Improving material parameter identification using spline FFD-based optimization of specimen shape

Morgane Chapelier (1, 2) , Robin Bouclier (2, 1) , Jean-Charles Passieux (1)

1 ICA - Institut Clément Ader
2 IMT - Institut de Mathématiques de Toulouse UMR5219

Given the today genuine digital revolution experienced in experimental mechanics, it appears possible to identify numerous mechanical parameters using a limited number of tests provided that the latter are finely optimized. In this context, we design a full numerical methodology for the shape optimization of the specimen with respect to identification ability. It is based on an adequate modeling of the optimization problem and on an advanced numerical resolution procedure using splines and the Free-Form Deformation concept. It results in a non-invasive CAD-based shape optimization procedure that allows to decrease the uncertainty on the identified constitutive parameters by a factor of 30.

Mots clés: Data Assimilation; Parameter identification; Digital Image Correlation; Shape optimization; Sensitivity analysis; CAD-based optimization

Domaines: Mécanique des solides [physics.class-ph]; Optimisation et contrôle [math.OC]

Morgane Chapelier, Robin Bouclier, Jean-Charles Passieux. Improving material parameter identification using spline FFD-based optimization of specimen shape. Photomechanics IDICS Conference, Nov 2021, Nantes, France. ⟨hal-03424493⟩