerical methods (Spectral, Finite Differences, Finite Elements, Discontinuous Galerkin) complement themselves with an ad hoc Poisson solver.
In uniform Cartesian grids with periodic boundary conditions the Fast Fourier Transform (FFT) with its complexity in O(N log(N)) –N denotes the number of points– and its spectral accuracy beats all concurrent numerical methods. In the 80’s, the multigrid methods [HACKBUSCH 85] with their complexity in O(N log(N)) (the log(N) factor stands for the number of iterations necessary to reach the accuracy corresponding to the increase of the number of points N) opened the door to efficient numerical methods suited to non periodic boundaries and immersed boundaries.
Their principle (to separate scales to apply Gauss Seidel iterations) inspired the preconditioning of powerful Linear Solvers (e.g. preconditioning of GMRES) establishing the algebraic multigrid methods. These are blind to the underlying grid structure and can be used in any contexts such as the adaptive grids for instance.
In the 90’s, the Fast Multipole Method [GREENGARD 1987] based on the integral solution of the Poisson Equation and on the properties of its Green kernel, appeared as a concurrent method efficiently addressing the adaptive context and the presence of boundaries. -
Arnaud Münch
Constructive exact controls for semilinear PDEs
26 avril 2022 - 14:00Salle de conférences IRMA
It has been proved by Zuazua in 1993 that the internally controlled semilinear 1D wave equation $\partial_{tt}y-\partial_{xx}y + f(y)=v 1_{\omega}$, with Dirichlet boundary conditions, is exactly controllable in $H^1_0(0,1)\cap L^2(0,1)$ with controls $f\in L^2((0,1)\times(0,T))$, for any $T>0$ and any nonempty open subset $\omega$ of $(0,1)$, assuming that $f\in \mathcal{C}^1(\R)$ does not grow faster than $\beta\vert r\vert \ln^{2}\vert r\vert$ at infinity for some $\beta>0$ small enough. The clever proof, based on the Leray-Schauder fixed point theorem, is not constructive.
In this talk,
- we present a constructive proof and algorithm for the exact controllability of semilinear 1D wave equations.
Assuming that $f^\prime$ does not grow faster than $\beta \ln^{2}\vert r\vert$ at infinity for some $\beta>0$ small enough and that $f^\prime$ is uniformly H\"older continuous on $\R$ for some exponent $p\in[0,1]$, we design a least-squares algorithm yielding an explicit sequence converging to a controlled solution for the semilinear equation, at least with order $1+p$ after a finite number of iterations.
- We extend the proof to the multidimensional case assuming that $f^\prime$ does not grow faster than $\beta \ln^{1/2}\vert r\vert$ at infinity, by using a result of Fu, Yong and Zhang in 2007.
- We show that the method also applies for the (much more intricate situation of) heat equation by considering appropriate cost functional for the controlled pair of the corresponding linearized equation, depending on parametrized Carleman weights. Large enough parameters ensure the convergence of the algorithm. We end the talk by remarking that a zero order fixed point operator derived from a zero order linearization is indeed contracting for any large enough Carleman parameter. This allows notably to greatly simplified the seminal proof of controllability due to Fernandez-Zuazua in 2000.
