Extracting inelastic metal behaviour through inverse analysis: a shift in focus from material models to material behaviour

This article implements a new data-driven inverse analysis method, SelfSim (self-learning simulations), for extracting material behaviour of metals. SelfSim uses load-displacement measurements from structural tests whereby the material experiences non-uniform stresses and strains to extract the material constitutive behaviour in the form of a stress-strain database unconstrained by a pre-defined material model. The method is verified using simulated and physical experiments on metal structures. SelfSim successfully extracts the anisotropic response of aluminium from multiple tests. The method simplifies the laborious and lengthy process of developing a conventional material model whenever a new material constitutive behaviour is to be characterized.

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