Numerical Results for Adaptive (negative norm) Constrained First Order System Least Squares Formulations

Authors

Andreas Schafelner, Johannes Kepler University of Linz
Panayot S. Vassilevski, Portland State UniversityFollow

Published In

Computers and Mathematics with Applications

Document Type

Article

Publication Date

2020

Subjects

Adaptivity -- computational studies

Abstract

We perform a follow-up 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.

Rights

©2020 The Author(s). Published by Elsevier Ltd.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Locate the Document

https://doi.org/10.1016/j.camwa.2020.08.025

DOI

10.1016/j.camwa.2020.08.025

Persistent Identifier

https://archives.pdx.edu/ds/psu/34808

Citation Details

Schafelner, A., & Vassilevski, P. S. (2020). Numerical results for adaptive (negative norm) constrained first order system least squares formulations. Computers & Mathematics with Applications.