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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-03-19
DOI
https://doi.org/10.1038/s41598-025-93909-2
Citations
2
Primary Topic
Soil Management and Crop Yield
Type
article
Field-Weighted Citation Impact
2.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Yalong Song, Can Hu, Long Wang, Shuo Zhang et al.
2 citations
Scientific Reports
Soil Management and Crop Yield
2.37
article

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

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

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.

Scientific ReportsVol. 15(1)
Xinjiang Production and Construction Corps (CN), Tarim University (CN)
Zero hunger
Openalex Percentile: Top 13%
Soil Management and Crop Yield
2.37
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.