Asymmetric Adaptive Particle Refinement in SPH and Its Application in Soil Cutting Problems
Asymmetric Adaptive Particle Refinement in SPH and Its Application in Soil Cutting Problems
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DOI：
10.1142/s0219876218500524
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发表时间：
2017-12
影响因子：
1.7
通讯作者：
Hao Wu;Jian Wang;Jianhua Wang;C. Liao
中科院分区：
文献类型：
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作者：
Hao Wu;Jian Wang;Jianhua Wang;C. Liao
针对土壤切割问题，提出了一种基于光滑粒子流体动力学(SPH)的非对称自适应粒子细化算法。位于结构切割刀片上的每个候选粒子被分成两个子粒子，以最小化接触力的振荡。从而减少局部不稳定性。为了使密度修正误差最小，给出了一种确定“子”粒子最佳平滑长度的数值方法。为了验证算法的准确性，将自适应精化过程分为两个模型：一个用于平面应变条件下的土方切割试验，另一个用于轴对称条件下的试件钻探试验。将观测到的土壤流态和接触力与文献中提供的实验室实验数据进行了比较。结果表明，所提出的非对称自适应加密算法可以显著避免严重的局部不稳定，有助于高精度的仿真。
In this study, a novel asymmetric adaptive particle refinement algorithm in smoothed particle hydrodynamics (SPH) is developed for soil cutting problems. Each candidate particle that located at the cutting blade of the structure is split into two “children” particles to minimize the oscillation of the contact force. And thus reduce the local instability. To minimize the density refinement error, a numerical method to determine the optimal smoothing lengths for “children” particles is given. To verify the accuracy of proposed algorithm, the adaptive refinement procedure are implemented into two models: one for soil cutting test on plane strain condition and the other for sample drilling test on axisymmetric condition. The observed flow pattern of the soil and contact forces are compared with laboratory experimental data available in the literature. Results indicate that the proposed asymmetric adaptive refinement algorithm could significantly avoid severe local instability and contributes to high-accuracy simulation.