This talk is based on a series of recent works with Kuntal Bhandari (Clermont-Ferrand), Arthur Bottois (Clermont-Ferrand), Sylvain Ervedoza (Bordeaux), Jérome Lemoine (Clermont-Ferrand), Irène Gayte (Sevilla) and Emmanuel Trélat (Sorbonne Paris). -
Benjamin Boutin
Différences finies avec bord et couches limites discrètes
3 mai 2022 - 14:00Salle de conférences IRMA
La résolution approchée de problèmes d’évolution par des schémas de différences finies nécessite un traitement spécifique des bords, ceci de façon à tronquer artificiellement le domaine de calcul et/ou à incorporer de façon satisfaisante les conditions de bords réalistes. Ce traitement du bord affecte les propriétés de consistance et de stabilité du schéma global et est susceptible, à ce titre, de nuire de façon parfois rédhibitoire à la qualité de l’approximation. La cause typique est l’apparition de modes discrets parasites au voisinage du bord. Je présenterai comment un développement à plusieurs échelles de la solution numérique permet d’analyser ce phénomène, en concentrant la discussion sur quelques exemples simples pour le transport linéaire avec Dirichlet ou Neumann en sortie. -
Nina Aguillon
Quantification a posteriori de la diffusion numérique
12 mai 2022 - 11:00Salle de conférences IRMA
Les solutions des systèmes hyperboliques contiennent des discontinuités. Ces solutions faibles vérifient non seulement les EDP de départ, mais aussi une inégalité d'entropie qui agit comme un critère de sélection déterminant si une discontinuité est physique ou non. Il est très important d'obtenir une version discrète de ces inégalités d'entropie lorsqu'on approxime numériquement les solutions, sans quoi le schéma est susceptible de converger vers des solutions non physiques ou pire d'être instable. Obtenir une inégalité d'entropie discrète est en général un travail difficile, souvent inatteignable pour des schémas d'ordre élevé. Dans cet exposé, je présenterai une approche où ces inégalités sont obtenues a posteriori en minimisant une fonctionnelle bien choisie. La difficulté principale est de prendre en compte la notion de consistance. Cette méthode permet d'obtenir des "cartes de diffusion numérique" pour des schémas d'ordre quelconque. Elle permet aussi de trouver, par une autre procédure d'optimisation, la pire donnée initiale vis à vis de l'entropie. C'est un travail en collaboration avec Emmanuel Audusse, Vivien Desveaux et Julien Salomon. -
Gabriel Peyré
Le transport optimal pour l'apprentissage machine
17 mai 2022 - 14:00Salle de conférences IRMA
Le transport optimal est un outil naturel pour comparer de manière géométrique des distributions de probabilité. Il trouve des applications à la fois pour l'apprentissage supervisé (pour la classification) et pour l'apprentissage non supervisé (pour entrainer des réseaux de neurones génératifs). Le transport optimal souffre cependant de la "malédiction de la dimension", le nombre d'échantillons nécessaires pouvant croitre exponentiellement vite avec la dimension. Dans cet exposé, j'expliquerai comment tirer parti de techniques de régularisation entropique afin d'approcher de façon rapide le transport optimal et de réduire l'impact de la dimension sur le nombre d'échantillons nécessaires. Plus d'informations et de références peuvent être trouvées sur le site de notre livre "Computational Optimal Transport" https://optimaltransport.github.io/ -
Gwenaël Peltier
Biological invasions: the role of adapation to environmental conditions
24 mai 2022 - 14:00Salle de conférences IRMA
In this presentation, we consider a population (typically bacteria) structured by both a spatial variable and a phenotypical trait. Our model takes into account the effects of migrations, mutations, growth and competition. When the environment is assumed homogeneous, if the population survives, it spreads to the whole space, and we have a complete picture of the large-time propagation: the solution converges towards a front, which connects a positive steady state to zero, and spreads at a determined speed.
