A machine-learning framework for peridynamic material models with physical constraints
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Publication:2246256
DOI10.1016/j.cma.2021.114062OpenAlexW3119471516MaRDI QIDQ2246256
Xiao Xu, John T. Foster, Marta D'Elia
Publication date: 16 November 2021
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2101.01095
Finite element methods applied to problems in solid mechanics (74S05) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) Peridynamics (74A70)
Related Items (9)
Anisotropic peridynamics for homogenized microstructured materials ⋮ An optimization-based approach to parameter learning for fractional type nonlocal models ⋮ Efficient optimization-based quadrature for variational discretization of nonlocal problems ⋮ A discussion on nonlocality: from fractional derivative model to peridynamic model ⋮ Machine learning of nonlocal micro-structural defect evolutions in crystalline materials ⋮ A data‐driven bond‐based peridynamic model derived from group method of data handling neural network with genetic algorithm ⋮ An Asymptotically Compatible Coupling Formulation for Nonlocal Interface Problems with Jumps ⋮ On the prescription of boundary conditions for nonlocal Poisson's and peridynamics models ⋮ New Insights on Convergence Properties of Peridynamic Models for Transient Diffusion and Elastodynamics
Cites Work
- Identification of the diffusion parameter in nonlocal steady diffusion problems
- Deformation of a peridynamic bar
- The effect of long-range forces on the dynamics of a bar
- Convergence of peridynamics to classical elasticity theory
- Reformulation of elasticity theory for discontinuities and long-range forces
- A general multiscale framework for the emergent effective elastodynamics of metamaterials
- Peridynamic states and constitutive modeling
- Analysis and Approximation of Nonlocal Diffusion Problems with Volume Constraints
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