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

J.N. Jomo (Corresponding author), F. de Prenter, M. Elhaddad, D. D'Angella, C.V. Verhoosel, S. Kollmannsberger, J.S. Kirschke, V. Nübel, E.H. van Brummelen, E. Rank

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

21 Citaten (Scopus)
46 Downloads (Pure)

Samenvatting

The finite cell method is a 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. The 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. This significantly limits 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 systems.

Originele taal-2Engels
Pagina's (van-tot)14-30
Aantal pagina's17
TijdschriftFinite Elements in Analysis and Design
Volume163
DOI's
StatusGepubliceerd - 1 okt 2019

Vingerafdruk

Duik in de onderzoeksthema's van 'Robust and parallel scalable iterative solutions for large-scale finite cell analyses'. Samen vormen ze een unieke vingerafdruk.

Citeer dit