When the environment is heterogeneous, the situation is much more complex. Depending on the profile of heterogeneities, the invasion may be either slowed or completely blocked. In some cases, the population adaption to the local environment is crucial for invasion to occur. We first consider a linear profile of heterogeneities, and then investigate the fully nonlinear case numerically as well as analytically (in a perturbative framework for the latter). -
Louis Reboul
Asymptotic-preserving ImEx schemes for hyperbolic balance laws with stiff relaxation and plasma discharge applications
6 septembre 2022 - 14:00Salle de conférences IRMA
Some fluid and kinetic systems of equations in the presence of (potentially multiple) small parameters admit so-called asymptotic regimes, where they reduce to a smaller set of equations, potentially with a different mathematical structure. However, classic numerical approaches, such as finite volume methods, do not naturally degenerate in these asymptotic regimes to consistent discretizations of the limit equations. Furthermore, even though stability conditions usually become more and more restrictive when we approach these asymptotic regimes, meaning smaller and smaller time steps, accuracy can be dramatically reduced and the results frequently unexploitable. Asymptotic preserving schemes are designed to both lift the restrictive stability conditions and remain accurate in the asymptotic regime. We introduce a new class of second-order in time and space numerical schemes, which are uniformly asymptotic preserving schemes. The proposed Implicit-Explicit (ImEx) approach, does not follow the usual path relying on the method of lines, either with multi-step methods or Runge-Kutta methods, or semi-discretized in time equations, but is inspired from the Lax-Wendroff approach with the proper level of implicit treatment of the source term. We are able to rigorously show that both the second-order accuracy and the stability conditions are independent of the fast scales in every asymptotic regime, including the study of boundary conditions. The method is also able to yield very accurate steady solutions in the nonlinear case when the source term depends on space. A thorough numerical assessment of the proposed strategy is provided by investigating smooth solutions, solutions with shocks and solutions leading to a steady state with variable source term in space. Our aim also includes plasma discharges with sheaths, where we have two small parameters related to Debye length and mass ratio, and we present some numerical simulations that assess and illustrate the potential of a method similar to the one we have introduced but applied to the isothermal Euler-Poisson equations. -
Bertrand Maury
Modèles sur graphe pour la propagation d’une épidémie en milieu professionnel
13 septembre 2022 - 14:00Salle de conférences IRMA
Nous proposons de décrire les principaux aspects d’un projet de développement d’un outil de simulation de la propagation du Covid 19 dans différents contextes : établissements scolaires (écoles, collèges ou lycées), universités, et entreprises. L’approche proposée est basée sur une équation déterministe d’évolution sur un graphe dynamique dont les sommets sont des personnes ou des groupes de personnes, et dont les arêtes suivent la matrice des contacts évoluant au fil du temps. Nous décrirons certaines propriétés théoriques de versions simplifiées de ce modèle, et préciserons la manière dont il peut être interprété comme une équation de chimiotaxie discrète. Dans un second temps, nous évoquerons des applications effectives de cette approche, en particulier une étude récente effectuée au sein du CHU du Kremlin-Bicêtre impliquant 210 étudiants en médecine, dont les contacts ont été tracés pendant plusieurs mois à l’aide de petits badges portés en permanence par les volontaires. Ces travaux résultent d’une collaboration avec S. Faure (Orsay) et F. Bourdin (ENS-PSL), ainsi qu’avec l’entreprise Kerlink (pour le contact tracing). -
Ludovic Godard-Cadillac
A bi-species kinetic model for cylindrical Langmuir probe : existence result and numerical analysis
20 septembre 2022 - 14:00Salle de conférences IRMA
We study a collisionless kinetic model for plasmas in the neighborhood of a cylindrical metallic Langmuir probe. This model consists in a bi-species Vlasov-Poisson equation in a domain contained between two cylinders with prescribed boundary conditions. The interior cylinder models the probe while the exterior cylinder models the interaction with the plasma core. We prove the existence of a weak-strong solution for this model in the sense that we get a weak solution for the 2 Vlasov equations and a strong solution for the Poisson equation. The first parts of this work are devoted to explain the model and proceed to a detailed study of the Vlasov equations. This study then leads to a reformulation of the Poisson equation as a 1D non-linear and non-local equation and we prove it admits a strong solution using an iterative fixed-point procedure. Eventually we proceed to a qualitative description of the solution under the so-called "generalized Bohm condition" on the incomming fluxes and a numerical investigation of the obtained equation. Due to technical obstacles, we mainly focussed on the "quasi-radial" fluxes for the numerical analysis, which turns out to be enough to validate the model. Curves of the obtained trajectories of particles and curves of the collected current versus the applied voltage are presented. -
