Hong-jie Fang, Shun Wang, Xuan Kang, Dian-qing Li, Wei Wu, Barbara Świtała
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SPH Implementation of a Dynamic Hypoplastic Model for Seismic Large Deformation Analysis in Slopes
Accurate modeling of soil behavior under seismic conditions is critical for understanding and mitigating earthquake-induced hazards. In this study, the Dyna–Simhypo model, an enhanced hypoplastic framework incorporating the intergranular strain tensor, is integrated with smoothed particle hydrodynamics (SPH) method for the first time to simulate co-seismic large deformation processes of slopes. The model's performance is validated through cyclic triaxial tests, seismic wave propagation analysis, and large-scale seismic slope simulations. Compared to the original Simhypo model, it eliminates ratcheting and reliably captures shear modulus reduction, damping buildup, and progressive soil degradation under cyclic loading. These advancements enable precise site response evaluations and accurate slope instability predictions, offering a robust tool for seismic hazard assessment.
期刊介绍:
The journal welcomes manuscripts that substantially contribute to the understanding of the complex mechanical behaviour of geomaterials (soils, rocks, concrete, ice, snow, and powders), through innovative experimental techniques, and/or through the development of novel numerical or hybrid experimental/numerical modelling concepts in geomechanics. Topics of interest include instabilities and localization, interface and surface phenomena, fracture and failure, multi-physics and other time-dependent phenomena, micromechanics and multi-scale methods, and inverse analysis and stochastic methods. Papers related to energy and environmental issues are particularly welcome. The illustration of the proposed methods and techniques to engineering problems is encouraged. However, manuscripts dealing with applications of existing methods, or proposing incremental improvements to existing methods – in particular marginal extensions of existing analytical solutions or numerical methods – will not be considered for review.