Numerical results for adaptive (negative norm) constrained first order system least squares formulations

We perform a followup computational study of the recently proposed space–time first order system least squares ( FOSLS ) method subject to constraints referred to as CFOSLS where we now combine it with the new capability we have developed, namely, parallel adaptive mesh refinement (AMR) in 4D. The A...

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Veröffentlicht in:	Computers & mathematics with applications (1987) 2021-08, Vol.95 (C), p.256-270
Hauptverfasser:	Schafelner, Andreas, Vassilevski, Panayot S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptivity CFOSLS Constraints Finite element method Grid refinement (mathematics) Least squares MATHEMATICS AND COMPUTING Space–time
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container_title	Computers & mathematics with applications (1987)
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creator	Schafelner, Andreas Vassilevski, Panayot S.
description	We perform a followup computational study of the recently proposed space–time first order system least squares ( FOSLS ) method subject to constraints referred to as CFOSLS where we now combine it with the new capability we have developed, namely, parallel adaptive mesh refinement (AMR) in 4D. The AMR is needed to alleviate the high memory demand in the combined space time domain and also allows general (4D) meshes that better follow the physics in space–time. With an extensive set of computational experiments, performed in parallel, we demonstrate the feasibility of the combined space–time AMR approach in both two space plus time and three space plus time dimensions.
doi_str_mv	10.1016/j.camwa.2020.08.025
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subjects	Adaptivity CFOSLS Constraints Finite element method Grid refinement (mathematics) Least squares MATHEMATICS AND COMPUTING Space–time
title	Numerical results for adaptive (negative norm) constrained first order system least squares formulations
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