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A non-intrusive neural-network based BFGS algorithm for parameter estimation in non-stationary elasticity (2312.17373v2)
Published 28 Dec 2023 in math.NA, cs.NA, and math.OC
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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