Evidence map›Paper›PMID 40108269›Full record

ArticleScientific reports2025

Modeling of sand-cultivated substrate for Gobi facility agriculture and validation of trenching test.

Yalong Song, Jiahui Xu, Shuo Zhang, Jianfei Xing, Long Wang, Xufeng Wang, Can Hu, Wentao Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yalong SongCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China.
Jiahui XuCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China.
Shuo ZhangCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China.
Jianfei XingCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China. 120200012@taru.edu.cn.
Long WangCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China. 120140002@taru.edu.cn.
Xufeng WangCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China.
Can HuCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China.
Wentao LiCollege of Mechanical and Electrical Engineering, Tarim University, Alar, 843300, China.

Funding

Core Agricultural Research Project of the Zhong nong United Fund ZNLH202401Key Technology Research Project of the Xinjiang Production and Construction Corps 2023AB005-01Project of the Aksu Comprehensive Experimental Station of the Xinjiang Vegetable Industry Technology System XJARS-07-25the "NYHXGG, 2023AA304" Project 2023AA304the "NYHXGG, 2023AA304" Project NYHXGGthe University-level Research Project TDGRI2024076Xinjiang Science and Technology Talent Program 2024DB031
6 · The paper itself

Abstract

Accurately simulating the interaction between trenching devices and river sand substrates is crucial for optimizing agricultural practices in Gobi Desert facility agriculture. This study calibrates Discrete Element Method (DEM) parameters for river sand substrate in the Gobi Desert of Northwest China, utilizing the Hertz-Mindlin contact model coupled with the Johnson-Kendall-Roberts (JKR) contact model in EDEM software. Key parameters, including stacking angle, particle size distribution, and morphology of the river sand, were measured using various methods and tools, such as an image acquisition system, vibration grading device, and stacking angle test apparatus. A model was developed to simulate the interaction between the river sand substrate and trenching device. The river sand matrix exhibited a stacking angle of 31.91°, with 9.85% of particles smaller than 0.25 mm, 52.60% ranging from 0.25 to 0.6 mm, and 37.55% exceeding 0.6 mm. A Plackett-Burman experimental design was employed to identify the sensitive parameters, including the static friction coefficient between river sand particles, the rolling friction coefficient of river sand and steel, and the restitution coefficient between river sands. The steepest ascent approach established the parameter ranges, and the Box-Behnken design (BBD) was used for optimization, resulting in the following parameter values: 0.533 for the static friction coefficient between river sand particles, 0.209 for the rolling friction coefficient of river sand and steel, and 0.213 for the coefficient of restitution between the river sand particles. A DEM model was developed based on these optimized parameters. Validation through experiments demonstrated that the simulation closely matched field test results, with errors in trench depth, surface width, and bottom width, all within a 9% margin of 8.8%, 4.8%, and 7.9%, respectively. These findings confirmed the accuracy and applicability of the DEM model for stimulating the interaction between river sand substrate and trenching equipment in Gobi Desert facility agriculture. This study provides a theoretical framework for optimizing trenching devices and rapidly constructing DEM models for river sand in sand farming systems.

Indexed as

Discrete element methodModelingParameter calibrationSand-cultivated substrateTrenching test

Identifiers

PMID40108269
PMCPMC11923169

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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.