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Computational Mechanics

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25-03-2023 | Original Paper

Frankenstein’s data-driven computing approach to model-free mechanics

Authors: Bram van der Heijden, Yunteng Wang, Gilles Lubineau

Published in: Computational Mechanics | Issue 6/2023

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Abstract

This paper proposes a data-driven method to predict mechanical responses for structures directly from full-field observations obtained on previously tested structures, with minimal introduction of arbitrary models. The fundamental concept is to directly use raw data, called patches from hereon, comprising displacement fields over large domains, obtained during data harvesting through full-field measurement. These displacement fields have been observed on domains of real structures, and hence are naturally viable solutions from static, kinematic, and constitutive viewpoint. We compile a library of such patches to compute response for new structures. Patches are assembled as pieces of a jigsaw puzzle, similar to how Frankenstein put his monster together from human patches. The approach is illustrated using a traditional beam problem for simplicity. However, the approach is not limited to beam or even solid mechanics, the concept can be applied to predict a wide range of physics and multi-physics phenomena.

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Title: Frankenstein’s data-driven computing approach to model-free mechanics
Authors: Bram van der Heijden
Yunteng Wang
Gilles Lubineau
Publication date: 25-03-2023
Publisher: Springer Berlin Heidelberg
Published in: Computational Mechanics / Issue 6/2023
Print ISSN: 0178-7675
Electronic ISSN: 1432-0924
DOI: https://doi.org/10.1007/s00466-023-02307-w

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