Biaxial characterization of soft elastomers: experiments and data-adaptive configurational forces for fracture
Miguel Angel Moreno-Mateos, Simon Wiesheier, Ali Esmaeili, Mokarram Hossain, Paul Steinmann

TL;DR
This paper combines experiments and computational modeling to understand fracture in soft elastomers under biaxial loading, introducing a data-adaptive hyperelastic model and a configurational force method for fracture analysis.
Contribution
It presents a novel integrated experimental-computational framework with a data-adaptive hyperelastic model and a post-processing configurational force method for fracture in soft elastomers.
Findings
Revealed diverse fracture behaviors in elastomers under biaxial loading.
Developed a versatile hyperelastic energy function capturing experimental responses.
Established a fracture criterion based on configurational force at crack tips.
Abstract
Understanding the fracture mechanics of soft solids remains a fundamental challenge due to their complex, nonlinear responses under large deformations. While multiaxial loading is key to probing their mechanical behavior, the role of such loading in fracture processes is still poorly understood. Here, we present a combined experimental-computational framework to investigate fracture in soft elastomers under equi-biaxial loading. We report original equi-biaxial quasi-static experiments on five elastomeric materials, revealing a spectrum of material and fracture behavior, from brittle-like to highly deformable response with crack tip strains exceeding 150 %. Motivated by these observations, we develop a hybrid computational testbed that mirrors the experimental setup and enables virtual biaxial tests. Central to this framework are two components: a data-adaptive formulation of…
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