A non-intrusive neural-network based BFGS algorithm for parameter estimation in non-stationary elasticity
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arXiv
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866911990347202560 |
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| author | Frei, Stefan Reichle, Jan Volkwein, Stefan |
| author_facet | Frei, Stefan Reichle, Jan Volkwein, Stefan |
| contents | We present a non-intrusive gradient and a non-intrusive BFGS algorithm for parameter estimation problems in non-stationary elasticity. To avoid multiple (and potentially expensive) solutions of the underlying partial differential equation (PDE), we approximate the PDE solver by a neural network within the algorithms. The network is trained offline for a given set of parameters. The algorithms are applied to an unsteady linear-elastic contact problem; their convergence and approximation properties are investigated numerically. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2312_17373 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A non-intrusive neural-network based BFGS algorithm for parameter estimation in non-stationary elasticity Frei, Stefan Reichle, Jan Volkwein, Stefan Numerical Analysis Optimization and Control We present a non-intrusive gradient and a non-intrusive BFGS algorithm for parameter estimation problems in non-stationary elasticity. To avoid multiple (and potentially expensive) solutions of the underlying partial differential equation (PDE), we approximate the PDE solver by a neural network within the algorithms. The network is trained offline for a given set of parameters. The algorithms are applied to an unsteady linear-elastic contact problem; their convergence and approximation properties are investigated numerically. |
| title | A non-intrusive neural-network based BFGS algorithm for parameter estimation in non-stationary elasticity |
| topic | Numerical Analysis Optimization and Control |
| url | https://arxiv.org/abs/2312.17373 |