L2EP

L2EP Logo

LABORATOIRE D'ELECTROTECHNIQUE ET D'ELECTRONIQUE DE PUISSANCE DE LILLE

Recherche, Développement et Innovation en Génie Electrique

Seminar in OMN TEAM

The research team OMN works on different numerical methods associated to electromagnetic field computation. We organize the Junior Seminar in LILLIAD Learning center innovation by our Ph.D. students, as well as our postdocs, and Invited Seminar by the external researchers.

If you would like to give us a talk or have some collaboration ideas about our work, please contact Zuqi who is in charge of the seminar, we can invite you to Lille.
The seminar can be held in English (or French) as you like. There is no limit for the duration of the seminar.

Seminars between Ph.D Student:

More details

  

Upcoming seminars:

TBA on December, 2019, Invited Seminar

Schedule

Olga MULA (Paris Dauphine University): TBA


 

 

November 28, 2019 at 14h00, Invited Seminar (Visiting Ph.D student from Hokkaido University


Shingo Hiruma (Hokkaido University, Japan)

Shingo Hiruma received the B.E. and M.E. degrees from Hokkaido University, Sapporo, Japan in 2017 and 2019. He is currently a Ph.D. student in Hokkaido University, and a research fellow of Japan Society for the Promotion of Science (JSPS). His research interest is the computational electromagnetism using model order reduction technique.

Model order reduction via Cauer circuit representation of quasi-static Maxwell equations

In this presentation, we discuss the relation between the quasi-static Maxwell equations and Cauer circuit representation. Starting from a discussion of 1-D model, Kameari’s Cauer ladder network (CLN) method is introduced. It is shown that the CLN method is equivalent to the self-adjoint Lanczos algorithm when the quasi-static Maxwell equations are discretized by the finite element method. From this relation, a new method is formulated which allow to approximate a given transfer function by a continued fraction.


 

 

July 8, 2019 at 14h00, Invited Seminar


Pr. Stéphane CLENET (ENSAM)

Stéphane Clénet is full professor of electrical engineering at Ecole Nationale Supérieure d’Arts et Métiers (ENSAM), France. After the completion of his PhD, he was Associate Professor at the University of Lille in 1994 before being appointed as full professor in 2002 at ENSAM. In 2008, he was visiting professor as Fulbright Grantee at the University of Akron (USA) in 2008 and 2014 and at Mc Gill University (Canada) in 2015. From 2007 to 2014, he ran a research team in the field of computational electromagnetics and its applications involving more than 25 professors, post docs and PhD students. From 2016 to 2019, he was the director of the campus ENSAM of Lille. He works on the development of 3D Finite Element Model in low frequency. Since 2004, his research focuses mainly on uncertainty quantification in computational electromagnetics based on stochastic approaches and also on Model Order Reduction technics (POD, PGD…). He is co-author of 85 publications in international journals. He has collaborated with numerous researchers from different universities in France but also from abroad like in Liège (Belgium), Akron (USA), Santa Catarina (Brésil), Mc Gill and Laval (Canada), Aalto (Finland), Tsinghua (China), Aachen (Germany). He develops numerous research projects in partnership with major companies like EdF, Valeo, CEA.

Why and how uncertain quantification can be useful in low frequency electromagnetism?

In some applications represented by very accurate models (the modelling and the numerical errors are negligible), if a gap exists between the measurements, assuming perfect, and the results given by the numerical model, it comes from deviations on input parameters which are not in the ”real world” equal to their prescribed values.
The origins of these deviations are numerous and are related to either a lack of knowledge or uncontrolled variations of quantities like temperature, pressure, magnetization. To account for these uncertain deviations on model parameters, the stochastic approach can be used. The model parameters as well as the outputs are then random fields or variables. Several methods are available in the literature to solve stochastic models like sampling methods, perturbation methods or approximation methods. In this presentation, we propose an overview on the solution of stochastic problems in computational electromagnetics. Some applications will be presented in order to illustrate the possibilities offered by this approach Finally, recent numerical techniques proposed in the literature to alleviate the cumbersome needs of resources in terms of memory and time calculation of the stochastic approach particularly due to the the curse of dimensionality appearing when the number of uncertain parameters increases.


 

 

June 27, 2019, Invited Seminar (Invited Prof. of ULille)

Dr. Shuai YAN (Institute of Electrical Engineering, Chinese Academy of Science)

Shuai Yan received the B.S. degree in Mathematics and Applied Mathematics from Beijing Normal University in 2007 and the M.S. degree in Computational Mathematic also from Beijing Normal University in 2010. She received the Ph.D. degree in Computational Optics in University of Erlangen-Nuremberg in Germany, 2014. After that, she joined the Chinese Academy of Science as an Associated Researcher. She has published more than ten papers in international journals. Her current research interests are model reduction techniques for full wave analysis and optimization of high frequency RFID systems and also efficient solvers for multi-physics analysis in integrated circuit design.

