An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture
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Abstract (arXiv)
Meshfree discretizations of state-based peridynamic models are attractive due to their ability to naturally describe fracture of general materials. However, two factors conspire to prevent meshfree discretizations of state-based peridynamics from converging to corresponding local solutions as resolution is increased: quadrature error prevents an accurate prediction of bulk mechanics, and the lack of an explicit boundary representation presents challenges when applying traction loads. In this paper, we develop a reformulation of the linear peridynamic solid (LPS) model to address these shortcomings, using improved meshfree quadrature, a reformulation of the nonlocal dilitation, and a consistent handling of the nonlocal traction condition to construct a model with rigorous accuracy guarantees. In particular, these improvements are designed to enforce discrete consistency in the presence of evolving fractures, whose it a priori unknown location render consistent treatment difficult. In the absence of fracture, when a corresponding classical continuum mechanics model exists, our improvements provide asymptotically compatible convergence to corresponding local solutions, eliminating surface effects and issues with traction loading which have historically plagued peridynamic discretizations. When fracture occurs, our formulation automatically provides a sharp representation of the fracture surface by breaking bonds, avoiding the loss of mass. We provide rigorous error analysis and demonstrate convergence for a number of benchmarks, including manufactured solutions, free-surface, nonhomogeneous traction loading, and composite material problems. Finally, we validate simulations of brittle fracture against a recent experiment of dynamic crack branching in soda-lime glass, providing evidence that the scheme yields accurate predictions for practical engineering problems.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jan 2021.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 1.
4 papers.
- 2021A physics-informed variational DeepONet for predicting the crack path in brittle materialscited by 98
- 2021A data-driven peridynamic continuum model for upscaling molecular dynamicscited by 17
- 2024Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurementscited by 4
- 2023Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fracturescited by 3
- 2024Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurements27 Mar 2024
- 2023Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures11 Jan 2023
- 2021A physics-informed variational DeepONet for predicting the crack path in brittle materials16 Aug 2021
- 2021A data-driven peridynamic continuum model for upscaling molecular dynamics4 Aug 2021