Removal mechanism and damage evolution of SiCp/Al composites based on FEM-MD model considering 3D random polyhedral particles in orthogonal cutting
This study investigates the cutting mechanism and particle damage evolution of SiCp/Al composites using a coupled FEM-MD modeling approach. A Python-based algorithm was developed for generating representative volume element (RVE) through stochastic convex polyhedron modeling, enabling geometrically...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
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| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785425007628 |
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| Summary: | This study investigates the cutting mechanism and particle damage evolution of SiCp/Al composites using a coupled FEM-MD modeling approach. A Python-based algorithm was developed for generating representative volume element (RVE) through stochastic convex polyhedron modeling, enabling geometrically faithful reconstruction of particle morphologies. At the micro-scale, molecular dynamics simulations calibrated the cohesive zone model parameters for Al–SiC interface, while meso-scale finite element modeling incorporated these MD-derived interfacial properties to establish particle-matrix interaction dynamics. Orthogonal cutting simulations systematically revealed three speed-dependent material removal regimes: 1) Low-speed (<200 mm/s) particle extraction inducing matrix tearing through interfacial debonding; 2) Medium-speed (200–400 mm/s) extrusion-dominated fragmentation generating angular debris; 3) High-speed (>400 mm/s) impact-induced comminution producing refined fragments that minimize surface damage. The polyhedral particle model demonstrated superior predictive accuracy over spherical approximations, particularly in capturing edge-driven stress concentrations and anisotropic debonding patterns. Experimental validation confirmed the multi-scale model's predictive accuracy for machining-induced surface damage. This study extends multi-scale modeling methodologies for composite machining by uniquely integrating Python-based stochastic geometry reconstruction with MD-calibrated interfacial mechanics, providing a systematic framework for studying the damage mechanism of SiCp/Al composites machining. |
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| ISSN: | 2238-7854 |