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The Augmented Lagrangian Method as a Framework for Stabilised Methods in Computational Mechanics
Department of Mathematics, University College London, London, United Kingdom.
Jönköping University, School of Engineering, JTH, Materials and Manufacturing.ORCID iD: 0000-0001-7352-1550
Department of Mathematics and Mathematical Statistics, Umeå University, Umeå, Sweden.
2023 (English)In: Archives of Computational Methods in Engineering, ISSN 1134-3060, E-ISSN 1886-1784, Vol. 30, p. 2579-2604Article in journal (Refereed) Published
Abstract [en]

In this paper we will present a review of recent advances in the application of the augmented Lagrange multiplier method as a general approach for generating multiplier-free stabilised methods. The augmented Lagrangian method consists of a standard Lagrange multiplier method augmented by a penalty term, penalising the constraint equations, and is well known as the basis for iterative algorithms for constrained optimisation problems. Its use as a stabilisation methods in computational mechanics has, however, only recently been appreciated. We first show how the method generates Galerkin/Least Squares type schemes for equality constraints and then how it can be extended to develop new stabilised methods for inequality constraints. Application to several different problems in computational mechanics is given.

Place, publisher, year, edition, pages
Springer, 2023. Vol. 30, p. 2579-2604
Keywords [en]
Constrained optimization, Iterative methods, Lagrange multipliers, Augmented lagrange multiplier methods, Augmented Lagrangian methods, Constrained optimi-zation problems, Constraint equation, Galerkin Least Squares, Iterative algorithm, Lagrange multiplier method, Penalty term, Stabilization methods, Stabilized method, Computational mechanics
National Category
Mathematics
Identifiers
URN: urn:nbn:se:hj:diva-59759DOI: 10.1007/s11831-022-09878-6ISI: 000920400800001Scopus ID: 2-s2.0-85146572606Local ID: HOA;intsam;860720OAI: oai:DiVA.org:hj-59759DiVA, id: diva2:1735158
Funder
eSSENCE - An eScience CollaborationSwedish Research Council, 2017-03911, 2018-05262, 2021-04925Available from: 2023-02-08 Created: 2023-02-08 Last updated: 2023-06-30Bibliographically approved

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Hansbo, Peter

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