Investigation of dynamic fracture of elastomers can still be considered to be a relatively open area. When a sheet of elastomer is stretched in a tensile machine and a crack is introduced, the crack propagates at a speed that depends on the initial stretch level. There are instances where this speed is noted to exceed the shear wave speed based on the elastic modulus under high imposed stretches. Such cracks are called transonic cracks. It was usually hypothesized that either the hyperelastic or viscoelastic stiffening of the bulk material raises the wave speeds resulting in crack speeds entering the transonic regime. This article revisits the experiments performed on Polyurethane elastomers in Corre et al. (Int J Fract 224(1):83-100, 2020) to study the implications of both these hypotheses. Crack propagation has not been explicitly modeled, but the crack speeds are implicitly imposed on the geometry using the boundary conditions extracted from the experimental data. It has been determined that the viscoelasticity in the bulk is needed to describe and understand the transonic cracks in polyurethane elastomer. The inclu-
Data Driven Computational Mechanics (DDCM) solves the boundary value problem by directly relying on the strain-stress data, bypassing the need for a constitutive model. In presence of materials exhibiting a softening response, Finite Element analyses performed with a constitutive model typically use a length scale, which can be introduced into the problem in multiple ways. A few commonly used ways include the addition of the gradient of damage variable in the energy density functional, using the gradient of strain while evaluating the internal variable, and so on. However, in the context of DDCM, these techniques may not be effective as the internal variables are not explicitly defined. Hence, the current article introduces a regularization technique, where the gradient of strain is constrained to lie within some interval. This prevents strain localization within an element by introducing a length scale into the problem. This article demonstrates the effectiveness of such a regularization technique in the case of 1D problems using a constitutive model while comparing its performance with strain gradient (SG) models.
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