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Riccardo TORCHIO, winner of the 2020 Academic Thesis Award

Riccardo TORCHIO is the winner of the Academic Thesis Award 2020 with 7 other PhDs for his thesis presented in 2019 and entitled "Extending the Unstructured PEEC Method to Magnetic, Transient, and Stochastic Electromagnetic Problems". The academic thesis prizes were awarded to eight Doctors using criteria of excellence specific to each discipline and represented by the 13 doctoral schools on site.
Winner of the 2020 Academic Thesis Award: Riccardo TORCHIO

Riccardo TORCHIO, lauréat du prix de thèse académique 2020Thesis title: Extending the Unstructured PEEC Method to Magnetic, Transient, and Stochastic Electromagnetic Problems

Doctoral school: EEATS - Electronics, Electrical Engineering, Automation, Signal Processing

Host laboratory: Grenoble Electrical Engineering Laboratory (G2Elab - CNRS / UGA / Grenoble INP-UGA)

Thesis supervisors: Olivier CHADEBEC (joint supervisor Gérard MEUNIER) and Federico MORO (joint supervisor with the University of Padua - Italy)

Key words: integral, electromagnetic, formulation, PEEC, low-rank

This thesis aims to extend and improve the capability of an electromagnetic modeling method, known as Generalized Partial Element Equivalent Circuit (PEEC). The use of this method is made necessary by the increasing need for fast and accurate numerical methods, which can help engineers in the design of new electrical engineering components.

The main focus of this thesis is to extend and improve the applicability and the accuracy of the Unstructured Partial Element Equivalent Circuit (PEEC) method. The interest on this subject is spurred by the growing need of fast and efficient numerical methods, which may help engineers during the design and other stages of the production of new generation electric components.
First, the PEEC method in its unstructured form is extended to magnetic media. In this regard, two formulations are developed and compared: the first one, based on the Amperian interpretation of the magnetization phenomena, is derived from the existing literature concerning the standard (structured) version of PEEC; the second one, based on the Coulombian interpretation of the magnetization phenomena, is proposed by the author with the aim of collocating PEEC in the context of Volume Integral Equation methods.
Then, the application of low-rank compression techniques to PEEC is investigated. Two different methods are applied: the first is based on hierarchical matrices (H and H2 matrices) whereas the second is based on hierarchical-semi-separable (HSS) matrices. The two methods are compared and the main numerical issues which emerge by applying low-rank techniques to PEEC are analyzed.
Finally, the developed unstructured PEEC method is combined with the Marching On-in-Time scheme for the study of fast transient phenomena with wide range of harmonics. Moreover, two different stochastic PEEC methods are developed for uncertainty quantification analysis. The first is based on the Polynomial Chaos expansion while the second is based on the Parametric Model Order Reduction technique coupled with spectral expansion.

> Discover all the winners of 2020 Thesis Awards

Updated on June 3, 2020


The College and the doctoral schools (except Philo) moved on September 1st, 2020 to join the Maison Jean Kuntzmann at 110 rue de la Chimie 38400 Saint-Martin-d'Hères on the University Campus (Tram B and C, stops "Bibliothèques universitaires").
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