Capturing the random mechanical behavior of granular materials: A comprehensive stochastic discrete element method study

Author:

Liu De-Yun1,Lyu Meng-Ze1

Affiliation:

1. Department of Civil & Environmental Engineering, Hong Kong University of Science & Technology Clear Water Bay, Hong Kong 999077, China, State Key Lab. of Disaster Reduction in Civil Engineering, Tongji University College of Civil Engineering, Tongji University 1239 Siping Rd, Shanghai 200092, China

Abstract

This research pioneers a stochastic discrete element method (DEM) by integrating the probability density evolution method (PDEM), offering a novel approach to connect particle-scale property uncertainties, specifically inter-particle friction coefficient (μ) and particle shear modulus (G_p), with macroscale soil behavior. Through 1,100 DEM simulations, this study reveals that, for uniform particle size distribution, the uncertainty in μ substantially affects large strain soil behaviour, with its effect being associated with packing density and soil state. The uncertainty effect of μ remains pronounced at the critical state, while the packing density effect diminishes. Stress distribution appears insensitive to uncertainty of μ, rather suggesting a predominant influence of particle size distributions. In contrast, uncertainty effect of μ becomes negligible on small strain behaviour, demonstrating limited effect on small strain stiffness. Uncertainty in G_p presents limited effects on large strain behaviour, including stress ratios and dilatancy. At small strains, G_p shows a significant impact on stiffness, diverging from minimal influence identified for μ. This study presents a framework that integrates experimental techniques to study particle-scale uncertainty propagation, enhancing predictions of macro-scale soil behavior. This approach could be beneficial for precise multi-scale simulations, incorporating particle-level uncertainties in engineering-scale models, thus improving geotechnical practice predictability.

Publisher

Emerald

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3