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arXiv · 2312.17373

A non-intrusive neural-network based BFGS algorithm for parameter estimation in non-stationary elasticity

Stefan Frei·Jan Reichle·Stefan Volkwein
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Abstract

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.

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Stefan Frei, Jan Reichle, Stefan Volkwein. 2023-12-28. A non-intrusive neural-network based BFGS algorithm for parameter estimation in non-stationary elasticity. https://arxiv.org/abs/2312.17373

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