A physics-guided smoothing method for material modeling with digital image correlation (DIC) measurements

TL;DR

This paper introduces a physics-guided smoothing method for DIC measurements that ensures physically consistent displacement and strain fields, enabling improved material modeling of biological tissues.

Contribution

It presents a novel optimization-based smoothing approach combined with a data-driven workflow for heterogeneous material modeling from DIC data.

Findings

Enhanced accuracy in modeling biological materials.

Physically consistent displacement and strain fields obtained.

Successful application to a porcine tricuspid valve leaflet.

Abstract

In this work, we present a novel approach to process the DIC measurements of multiple biaxial stretching protocols. In particular, we develop a optimization-based approach, which calculates the smoothed nodal displacements using a moving least-squares algorithm subject to positive strain constraints. As such, physically consistent displacement and strain fields are obtained. Then, we further deploy a data-driven workflow to heterogeneous material modeling from these physically consistent DIC measurements, by estimating a nonlocal constitutive law together with the material microstructure. To demonstrate the applicability of our approach, we apply it in learning a material model and fiber orientation field from DIC measurements of a porcine tricuspid valve anterior leaflet. Our results demonstrate that the proposed DIC data processing approach can significantly improve the accuracy of modeling biological materials.