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对不同水分含量的凝聚性土壤的离散元素参数的校准
Shixi Wei1,2, Bing Li1,3, Jinxia Yang4
1School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China.
PloS one
|February 9, 2026
概括
本研究校准了使用赫茨-明德林与约翰逊-肯达尔-罗伯茨 (JKR) 模型对凝聚性土壤的离散元素方法 (DEM) 模拟参数. 粒子集群优化 (PSO) 提高了加载器削过程的模拟精度.
科学领域:
- 地质技术工程 地质技术工程
- 计算力学 计算力学 计算力学
背景情况:
- 准确的离散元素方法 (DEM) 模拟凝聚性土壤行为对于优化像装载机这样的重型机械操作至关重要.
- 现有的模型通常需要精确的校准,以适应不同的土壤条件,特别是水分含量.
研究的目的:
- 为了校准不同的水分含量下的凝聚性土壤的DEM模拟参数,使用赫茨-明德林与约翰逊-肯德尔-罗伯茨 (JKR) 凝聚性接触模型.
- 为了提高 DEM 模拟的准确性,用于加载器擦除过程.
主要方法:
- 准备具有不同水分含量的凝聚性土壤样本.
- 确定颗粒大小分布,土壤-钢的摩擦系数和静止角度.
- 在EDEM (专家离散元件建模) 中实施JKR V2粘附模型.
- 普莱克特-伯曼测试用于显著参数选.
- 盒-贝恩肯设计和响应表面分析,以优化参数.
- 粒子群集优化 (PSO) 的应用,以优化静止角度.
主要成果:
- 凝聚性土壤的休息角从30.83°增加到37.13°,随着水分含量的增加.
- 确定了重要的参数包括JKR表面能量,土壤土壤恢复系数和静态摩擦系数.
- PSO算法将模拟误差降低到2.2%以内,而响应表面方法的最大误差为3.38%.
结论:
- 开发了一种高精度参数化方法,用于凝聚性土壤的DEM建模.
- 优化的参数和方法为涉及装载机与土壤相互作用的DEM模拟提供了有价值的参考.
- 该研究证明了PSO在改善凝聚性土壤的DEM模拟精度方面的有效性.
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