• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 2
  • 2
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Inertial Gradient-Descent algorithms for convex minimization / Algorithmes de descente de gradient inertiels pour la minimisation convexe.

Apidopoulos, Vasileios 11 October 2019 (has links)
Cette thèse porte sur l’étude des méthodes inertielles pour résoudre les problèmes de minimisation convexe structurés. Depuis les premiers travaux de Polyak et Nesterov, ces méthodes sont devenues très populaires, grâce à leurs effets d’accélération. Dans ce travail, on étudie une famille d’algorithmes de gradient proximal inertiel de type Nesterov avec un choix spécifique de suites de sur-relaxation. Les différentes propriétés de convergence de cette famille d’algorithmes sont présentées d’une manière unifiée, en fonction du paramètre de sur-relaxation. En outre, on étudie ces propriétés, dans le cas des fonctions lisses vérifiant des hypothèses géométriques supplémentaires, comme la condition de croissance (ou condition de Łojasiewicz). On montre qu’en combinant cette condition de croissance avec une condition de planéité (flatness) sur la géométrie de la fonction minimisante, on obtient de nouveaux taux de convergence. La stratégie adoptée ici, utilise des analogies du continu vers le discret, en passant des systèmes dynamiques continus en temps à des schémas discrets. En particulier, la famille d’algorithmes inertiels qui nous intéresse, peut être identifiée comme un schéma aux différences finies d’une équation/inclusion différentielle. Cette approche donne les grandes lignes d’une façon de transposer les différents résultats et leurs démonstrations du continu au discret. Cela ouvre la voie à de nouveaux schémas inertiels possibles, issus du même système dynamique. / This Thesis focuses on the study of inertial methods for solving composite convex minimization problems. Since the early works of Polyak and Nesterov, inertial methods become very popular, thanks to their acceleration effects. Here, we study a family of Nesterov-type inertial proximalgradient algorithms with a particular over-relaxation sequence. We give a unified presentation about the different convergence properties of this family of algorithms, depending on the over-relaxation parameter. In addition we addressing this issue, in the case of a smooth function with additional geometrical structure, such as the growth (or Łojasiewicz) condition. We show that by combining growth condition and a flatness-type condition on the geometry of the minimizing function, we are able to obtain some new convergence rates. Our analysis follows a continuous-to-discrete trail, passing from continuous-on time-dynamical systems to discrete schemes. In particular the family of inertial algorithms that interest us, can be identified as a finite difference scheme of a differential equation/inclusion. This approach provides a useful guideline, which permits to transpose the different results and their proofs from the continuous system to the discrete one. This opens the way for new possible inertial schemes, derived by the same dynamical system.
2

Interface Balance Laws, Growth Conditions and Explicit Interface Modeling Using Algebraic Level Sets for Multiphase Solids with Inhomogeneous Surface Stress

Pavankumar Vaitheeswaran (9435722) 16 December 2020 (has links)
Interface balance laws are derived to describe transport across a phase interface. This is used to derive generalized conditions for phase nucleation and growth, valid even for solids with inhomogeneous surface stress.<div><br></div><div>An explicit interface tracking approach called Enriched Isogeometric Analysis (EIGA) is used to simulate phase evolution. Algebraic level sets are used as a measure of distance and for point projection, both necessary operations in EIGA. Algebraic level sets are observed to often fail for surfaces. Rectification measures are developed to make algebraic level sets more robust and applicable for general surfaces. The proposed methods are demonstrated on electromigration problems. The simulations are validated by modeling electromigration experiments conducted on Cu-TiN line structures.</div><div><br></div><div>To model topological changes, common in phase evolution problems, Boolean operations are performed on the algebraic level sets using R-functions. This is demonstrated on electromigration simulations on solids with multiple voids, and on a bubble coalescence problem. </div>

Page generated in 0.1021 seconds