Robust and parallel scalable iterative solutions for large-scale finite cell analyses

Autor: V. Nübel, M. Elhaddad, E.H. van Brummelen, J. Jomo, F. de Prenter, Davide D’Angella, Ernst Rank, Jan S. Kirschke, Stefan Kollmannsberger, Clemens V. Verhoosel
Přispěvatelé: Energy Technology, Center for Analysis, Scientific Computing & Appl.
Rok vydání: 2019
Předmět:
FOS: Computer and information sciences
Parallel computing
Discretization
Computer science
Computation
G.1.8
0211 other engineering and technologies
Preconditioning
02 engineering and technology
01 natural sciences
Computational science
G.1.10
FOS: Mathematics
Mathematics - Numerical Analysis
0101 mathematics
021106 design practice & management
Preconditioner
Applied Mathematics
Numerical analysis
Finite cell method
Computer Science - Numerical Analysis
General Engineering
Numerical Analysis (math.NA)
Supercomputer
Computer Graphics and Computer-Aided Design
Finite element method
65N85
65N30
010101 applied mathematics
Range (mathematics)
hp-refinement
Computer Science - Distributed
Parallel
and Cluster Computing
Scalability
Immersed methods
Iterative solvers
Distributed
Parallel
and Cluster Computing (cs.DC)
High performance computing
Analysis
Zdroj: Finite Elements in Analysis and Design
Finite Elements in Analysis and Design, 163, 14-30. Elsevier
ISSN: 0168-874X
0045-7825
DOI: 10.1016/j.finel.2019.01.009
Popis: The finite cell method is a highly flexible discretization technique for numerical analysis on domains with complex geometries. By using a non-boundary conforming computational domain that can be easily meshed, automatized computations on a wide range of geometrical models can be performed. Application of the finite cell method, and other immersed methods, to large real-life and industrial problems is often limited due to the conditioning problems associated with these methods. These conditioning problems have caused researchers to resort to direct solution methods, which signifi- cantly limit the maximum size of solvable systems. Iterative solvers are better suited for large-scale computations than their direct counterparts due to their lower memory requirements and suitability for parallel computing. These benefits can, however, only be exploited when systems are properly conditioned. In this contribution we present an Additive-Schwarz type preconditioner that enables efficient and parallel scalable iterative solutions of large-scale multi-level hp-refined finite cell analyses.
Comment: 32 pages, 17 figures
Databáze: OpenAIRE
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