Eigenvalue extraction for large finite element models using a new conjugate gradient algorithm

DOI<77::AID-CNM953>3.0.CO;2-7 10.1002/(SICI)1099-0887(199602)12:2<77::AID-CNM953>3.0.CO;2-7zbMath0840.73061OpenAlexW2030613147MaRDI QIDQ4869509

R. A. Lafreniere, Michael L. Accorsi

Publication date: 5 May 1996

Full work available at URL: https://doi.org/10.1002/(sici)1099-0887(199602)12:2<77::aid-cnm953>3.0.co;2-7

zbMATH Keywords

Lanczos methodmatrix inversionQR factorizationstatic problemreorthogonalizationequivalent tridiagonal matrix

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Finite element methods applied to problems in solid mechanics (74S05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

Cites Work

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• A partial preconditioned conjugate gradient method for large eigenproblems
• An orthogonal accelerated deflation technique for large symmetric eigenproblems
• Lanczos method for heat conduction analysis
• A projected conjugate gradient method for structural stability analysis with linear constraints
• The computational efficiency of a new minimization algorithm for eigenvalue analysis

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