Evidence map›Paper›PMID 41662244›Full record

ArticlePloS one2026

Calibration of discrete element parameters for cohesive soils at different moisture contents.

Shixi Wei, Bing Li, Jinxia Yang, Dengsheng Cai, Wubin Xu, Zhaoyang Liu

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shixi WeiSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China.ORCID https://orcid.org/0009-0005-6165-992X
Bing LiSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China.
Jinxia YangGuangxi Liugong Machinery Co., Ltd., Liuzhou, China.
Dengsheng CaiGuangxi Liugong Machinery Co., Ltd., Liuzhou, China.
Wubin XuGuangxi Colleges and Universities Engineering Research Center for High-End Engineering Machinery Equipment, Liuzhou, China.
Zhaoyang LiuSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To obtain discrete element method simulation parameters for cohesive soil during the scrapping process of loaders, this paper calibrates parameters of cohesive soil with different moisture contents based on the Hertz-Mindlin with Johnson-Kendall-Roberts (JKR) Cohesion contact model in Experts in Discrete Element Modeling (EDEM). First, five cohesive soil samples with different moisture contents were prepared. By combining vibration sieving, the inclined plane method, and angle of repose experiments, the measured data ranges of particle size distribution, soil-steel friction coefficient, and angle of repose were obtained. Secondly, the JKR V2 adhesion model was constructed in EDEM. Significant parameters were screened using the Plackett-Burman test. Finally, the response surface analysis range was determined by integrating climbing experiments, and a quadratic regression model was established through Box-Behnken design to optimize parameter combinations. Furthermore, a Particle Swarm Optimization (PSO) algorithm was introduced for single-objective optimization of the angle of repose. The experimental results show that with the increase of moisture content, the angle of repose increases from 30.83° to 37.13°, and the significant parameters are JKR surface energy, soil-soil restitution coefficient, and static friction coefficient. The simulation error of the PSO algorithm is reduced from the maximum 3.38% in the response surface method to within 2.2%. This study provides a high-precision parameterization method for DEM modeling of cohesive soil, offering references for establishing DEM simulations of loaders scraping cohesive soil.

Indexed as

SoilWaterAlgorithmsCalibrationModels, TheoreticalParticle SizeParticle Swarm OptimizationSoilWater

Identifiers

PMID41662244
PMCPMC12885266

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.