Title: Model Order Reduction with POD/PGD and Related Applications in Computational Electromagnetics

Modern industrial development brings new challenges to computational electromagnetics by introducing extremely computationally intensive problems and the needs of real-time simulation. Model order reduction can help with tacking these challenges from two perspectives. One is to solve the problems with less computational cost in time and memory, another is to build a compact parametric model from an “offline process” which can be used to achieve a fast solution during an “online process”. POD and PGD are two important MOR techniques that attracts much attention in recent years. In this presentation, I will discuss about the implementation of POD and PGD in both static and high frequency problems. Issues including complex domains, high dimensionality as well as adaptive algorithms will be addressed.


 

 

June 13, 2019, Junior Seminar


Dr. Emna JAIEM

Emna Jaïem obtained a PhD degree in Applied Mathematics from Tunis El Manar University, Tunis, Tunisia in July 2016. During her PhD thesis, she investigated the geometrical inverse problem related to the identification of defects in mechanical structures from, on the one hand, overdetermined boundary data and, on the other hand sub-Cauchy data. Indeed, her research fields include shape optimization (shape derivative, topological derivative, level set method, …). In September 2017, her work was recognized with the TWMA (Tunisian Women Mathematicians’ Association) award for the best PhD thesis in Applied Mathematics for Tunisian women. She is currently a postdoctoral researcher at L2EP working on the numerical analysis of electromagnetic fields and more precisely on spectral methods (Harmonic Balance Method).

Harmonic balance finite element method applied to electromagnetic problems

The time stepping approach is a well-known numerical method to model electromagnetic problems. However, it can present some drawbacks since it requires expensive computation time in the case of a large transient state. To overcome this problem, harmonic balance method can be used. In the first part of the presentation, we introduce this method. Then, we apply it for electrical machines taking into account the motion. Furthermore, we compare the solutions obtained by the harmonic balance finite element method coupled, on the one hand, with the A formulation and, on the other hand, with Ω formulation with those obtained by the reference method; namely the time stepping finite element method.

Since harmonic balance method relies on the representation of time-periodic function by a truncated Fourier series, the problem of harmonics selection is discussed in the second part of the presentation. A novel approach based on time residual is proposed to solve a nonlinear magnetostatic problem using harmonic balance method.


 

 

June 07, 2019, Invited Seminar


Pr. Mircea M. RADULESCU (Université Technique de Cluj-Napoca, Roumanie)

Mircea M. Radulescu received the Dipl.-Ing. degree in electrical engineering (with honors) from the Technical University of Cluj-Napoca, Cluj-Napoca, Romania, in 1978, and the Ph.D. degree in electrical engineering from the Polytechnic University of Timisoara, Timisoara, Romania, in 1993. Since 1983, he has been with the Faculty of Electrical Engineering, Technical University of Cluj-Napoca, where he is currently a Full Professor in the Department of Electric Machines and Drives, and Head of the Special Electric Machines and Light Electric Traction (SEMLET) Research Laboratory.
He is the author or co-author of more than 180 published scientific papers in refereed technical journals and international conference and symposium proceedings.
His teaching and research activities include classical and special electric machines; computer-aided design of electromechanical devices; design and control of small electronically-commutated motors; actuators and mechatronic drives; light electric traction systems; design and analysis of small-scale renewable energy equipment.
He was an Invited Professor at Swiss Federal Institute of Technology Lausanne – EPFL, Switzerland; Helsinki University of Technology, Espoo, Finland; RWTH Aachen, Aachen, Germany; University of Akron, Akron, USA; University ‘Pierre et Marie Curie’, Paris, France; University of Picardie ‘Jules Verne’, Amiens, France, and Centrale Lille,
Villeneuve d’Ascq, France.
He is an Associate Editor of the international scientific quarterly ‘Electromotion’. His biography is listed in several editions of ‘Who’s Who in the World’ and ‘Who’s Who in Science and Engineering’.
Prof. Radulescu is a Senior Member of IEEE, USA and a Member of IET, UK. He is also a member of the International Steering Committees of several conferences and symposia in the field of electric motor drives, electric traction, and renewable energy.

Nouvelles topologies de générateurs électriques pour micro-éoliennes

Contenu

Introduction aux éoliennes à petite échelle
Exigences de conception des générateurs électriques pour les micro-systèmes de conversion d’énergie éolienne
Analyse comparative de la conception des nouvelles topologies des micro-aérogénérateurs électriques
Conclusion


 

 

June 04, 2019, Visiting Professor from Shanghai Maritime University


Dr. Hao CHEN (Shanghai Maritime University, China)

Hao Chen (M’ 17) was born in Jiangsu, China, in 1985. He received the B.E. degree in automation from Shanghai Maritime University, Shanghai, China, the M.E. and Ph.D. degrees in electrical engineering from the University of Nantes, Nantes, France, in 2008, 2010, and 2014, respectively. He is currently a lecture with Shanghai Maritime University China. His research interests include designing, modeling and control of electrical machines, and wind or tidal energy conversion system.

Research on power electronics and electric drives at Shanghai Maritime University

In the presentation, I firstly introduce Shanghai Maritime University and the colleges briefly. Then, I will focus on the introduction of the department of electrical engineering, especially the research institute of power drive and control. At last, I will present some personal research interests.


 

 

Past seminars:

2018
2017