A Posteriori Error Estimates for Nonconforming Approximations of Evolutionary Convection-Diffusion Problems

We derive computable upper bounds for the difference between an exact solution of the evolutionary convection-diffusion problem and an approximation of this solution. The estimates are obtained by certain transformations of the integral identity that defines the generalized solution. These estimates depend on neither special properties of the exact solution nor its approximation, and involve only global constants coming from embedding inequalities. The estimates are first derived for functions in the corresponding energy space, and then possible extensions to classes of piecewise continuous approximations are discussed.Comment: 10 page

Guaranteed upper bounds for the velocity error of pressure-robust Stokes discretisations

This paper improves guaranteed error control for the Stokes problem with a focus on pressure-robustness, i.e. for discretisations that compute a discrete velocity that is independent of the exact pressure. A Prager-Synge type result relates the errors of divergence-free primal and H(div)-conforming dual mixed methods (for the velocity gradient) with an equilibration constraint that needs special care when discretised. To relax the constraints on the primal and dual method, a more general result is derived that enables the use of a recently developed mass conserving mixed stress discretisation to design equilibrated fluxes that yield pressure-independent guaranteed upper bounds for any pressure-robust (but not necessarily divergence-free) primal discretisation. Moreover, a provably efficient local design of the equilibrated fluxes is presented that reduces the numerical costs of the error estimator. All theoretical findings are verified by numerical examples which also show that the efficiency indices of our novel guaranteed upper bounds for the velocity error are close to 1

Guaranteed upper bounds for the velocity error of pressure-robust Stokes discretisations

This paper improves guaranteed error control for the Stokes problem with a focus on pressure-robustness, i.e. for discretisations that compute a discrete velocity that is independent of the exact pressure. A Prager-Synge type result relates the errors of divergence-free primal and H(div)-conforming dual mixed methods (for the velocity gradient) with an equilibration constraint that needs special care when discretised. To relax the constraints on the primal and dual method, a more general result is derived that enables the use of a recently developed mass conserving mixed stress discretisation to design equilibrated fluxes that yield pressure-independent guaranteed upper bounds for any pressure-robust (but not necessarily divergence-free) primal discretisation. Moreover, a provably efficient local design of the equilibrated fluxes is presented that reduces the numerical costs of the error estimator. All theoretical findings are verified by numerical examples which also show that the efficiency indices of our novel guaranteed upper bounds for the velocity error are close to 1

Numerical Methods for Algorithmic Systems and Neural Networks

These lecture notes are devoted to numerical concepts and solution of algorithmic systems and neural networks. The course is divided into four parts: traditional AI (artificial intelligence), deep learning in neural networks, applications to (and with) differential equations, and project work. Throughout this course an emphasis is on mathematical ingredients from which several are rigorously proven. In the project work, the participants usually form groups and work together on a given problem to train themselves on mathematical modeling, design of algorithms, implementation, and analysis and intepretation of the simulation results

développement d'outils d'optimisation pour freefem++

Cette thèse est consacrée au développement d'outils pour FreeFem++ destinés à faciliter la résolution des problèmes d'optimisation. Ce travail se compose de deux parties principales. La première consiste en la programmation, la validation et l'exploitation d'interfaces permettant l¿utilisation de routines d'optimisation directement dans le logiciel. La seconde comprend le développement de solutions pour le calcul automatisé des dérivées, toujours au sein de FreeFem++, en exploitant les paradigmes de la différentiation automatique. FreeFem++ est un environnement de développement intégré dédié à la résolution numérique d¿équations aux dérivées partielles en dimension 2 et 3. Son langage ergonomique permet à l'utilisateur d'exploiter aisément ses nombreux outils de création de maillages, de résolution de systèmes linéaires, ainsi que ses bibliothèques d'éléments finis, etc... Nous introduisons les nouvelles routines d'optimisation désormais accessibles depuis la bibliothèque de modules du logiciel. En particulier, le logiciel libre d'optimisation sous contraintes IPOPT, qui implémente une méthode de points intérieurs très robuste pour l¿optimisation en grande dimension. Nous appliquons avec succès ces algorithmes à une série de problèmes concrets parmi lesquels la résolution numérique de problèmes de sur- faces minimales, la simulation de condensats de Bose-Einstein, ou encore un problème de positionnement inverse en mécanique des fluides. Une version prototypique de FreeFem++ contenant les outils de différentiation automatique est présentée, après avoir exposé les principes fondamentaux de cette méthode de calcul de dérivées pour le calcul scientifique.The goal of this Ph.D. thesis was the development of tools for the FreeFem++ software in order to make optimization problems easier to deal with. This has been accomplished following two main directions. Firstly, a set of optimization softwares is interfaced and validated before making use of them. Then, we analyse the field of automatic differentiation as a potential mean of simplification for the users. FreeFem++ is an integrated development environment dedicated to numerically solving partial differential equations. Its high level language allows the user for a comfortable experience while using its mesh generation capabilities, linear system solvers, as well as finite elements capabilities. We describe the newly available optimization features, with a certain emphasis on the open source software IPOPT, which implements a state of the art interior points method for large scale optimization. These optimization tools are then used in a set of quite successful applications, among which minimal surfaces, Bose-Einstein condensate simulation, and an inverse positioning problem in the context of computational fluid dynamics. Finally, after an introduction to the techniques of algorithmic differentiation, we also present an unstable prototype version of FreeFem++ including automatic differentiation features.PARIS-JUSSIEU-Bib.électronique (751059901) / SudocSudocFranceF

Fragments d'Optimisation Différentiable - Théories et Algorithmes

MasterLecture Notes (in French) of optimization courses given at ENSTA (Paris, next Saclay), ENSAE (Paris) and at the universities Paris I, Paris VI and Paris Saclay (979 pages).Syllabus d’enseignements délivrés à l’ENSTA (Paris, puis Saclay), à l’ENSAE (Paris) et aux universités Paris I, Paris VI et Paris Saclay (979 pages)