Material parameter identification for clinching process simulation using neural network metamodels

Clinching is a mechanical joining method in which two sheet workpieces are clamped and locked together using a punch and a die. Process parameters for such joint elements are often designed based on numeric simulation. Before this step, the identification of good material parameters is crucial to get validated computational results. In this paper, neural network metamodels are used for this specific task as a means to deal with large computation time. The identified material parameters reduce significantly the error between computational results and experimental results.

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Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).