Massively parallel anisotropic mesh adaptation

Autor: Patrice Laure, Thierry Coupez, Hugues Digonnet, Luisa Silva
Přispěvatelé: Institut de Calcul Intensif (ICI), École Centrale de Nantes (ECN), Laboratoire Jean Alexandre Dieudonné (JAD), Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Centre de Mise en Forme des Matériaux (CEMEF), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2017
Předmět:
Zdroj: International Journal of High Performance Computing Applications
International Journal of High Performance Computing Applications, SAGE Publications, 2017, ⟨10.1177/1094342017693906⟩
ISSN: 1741-2846
1094-3420
DOI: 10.1177/1094342017693906
Popis: International audience; Mesh adaptation has proven to be very efficient for simulating transient multiphase computational fluid dynamics applications. In this work, we present a new parallel anisotropic mesh adaptation technique relying on an edge based error estimator. It provides a high level of accuracy while substantially reducing the computational effort. This technique enables a good capture of physical phenomena, boundary layers, interfaces, free surfaces and even multiphase turbulent flows, and has a great potential to simulate a large variety of applications. Current investigations explore the performance of the new algorithm on massively parallel resources. In this paper, we show that the developed adaptive meshing works very well in a parallel environment involving topological mesh modifications and dynamic repartitioning of parallel slots. It is also shown that the proposed methodology provides an additional gain in terms of computational cost due the production of a non-uniform mesh size distribution. Runs performed on national and European supercomputers will show the scalability and pertinence of our developments.
Databáze: OpenAIRE