Dr. Pascal Lava, MatchID  “The digital twin in material identification, FE model validation and fracture mechanics” 

Digital Image Correlation (DIC) is gradually becoming a standard tool in experimental mechanics, for both industry and academia. Despite the fact that the measurement system is often sold with the argument of being easy in use and setup, a poor understanding of issues arising in the whole measurement chain can result in poor or misinterpreted results.
A digital twin methodology will be presented that relies on the use of synthetic speckle image deformation to generate ground-truth strain images, enabling to properly evaluate the spatial resolution and inherent systematic and random errors of DIC.
This strategy will be invoked to elaborate on the concept of material testing 2.0 and geometry optimization, applied to composites, elastomers and sheet metal.
In a second part, the difficult question of how to validate FEA simulations via full-field DIC data is addressed. The underpinning novelty is the fact that it takes into account the filtering effects of DIC, which according to the authors, is a compulsory step to obtain robust validation.
The digital twin concept will be applied to uncertainty quantification of DIC on fracture properties, such as crack-tip position, crack growth, stress intensity factors and energy release rate using J-Integrals.

Dr. Pascal Lava brings a wealth of experience in the practical application/data analysis of DIC, the dentification of mechanical material properties via the virtual fields method and the validation of FE simulations.