An end-to-end data-driven optimization framework for constrained trajectories

Abstract Many real-world problems require to optimize trajectories under constraints. Classical approaches are often based on optimal control methods but require an exact knowledge of the underlying dynamics and constraints, which could be challenging or even out of reach. In view of this, we leverage data-driven approaches to design a new end-to-end framework which is dynamics-free for optimized and realistic trajectories. Trajectories are here decomposed on function basis, trading the initial infinite dimension problem on a multivariate functional space for a parameter optimization problem. Then a maximum a posteriori approach which incorporates information from data is used to obtain a new penalized optimization problem. The penalized term narrows the search on a region centered on data and includes estimated features of the problem. We apply our data-driven approach to two settings in aeronautics and sailing routes optimization. The developed approach is implemented in the Python library PyRotor

An end-to-end data-driven optimisation framework for constrained trajectories

28 pagesMany real-world problems require to optimise trajectories under constraints. Classical approaches are based on optimal control methods but require an exact knowledge of the underlying dynamics, which could be challenging or even out of reach. In this paper, we leverage data-driven approaches to design a new end-to-end framework which is dynamics-free for optimised and realistic trajectories. We first decompose the trajectories on function basis, trading the initial infinite dimension problem on a multivariate functional space for a parameter optimisation problem. A maximum \emph{a posteriori} approach which incorporates information from data is used to obtain a new optimisation problem which is regularised. The penalised term focuses the search on a region centered on data and includes estimated linear constraints in the problem. We apply our data-driven approach to two settings in aeronautics and sailing routes optimisation, yielding commanding results. The developed approach has been implemented in the Python library PyRotor

Analysis of interfacial forces on the physics of two-phase flow and hyperbolicity of the two-fluid model

The scope of this Master Thesis is the two-fluid model. This study aims at analysing their ill-posedness, showing how it is related to non-hyperbolicity and giving a measurement that I call the numerical hyperbolicity. As a cure to this important issue, we will propose a combination of physical and mathematical solutions. The physical forces that we will focus on are two interfacial forces: the interfacial pressure and the virtual mass. We will quantify the minimum correction that is necessary to ensure hyperbolicity of the two-fluid model. We will then compare the two forces and combine them into an aggregated correction. This correction is proposed for use as a criteria in the next generation of nuclear reactor thermal-hydraulics codes

Simulation numérique directe de bulles sur maillage adaptatif avec algorithmes distribués

This PhD work presents the implementation of the simulation of two-phase flows in conditions of water-cooled nuclear reactors, at the scale of individual bubbles. To achieve that, we study several models for Thermal-Hydraulic flows and we focus on a technique for the capture of the thin interface between liquid and vapour phases. We thus review some possible techniques for Adaptive Mesh Refinement (AMR) and provide algorithmic and computational tools adapted to patch-based AMR, which aim is to locally improve the precision in regions of interest. More precisely, we introduce a patch-covering algorithm designed with balanced parallel computing in mind. This approach lets us finely capture changes located at the interface, as we show for advection test cases as well as for models with hyperbolic-elliptic coupling. The computations we present also include the simulation of the incompressible Navier-Stokes system, which models the shape changes of the interface between two non-miscible fluids.Ce travail de thèse présente l'implémentation de la simulation d'écoulements diphasiques dans des conditions de réacteurs nucléaires à caloporteur eau, à l'échelle de bulles individuelles. Pour ce faire, nous étudions plusieurs modèles d'écoulements thermohydrauliques et nous focalisons sur une technique de capture d'interface mince entre phases liquide et vapeur. Nous passons ainsi en revue quelques techniques possibles de maillage adaptatif (AMR) et nous fournissons des outils algorithmiques et informatiques adaptés à l'AMR par patchs dont l'objectif localement la précision dans des régions d'intérêt. Plus précisément, nous introduisons un algorithme de génération de patchs conçu dans l'optique du calcul parallèle équilibré. Cette approche nous permet de capturer finement des changements situés à l'interface, comme nous le montrons pour des cas tests d'advection ainsi que pour des modèles avec couplage hyperbolique-elliptique. Les calculs que nous présentons incluent également la simulation du système de Navier-Stokes incompressible qui modélise la déformation de l'interface entre deux fluides non-miscibles