Experimental and numerical study on helical piles in aeolian sand: bearing behavior and design methods

In aeolian sand, the mechanical behavior of helical anchors involves complex performance evolution mechanisms that are not yet fully understood. This study employs a multi-scale integrated approach combining field tests, numerical simulations, and machine learning to systematically investigate the evolution laws of the bearing behavior of helical anchors. The results indicate: (1) The critical embedment depth threshold for helical anchors in aeolian sand is H = 5 D ; beyond this threshold, the load direction effect can be neglected. (2) Multi-plate helical anchors exhibit significant geometrically nonlinear superposition behavior. Dense spacing ( S / D < 4) produces notable stress superposition effects ( η = 1.15–1.32), whereas wide spacing ( S / D ≥ 4) results in independent bearing units ( η = 0.97–1.03). (3) The XGBoost machine learning model identifies the internal friction angle, anchor plate diameter, and embedment depth ratio as the most influential features affecting bearing capacity. Based on these control parameters, predictive equations for the bearing capacity coefficient N q and soil lateral friction coefficient K u were developed, with predictions showing excellent agreement with experimental data. This provides engineers with a reliable analytical framework for performance-based design. The study not only deepens the understanding of the behavioral mechanisms of helical piles in aeolian sand but also offers practical solutions for geotechnical engineering practice.

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Publication Details

Journal
SOILS AND FOUNDATIONS
Published
2025-08-22
DOI
https://doi.org/10.1016/j.sandf.2025.101680
Primary Topic
Aeolian processes and effects
Type
article
Field-Weighted Citation Impact
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article

Experimental and numerical study on helical piles in aeolian sand: bearing behavior and design methods

Yongping Li, Yijin Wu, Jing Bai, Songzhao Qu et al.
SOILS AND FOUNDATIONS
Aeolian processes and effects
article

Experimental and numerical study on helical piles in aeolian sand: bearing behavior and design methods

Yongping Li, Yijin Wu, Jing Bai, Songzhao Qu, Ruiyuan Han, Suoting Hu, Dapeng Wang, Zhe Zhang, Yi Zhang, Xiang Yuan, Yonghua Guo, Lulu Di, Dongming Yang
article en

Abstract

In aeolian sand, the mechanical behavior of helical anchors involves complex performance evolution mechanisms that are not yet fully understood. This study employs a multi-scale integrated approach combining field tests, numerical simulations, and machine learning to systematically investigate the evolution laws of the bearing behavior of helical anchors. The results indicate: (1) The critical embedment depth threshold for helical anchors in aeolian sand is H = 5 D ; beyond this threshold, the load direction effect can be neglected. (2) Multi-plate helical anchors exhibit significant geometrically nonlinear superposition behavior. Dense spacing ( S / D < 4) produces notable stress superposition effects ( η = 1.15–1.32), whereas wide spacing ( S / D ≥ 4) results in independent bearing units ( η = 0.97–1.03). (3) The XGBoost machine learning model identifies the internal friction angle, anchor plate diameter, and embedment depth ratio as the most influential features affecting bearing capacity. Based on these control parameters, predictive equations for the bearing capacity coefficient N q and soil lateral friction coefficient K u were developed, with predictions showing excellent agreement with experimental data. This provides engineers with a reliable analytical framework for performance-based design. The study not only deepens the understanding of the behavioral mechanisms of helical piles in aeolian sand but also offers practical solutions for geotechnical engineering practice.

SOILS AND FOUNDATIONSVol. 65(5)
Inner Mongolia Electric Power (China) (CN), Henan Energy & Chemical Industry Group (China) (CN), Inner Mongolia Electric Power Survey & Design Institute (China) (CN), Henan University of Urban Construction (CN)
Openalex Percentile: Top 76%
Aeolian processes and effects
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