Mirco Ciallella
Arbitrary High Order WENO Finite Volume Scheme with Flux Globalization for Moving Equilibria Preservation
27 septembre 2022 - 14:00Salle de conférences IRMA
In the context of preserving stationary states, e.g. lake at rest and moving equilibria, a new formulation of the shallow water system, called Flux Globalization has been introduced by Cheng et al. (2019). This approach consists in including the integral of the source term in the global flux and reconstructing the new global flux rather than the conservative variables. The resulting scheme is able to preserve a large family of smooth and discontinuous steady-state moving equilibria. In this work, we focus on an arbitrary high order WENO Finite Volume (FV) generalization of the global flux approach. The most delicate aspect of the algorithm is the appropriate definition of the source flux (integral of the source term) and the quadrature strategy used to match it with the WENO reconstruction of the hyperbolic flux. When this construction is correctly done, one can show that the resulting WENO FV scheme admits exact discrete steady states characterized by constant global fluxes. We also show that, by an appropriate quadrature strategy for the source, we can embed exactly some particular steady states, e.g. the lake at rest for the shallow water equations. It can be shown that an exact approximation of global fluxes leads to a scheme with better convergence properties and improved solutions. The novel method has been tested and validated on classical cases and their perturbation: subcritical, supercritical and transcritical flows. -
Youssouf Nasseri
An overview on the time discretization of MAC schemes for the shallow water equations
4 octobre 2022 - 14:00Salle de conférences IRMA
In this talk, i will present some results for the time discretization MAC schemes for the shallow water equations (SWE). The space discretization is staggered where the height is stored on the cell-center and the velocity on the cell-edges. Several time integration techniques are discussed like explicit, decoupled, pressure correction and second order Heun method. Numerical simulations will be investigated to assess the strong stability, well-balanced and accuracy first for the SWE and then for the SWE with Coriolis source term. -
Thomas Bellotti
Finite Difference formulation of any lattice Boltzmann scheme: consistency and stability
11 octobre 2022 - 14:00Salle de conférences IRMA
Lattice Boltzmann schemes rely on the enlargement of the size of the target problem in order to solve PDEs in a highly parallelizable and efficient kinetic-like fashion, split into a collision and a stream phase. This structure, despite the well-known advantages from a computational standpoint, is not suitable to construct a rigorous notion of consistency with respect to the target equations and to provide a precise notion of stability. In order to alleviate these shortages and introduce a rigorous framework, we demonstrate that any lattice Boltzmann scheme can be rewritten as a corresponding multi-step Finite Difference scheme on the conserved variables. This is achieved by devising a suitable formalism based on operators, commutative algebra and polynomials. Therefore, the notion of consistency of the corresponding Finite Difference scheme allows to invoke the Lax-Richtmyer theorem in the case of linear lattice Boltzmann schemes. Moreover, we show that the frequently-used von Neumann-like stability analysis for lattice Boltzmann schemes entirely corresponds to the von Neumann stability analysis of their Finite Difference counterpart. More generally, the usual tools for the analysis of Finite Difference schemes are now readily available to study lattice Boltzmann schemes. Their relevance is verified by means of numerical illustrations. -
Léopold Trémant
Autonomous geometric averaging and numerics
18 octobre 2022 - 14:00Salle de conférences IRMA
Highly-oscillatory phenomena present well-known numerical challenges, such as order reduction and energy preservation. The method of high-order averaging allows to separate the "drift" dynamics from the oscillations using formal calculations. This method is used to generates new, modified problems, namely a micro-macro problem or a pulled-back problem, which can be solved with better numerical accuracy. In this talk, I will introduce high-order averaging using a (somewhat recent) closed form approach, based on an ansatz, which facilitates the discussion around such methods. The focus will mostly be on the geometric properties of the method, notably the preservation of a Hamiltonian structure. Perhaps unsurprisingly, the averaging procedure is close to that of normal forms. Therefore if time allows, I will briefly present in which context these methods are equivalent. Of course, discussions around numerical accuracy will permeate the entire talk. -
Wasilij Barsukow
Preserving discrete involutions on Cartesian grids
15 novembre 2022 - 14:00Salle de conférences IRMA
Exact solutions to systems of conservation laws in multiple spatial dimensions often possess interesting additional properties which are a consequence of the equations and which can be formulated as PDEs. Examples are the evolution equations of vorticity or angular momentum, involutional constraints, stationary states or singular limits. Usually, the same numerical diffusion which stabilizes a Finite Volume method, prevents it from preserving any of those additional properties. I will show strategies how to analyse linear numerical methods on Cartesian grids, and how to modify the numerical diffusion in a truly multi-dimensional fashion in order to obtain vorticity preserving and low Mach number compliant methods. This enables the numerical methods to capture essential properties of the equations without excessive grid refinement. -
