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A GPU-accelerated three-dimensional element-based peridynamic contact modeling framework
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DOI：10.1016/j.cma.2026.119268.png)
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Abstract
En 中文
Accurate and stable contact modeling in complex three-dimensional (3D) peridynamic (PD) simulations across diverse contact scenarios remains challenging. This study proposes a GPU-accelerated 3D element-based PD contact modeling framework (3D-EBCM). The framework reconstructs finite local micro contact surfaces in the current configuration and determines normal and tangential contact stiffnesses from the local incremental PD responses of contacting particles. A critical time-step estimate accounting for contact stiffness is then established. The 3D-EBCM contact routine is implemented on GPUs using bond- and particle-mapping strategies combined with background-grid-assisted candidate search. The results of the two-cylinder benchmarks agree well with the Hertz solution over the examined material-stiffness ratios and particle resolutions. For the examined stiffness ratios, peak contact-pressure errors are approximately 1%, while penetration ratios remain near 1% across the benchmark cases. The GPU-accelerated contact routine achieves overall speedups of 99.1–263.0 relative to the corresponding serial CPU implementation. Impact-contact, frictional-contact, and rolling-contact examples further assess the method. The impact-contact results obtained using time steps below the estimated critical value reproduce the experimentally observed fracture pattern and support the contact-related critical time-step estimate for selecting a stable fixed time step. The frictional-contact results agree with finite-element results, whereas the rolling-contact results agree with the corresponding Hertz and Carter solutions. The method also captures damage-induced contact-force redistribution and the effects of creepage, surface cracks, and surface irregularity, and resolves two simultaneous, spatially separated rolling-contact regions.
Keywords:
Peridynamics
Contact modeling
Damage evolution
Three-dimensional simulation
GPU acceleration
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7.3
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5.6W
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