Process-zone condensation: a discretization-exact reduced cell model for FE2 analysis of composites with fibre-matrix debonding and matrix plasticity
Leonilson Toffoli Pedrini, Maycoln Conci, Rafael Marin Ferro
Abstract
Periodic composites with cohesive interfaces and matrix plasticity require nonlinear cell solutions in multiscale analysis. Process-zone condensation eliminates the linear elastic remainder of the cell by a Schur complement, retaining all interfacial and process-zone internal variables. Influence matrices recover macroscopic stress and consistent tangent. One back-substitution per increment checks that the matrix outside the retained zone remains elastic. While this holds, the reduction is exact relative to the full discretisation, also with a plastic matrix, and requires no training. In an E-glass/epoxy cell, eight of nine two-dimensional paths agree with the full cell to 1e-11 in stress and tangent; the check flags the ninth. Three paths on each of two three-dimensional meshes need zone expansion. Excluding setup and checks, two-dimensional path timings show an aggregate speed-up of 3.3; certified three-dimensional zones show none. In adaptive finite element squared (FE2) simulations of a perforated plate, the reduced solver reproduces the full-cell response within solver tolerances, 1.51 times faster for glass/polypropylene and slower for glass/epoxy. Independent Ansys models agree to below 1e-3 in cell stress and about 0.6% in plate reactions, although local damage and plasticity onsets differ. The advantage depends on zone size, active set and adaptation costs.
Create a lesson
Related papers
Enabling risk and reliability analysis in next-generation computational tools via multifidelity methods
Anirban Chaudhuri, Karen Willcox
Methodological Assessment of Instrumented Indentation for Spatially Resolved Mesoscale Stiffness and Creep in Short Fiber-Reinforced Injection-Molded PBT Components
Eduard Klatt, Natalie Rauter
Stabilizing Neural Emulation of Spatiotemporal Physical Dynamics through Denoising Koopman Latent Dynamics
Chenxu Wu, Sixing Chen, Junming Hou et al.
Optimized size, shape and orientation of rhombic transposition flaps and excisions by gradient-based methods
Niels Aage, Brandon Marshal Parks
Theory-guided relational learning for data product pricing: An interpretable meta-path-guided graph neural network approach
Ruize Gao, Feng Xiao, Jinpu Li et al.
LLM-Generated Investment Research Memos Need Validation
Xukang Gong, Chenri Luo, Binyan Yu et al.