Efficient jacobian matrix determination for H2 representations of nonlinear electrostatic surface integral equations

John C. Young; Robert J. Adams; Stephen D. Gedney

doi:10.47037/2020.ACES.J.351101

Efficient jacobian matrix determination for H² representations of nonlinear electrostatic surface integral equations

John C. Young
, Robert J. Adams
, Stephen D. Gedney

Producción científica: Article › revisión exhaustiva

Resumen

In this paper, a nonlinear electrostatic surface integral equation is presented that is suitable for predicting corrosion-related fields. Nonlinear behavior arises due to electrochemical reactions at polarized surfaces. Hierarchical H² matrices are used to compress the discretized integral equation for the fast solution of large problems. A technique based on randomized linear algebra is discussed for the efficient computation of the Jacobian matrix required at each iteration of a nonlinear solution.

Idioma original	English
Páginas (desde-hasta)	1264-1265
Número de páginas	2
Publicación	Applied Computational Electromagnetics Society Journal
Volumen	35
N.º	11
DOI	https://doi.org/10.47037/2020.ACES.J.351101
Estado	Published - nov 2020

Nota bibliográfica

Publisher Copyright:
© ACES.

Financiación

This work was supported in part by Office of Naval Research Grant N00014-16-1-3066. This work was supported in part by Office of Naval N00014-16-1-3066.

Financiadores	Número del financiador
Office of Naval N00014-16-1-3066
Office of Naval Research Naval Academy	N00014-16-1-3066

ASJC Scopus subject areas

Astronomy and Astrophysics
Electrical and Electronic Engineering

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10.47037/2020.ACES.J.351101

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abstract = "In this paper, a nonlinear electrostatic surface integral equation is presented that is suitable for predicting corrosion-related fields. Nonlinear behavior arises due to electrochemical reactions at polarized surfaces. Hierarchical H2 matrices are used to compress the discretized integral equation for the fast solution of large problems. A technique based on randomized linear algebra is discussed for the efficient computation of the Jacobian matrix required at each iteration of a nonlinear solution.",

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