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Sor vs. conjugate gradients in a finite element discretization
Author(s) -
Fried Isaac,
Metzler Jim
Publication year - 1978
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.1620120809
Subject(s) - discretization , finite element method , conjugate gradient method , mathematics , conjugate , mathematical analysis , biconjugate gradient method , linear system , derivation of the conjugate gradient method , set (abstract data type) , conjugate residual method , geometry , mathematical optimization , computer science , engineering , structural engineering , gradient descent , machine learning , artificial neural network , programming language
Sucessive Overrlaxation and Conjugate Gradients are used to solve the linear algebraic system set up with finite elements for the discretization of a plane, linear, head conducting problem. It is numerically shown that even with the optimal overrelaxation factor SOR is hardly superior to CG which is decisively simpler to program.