Virginie Ehrlacher
Boundary stabilization of cross-diffusion systems in moving domains
22 novembre 2022 - 14:00Salle de conférences IRMA
This work is motivated by a collaboration with the French Photovoltaic Institute. The aim of the project is to propose a model in order to simulate and optimally control the fabrication process of thin film solar cells. The production of the thin film inside of which occur the photovoltaic phenomena accounting for the efficiency of the whole solar cell is done via a Physical Vapor Deposition (PVD) process. More precisely, a substrate wafer is introduced in a hot chamber where the different chemical species composing the film are injected under a gaseous form. Molecules deposit on the substrate surface, so that a thin film layer grows by epitaxy. In addition, the different components diffuse inside the bulk of the film, so that the local volumic fractions of each chemical species evolve through time. The efficiency of the final solar cell crucially depends on the final chemical composition of the film, which is freezed once the wafer is taken out of the chamber. A major challenge consists in optimizing the fluxes of the different atoms injected inside the chamber during the process for the final local volumic fractions in the layer to be as close as possible to target profiles. Two different phenomena have to be taken into account in order to correctly model the evolution of the composition of the thin film: 1) the cross-diffusion phenomena between the various components occuring inside the bulk; 2) the evolution of the surface. As a consequence, the underlying model reads as a cross-diffusion system defined on a moving boundary domain. The complete optimal control problem of the fluxes injected in the hot chamber is currently out-of-reach in terms of mathematical analysis. The aim of this talk is to theoretically investigate a simpler problem, which is the boundary stabilization of the model used to simulate the PVD process. We show first exponential stabilization and then finite-time stabilization in arbitrary small time of the linearized system around uniform equilibria, provided the underlying cross-diffusion system has an entropic structure with a symmetric mobility matrix. This stabilization is achieved with respect to both the volumic fractions of the different chemical species composing the thin film and the thickness of the latter. The feedback control is derived using the backstepping technique, adapted to the context of a time-dependent domain. In particular, the norm of the backward backstepping transform is carefully estimated with respect to time. Joint work with Jean Cauvin-Vila and Amaury Hayat. -
Borjan Geshkovski
On the intersection of control theory and machine learning
29 novembre 2022 - 14:00Salle de conférences IRMA
In this talk I will survey some recent results on the neural ODE perspective of machine learning, popularised by Weinan E (2017). This point of view is particularly compelling since many central tasks in machine learning find a natural counterpart in control theory. For instance, supervised learning can be seen as a simultaneous control(lability) problem for a nonlinear ODE, in which one seeks to steer a large amount of initial data to equally as many targets by using a single control. Herein, one can quickly see the necessity of using dynamics which are nonlinear — in fact, many of the commonly used dynamics in machine learning practice are “unusual” compared to more classical control settings, and require new analysis. I will focus mainly (but not exclusively) on the optimal control perspective of supervised learning, and present convergence results for the error, and optimal controls, when the final time horizon is large. Implications to the possible generalization beyond data used for constructing the control, the required depth for the corresponding residual neural network (ResNet), and the turnpike property, will be discussed. The talk will be based on works done in collaboration with Carlos Esteve-Yague, Dario Pighin, and Enrique Zuazua. -
Maria Han Veiga
High fidelity numerical codes: structure-preserving schemes with data-driven models
6 décembre 2022 - 14:00Salle de conférences IRMA
Many engineering and scientific problems can be described by equations of fluid dynamics, namely, systems of time dependent nonlinear hyperbolic PDEs. The mathematical description of these processes as well as the numerical discretisation of the resulting PDEs will depend on the level of detail required to study them. In this talk I will focus on two directions towards higher fidelity numerical simulations: first, I present a novel structure-preserving arbitrarily high-order method that solves the nonlinear ideal magneto-hydrodynamics equations. Secondly, I will focus on our work using Machine Learning (ML) methods with the aim to improve or speed up numerical simulations, through the development of parameter-free routines as part of a numerical solver or surrogate models, with the goal of creating hybrid simulation pipelines that can improve over time.