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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.12026 |
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| _version_ | 1866913548316180480 |
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| author | Green, Kiefer Antil, Harbir |
| author_facet | Green, Kiefer Antil, Harbir |
| contents | This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from computational geometry. They may enable experimentation with novel mesh generation techniques and could simplify the implementation of methods such as multigrid. We also implement quadrature methods following the work of Grundmann and Moller. These methods have been overlooked in the past but are more efficient than traditional tensor product methods. The proposed framework is applied to several standard examples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_12026 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Generic MATLAB Toolbox to Approximate PDEs Using Computational Geometry Green, Kiefer Antil, Harbir Numerical Analysis This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from computational geometry. They may enable experimentation with novel mesh generation techniques and could simplify the implementation of methods such as multigrid. We also implement quadrature methods following the work of Grundmann and Moller. These methods have been overlooked in the past but are more efficient than traditional tensor product methods. The proposed framework is applied to several standard examples. |
| title | A Generic MATLAB Toolbox to Approximate PDEs Using Computational Geometry |
| topic | Numerical Analysis |
| url | https://arxiv.org/abs/2410.12026 |