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Minimization of p-Laplacian via the Finite Element Method in MATLAB
- 1.0556726 - ÚI 2023 RIV CH eng C - Conference Paper (international conference)
Matonoha, Ctirad - Moskovka, A. - Valdman, Jan
Minimization of p-Laplacian via the Finite Element Method in MATLAB.
Large-Scale Scientific Computing. Cham: Springer, 2022 - (Lirkov, I.; Margenov, S.), s. 533-540. Lecture Notes in Computer Science, 13127. ISBN 978-3-030-97548-7. ISSN 0302-9743.
[LSSC 2021: International Conference on Large-Scale Scientific Computations /13./. Sozopol (BG), 07.06.2021-11.06.2021]
R&D Projects: GA MŠMT 8J21AT001; GA ČR GA18-03834S
Institutional support: RVO:67985807 ; RVO:67985556
Keywords : Finite elements * Energy functional * Trust-region methods * p-Laplace equation * MATLAB code vectorization
OECD category: Pure mathematics; Applied mathematics (UTIA-B)
http://dx.doi.org/10.1007/978-3-030-97549-4_61
Minimization of energy functionals is based on a discretization by the finite element method and optimization by the trust-region method. A key tool to an efficient implementation is a local evaluation of the approximated gradients together with sparsity of the resulting Hessian matrix. Vectorization concepts are explained for the p-Laplace problem in one and two space-dimensions.
Permanent Link: http://hdl.handle.net/11104/0330880
Number of the records: 1