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Domain Decomposition Methods in Science and Engineering XXVII

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Zdeněk Dostál

    1. VSB - Technical University of Ostrava, Ostrava, Czech Republic

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  2. Tomáš Kozubek

    1. VSB - Technical University of Ostrava, Ostrava, Czech Republic

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  3. Axel Klawonn

    1. Division of Mathematics, University of Cologne, Köln, Germany

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  4. Ulrich Langer

    1. Institute of Numerical Mathematics, Johannes Kepler University Linz, Linz, Austria

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  5. Luca F. Pavarino

    1. University of Pavia, Pavia, Italy

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  6. Jakub Šístek

    1. Institute of Mathematics, Czech Academy of Sciences, Prague, Czech Republic

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  7. Olof B. Widlund

    1. Courant Institute, New York University, New York, USA

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Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 149)

Included in the following conference series:

Conference proceedings info: DD 2022.

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Table of contents (62 papers)

  1. Front Matter

    Pages i-xxv
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  2. Plenary Talks (PT)

    1. Front Matter

      Pages 1-1
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    2. A Short Note on Solving Partial Differential Equations Using Convolutional Neural Networks

      • Viktor Grimm, Alexander Heinlein, Axel Klawonn
      Pages 3-14

    3. Optimized Robin Transmission Conditions for Anisotropic Diffusion on Arbitrary Meshes

      • Martin J. Gander, Laurence Halpern, Florence Hubert, Stella Krell
      Pages 15-26

    4. Domain Decomposition Algorithms for Neural Network Approximation of Partial Differential Equations

      • Hyea Hyun Kim, Hee Jun Yang
      Pages 27-37

    5. Convergence Bounds for One-Dimensional ASH and RAS

      • Marcus Sarkis, Maksymilian Dryja
      Pages 39-50

  3. Talks in Minisymposia

    1. Front Matter

      Pages 51-51
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    2. Weak Scalability of Domain Decomposition Methods for Discrete Fracture Networks

      • Stefano Berrone, Tommaso Vanzan
      Pages 53-60

    3. How Does the Partition of Unity Influence SORAS Preconditioner?

      • Marcella Bonazzoli, Xavier Claeys, Frederic Nataf, Pierre-Henri Tournier
      Pages 61-68

    4. Convergence of the Micro-Macro Parareal Method for a Linear Scale-Separated Ornstein-Uhlenbeck SDE

      • Ignace Bossuyt, Stefan Vandewalle, Giovanni Samaey
      Pages 69-76

    5. A Trefftz-Like Coarse Space for the Two-Level Schwarz Method on Perforated Domains

      • Miranda Boutilier, Konstantin Brenner, Victorita Dolean
      Pages 77-84

    6. On Global and Monotone Convergence of the Preconditioned Newton’s Method for Some Mildly Nonlinear Systems

      • Konstantin Brenner
      Pages 85-92

    7. Optimized Schwarz Method in Time for Transport Control

      • Duc-Quang Bui, Berangere Delourme, Laurence Halpern, Felix Kwok
      Pages 93-100

    8. An Overlapping Preconditioner for 2D Virtual Problems Posed in H(rot) with Irregular Subdomains

      • Juan G. Calvo, César Herrera, Filánder A. Sequeira
      Pages 101-108

    9. A Two-Level Restricted Additive Schwarz Method for Asynchronous Computations

      • Faycal Chaouqui, Daniel B. Szyld
      Pages 109-116

    10. Cross-Points in the Neumann-Neumann Method

      • Bastien Chaudet-Dumas, Martin J. Gander
      Pages 117-124

    11. A Preconditioner for Free-Surface Hydrodynamics BEM

      • Gabriele Ciaramella, Marco Gambarini, Edie Miglio
      Pages 125-132

    12. A Performance Comparison of Classical Volume and New Substructured One- and Two-Level Schwarz Methods in PETSc

      • Gabriele Ciaramella, Martin J. Gander, Serge Van Criekingen, Tommaso Vanzan
      Pages 133-140

    13. Semi-Discrete Analysis of a Simplified Air-Sea Coupling Problem with Nonlinear Coupling Conditions

      • Simon Clement, Florian Lemarie, Eric Blayo
      Pages 141-148

    14. A Block Jacobi Sweeping Preconditioner for the Helmholtz Equation

      • Ruiyang Dai
      Pages 149-156
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  1. Domain Decomposition Methods in Science and Engineering XXVII

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About this book

These are the proceedings of the 27th International Conference on Domain Decomposition Methods in Science and Engineering, which was held in Prague, Czech Republic, in July 2022.

Domain decomposition methods are iterative methods for solving the often very large systems of equations that arise when engineering problems are discretized, frequently using finite elements or other modern techniques. These methods are specifically designed to make effective use of massively parallel, high-performance computing systems.

The book presents both theoretical and computational advances in this domain, reflecting the state of art in 2022.



Editors and Affiliations

  • VSB - Technical University of Ostrava, Ostrava, Czech Republic

    Zdeněk Dostál, Tomáš Kozubek

  • Division of Mathematics, University of Cologne, Köln, Germany

    Axel Klawonn

  • Institute of Numerical Mathematics, Johannes Kepler University Linz, Linz, Austria

    Ulrich Langer

  • University of Pavia, Pavia, Italy

    Luca F. Pavarino

  • Institute of Mathematics, Czech Academy of Sciences, Prague, Czech Republic

    Jakub Šístek

  • Courant Institute, New York University, New York, USA

    Olof B. Widlund

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