Gradient Recovery-Type a Posteriori Error Estimates for Steady-State Poisson-Nernst-Planck Equations
Year: 2020
Author: Ruigang Shen, Shi Shu, Ying Yang, Mingjuan Fang
Advances in Applied Mathematics and Mechanics, Vol. 12 (2020), Iss. 6 : pp. 1353–1383
Abstract
In this article, we derive the a posteriori error estimators for a class of steady-state Poisson-Nernst-Planck equations. Using the gradient recovery operator, the upper and lower bounds of the a posteriori error estimators are established both for the electrostatic potential and concentrations. It is shown by theory and numerical experiments that the error estimators are reliable and the associated adaptive computation is efficient for the steady-state PNP systems.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/aamm.OA-2019-0046
Advances in Applied Mathematics and Mechanics, Vol. 12 (2020), Iss. 6 : pp. 1353–1383
Published online: 2020-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 31
Keywords: Poisson-Nernst-Planck equations gradient recovery a posteriori error estimate.