L`équipe matériaux magnétiques - Ampère Lab

Ecole Centrale de Lyon - INSA de Lyon – Université Claude Bernard Lyon 1
Laboratoire Ampère
Unité Mixte de Recherche du CNRS - UMR 5005
Génie Electrique, Electromagnétisme, Automatique, Microbiologie environnementale
et Applications
Titre : Models for Active Drag Reduction
Laboratoire :
Département(s) concerné(s) :
Priorité principale :
Domaine scientifique principal :
Priorité secondaire :
Domaine scientifique secondaire :
Mots clés (5 max) :
Ampère, UMR CNRS 5005
MIS
M1 « Systèmes et performances »
Modélisation et réduction des équations de Navier-Stokes
M2 « Systèmes et multi-énergie »
Systèmes à fluide sous-pression
Aerodynamics, Partial Differential Equation, Model reduction,
Control oriented model, State/parameter estimation
Directeurs de thèse et comité d’encadrement
Directeur de thèse
Eric BIDEAUX
Comité d’encadrement (co-encadrant n°1)
Éric BIDEAUX, Damien EBERARD, Federico
BRIBIESCA ARGOMEDO, Michael DI LORETO
Collaboration(s)/partenariat(s) extérieurs
Thomas Castellain (LMFA), Bernd Noack (Pprime)
Contexte Scientifique (5 lignes max)
The main objective of this PhD consists on the development of control- and observation-oriented
models for active drag-reduction applications using pulsed-jet actuators. This is a complex task since
the system under consideration is governed by a set of coupled nonlinear partial differential equations
(PDEs) describing the fluid flow in a 3D domain. Further complicating the development of a controloriented model is the fact that pulsed-jet actuation is discontinuous in nature.
Objectif de la thèse, verrous scientifiques et contribution originale attendue (1 page max)
The main challenges are:
 Adequately capturing the global effect on the vehicle stemming from local phenomena
without including fine-grained turbulence models.
 Capturing the effect of the discontinuous high frequency pulsed-jet input in the variables
relevant for drag reduction purposes.
 Identifying the optimal sensor/actuator choices for reducing the overall energy consumption
of the system.
These challenges will likely require the development of averaged models in space and time; in space
for the average effect of the local phenomena and in time for the average effect of the high-frequency
inputs. These average models may be completed with 0D dynamic models that could represent the
evolution of some average properties in the system.
Programme de recherche et démarche scientifique proposée (1/2 page max)
The main tasks that will need to be addressed during the PhD are:
1. Model reduction: passing from a set of 3D nonlinear equations to a more manageable 1D
PDE model (for instance, a linear parameter-varying model) that retains the relevant
information relating to aerodynamic drag. Since the main transport phenomenon will
doubtlessly be the advection due to the speed of the vehicle, another natural approach would
be to use delay systems to either directly model the system or as an approximation tool for
the 1D PDE system.
2. Both PDE and delay tools can then be used to analyze the models developed in Task 1 with
the dual purpose of identifying their properties (e.g. stabilizability, observability) and also
suggesting the best actuator and sensor locations for active drag reduction purposes.
Profil du candidat recherché (prérequis) :
The Phd candidate must have a solid knowledge in applied mathematics and control theory with a
desirable background in fluid mechanics.
Compétences développées au cours de la thèse et perspective professionnelle (5 lignes max)
During his PhD, the candidate will develop high level skills in mathematic modeling of complex
systems in fluid mechanics. Active control of fluid systems having a growing interest in industry and
academics, the candidate should have many opportunities at the end of his PhD.
Bibliographie sur le sujet de thèse
(1) Pastoor, M., Henning, L., Noack, B., King, R. and Tadmor, G. (2008). "Feedback shear layer
control for bluff body drag reduction." Jour. Fluid Mech. 608: 161–196.
(2) Seifert, A., Stalnov, Sperber, O.D., Arwatz, G. Palei, David, V.S. Dayan, I., Fono. I. Large
Trucks Drag Reduction using Active Flow Control. The Aerodynamics of Heavy Vehicles II:
Trucks, Buses and Trains. Lecture Notes in Applied and Computational Mechanics Volume
41, 115-133. 2009
(3) Vukasinovic, B., Rusak, Z. and Glezer, A. (2010). "Dissipative small-scale actuation of a
turbulent shear layer." J. Fluid Mech. 656: 51-81.
(4) Östh, J., Noack, B.R., Krajnović, S., Barros, D. and Borée, J. (2014), "On the need for a
nonlinear subscale turbulence term in POD models as exemplified for a high-Reynoldsnumber flow over an Ahmed body" J. Fluid Mech. 747: 518–544.Oxlade, A. R., Morrison, J. F.,
Qubain, A. and Rigas, G. (2015). "High-frequency forcing of a turbulent axisymmetric wake." J.
Fluid Mech. 770: 305-318.
(5) Pfeiffer, J. and King, R. (2012). Multivariable closed-loop flow control of drag and yaw moment
for a 3d bluff body. Proceedings of the 6th AIAA Flow Control Conference.
(6) Control of Fluid Flow, Lecture Notes in Control and Information Sciences, Volume 330 2006,
Editors: Petros Koumoutsakos, Igor Mezic, ISBN: 978-3-540-25140-8