DUVIGNEAU , Regis

Population-based optimization methods like genetic algorithms and particle swarm optimization are very general and robust but can be costly since they require large number of function evaluations. The costly function evaluations can be replaced by cheaper models which are refered to as surrogate or meta models. Here we consider data-fitting...

Modern optimization methods like Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been found to be very robust and general for solving engineering design problems. They require the use of large population size and may suffer from slow convergence. Both of these lead to large number of function evaluations which can...

We analyze numerically two macroscopic models of crowd dynamics: the classical Hughes model and the second order model being an extension to pedestrian motion of the Payne-Whitham vehicular traffic model. The desired direction of motion is determined by solving an eikonal equation with density dependent running cost, which results in...

The objective of this study is to simulate the flow in the cooling duct of a Formula-E vehicle, and then optimize the duct shape to maximize the flow rate. In this perspective, weconsider a radiator model defined as a porous medium, implemented in a Finite-Volume codebased on the resolution of Reynolds-averaged Navier-Stokes equations. A...

We analyze numerically two macroscopic models of crowd dynamics: the classical Hughes model and the second order model being an extension to pedestrian motion of the Payne-Whitham vehicular traffic model. The desired direction of motion is determined by solving an eikonal equation with density dependent running cost, which results in...

We analyze numerically some macroscopic models of pedestrian motion to compare their capabilities of reproducing characteristic features of crowd behavior, such as travel times minimization and crowded zones avoidance, as well as complex dynamics like stop-and-go waves and clogging at bottlenecks. We compare Hughes' model with different running...

The design of car shapes requires a delicate balance between aesthetic and performance. While fluid simulation provides themeans to evaluate the aerodynamic performance of a given shape, its computational cost hinders its usage during the early explorative phases of design, when aesthetic is decided upon. We present an interactive system to...

National audience

We are interested by the general problem consisting of minimizing a functional of a state field solution of a PDE state equation. In Particular in this work, we optimize a 3D wing shape immersed an in inviscid flow to reduce drag. Whence, each evaluation of the cost functional is computationally expensive. For improving the convergence rate of...

This paper describes a new generic parametric modeller integrated into an automated optimization loop for shape optimization. The modeller enables the generation of shapes by selecting a set of design parameters that controls a twofold parameterization: geometrical - based on a skeleton approach - and architectural - based on the experience of...