DEM study on the effect of fiber length and content on the macro-micro mechanical behavior of fiber-sand mixture

This paper investigates the mechanical behavior of fiber-sand mixtures (FSM) by comprehensively examining the effects of fiber volumetric content (FC) and fiber length (FL) from both macroscopic and microscopic perspectives using the discrete element method (DEM). A hybrid digital photogrammetry and deep learning approach integrating YOLOv5 and U-Net is developed to rapidly identify particle contours and construct realistic shape databases for fibers and sand grains. Based on these databases, numerical biaxial compression tests are conducted on FSM samples with different FC and FL. The results show that increasing FC and FL significantly enhances the peak and residual stress ratios, leading to increases in peak and residual friction angles of up to 8.5% and 6.2%, respectively. Higher FC values also promote volumetric shrinkage, while longer fibers delay volume contraction by providing additional bridging and rotational restraint. Microscopic analysis reveals that increasing FC reduces sand-sand coordination numbers and increases sand-fiber contacts, while longer fibers contribute to a higher sliding contact ratio and improve internal stability by restricting particle rearrangement. The findings elucidate the micro-mechanisms governing strength improvement and deformation behavior in FSM and provide guidance for optimizing fiber reinforcement strategies in geotechnical engineering applications.

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Publication Details

Journal
Scientific Reports
Published
2026-01-13
DOI
https://doi.org/10.1038/s41598-025-34063-7
Primary Topic
Geotechnical Engineering and Soil Stabilization
Type
article
Field-Weighted Citation Impact
0.00

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article

DEM study on the effect of fiber length and content on the macro-micro mechanical behavior of fiber-sand mixture

Pengpeng Zhao, Fengling Tan, Guocheng Sun, Guangjing Yin et al.
Scientific Reports
Geotechnical Engineering and Soil Stabilization
article

DEM study on the effect of fiber length and content on the macro-micro mechanical behavior of fiber-sand mixture

Pengpeng Zhao, Fengling Tan, Guocheng Sun, Guangjing Yin, Zongtang Zhang, Zhe Li
article en

Abstract

This paper investigates the mechanical behavior of fiber-sand mixtures (FSM) by comprehensively examining the effects of fiber volumetric content (FC) and fiber length (FL) from both macroscopic and microscopic perspectives using the discrete element method (DEM). A hybrid digital photogrammetry and deep learning approach integrating YOLOv5 and U-Net is developed to rapidly identify particle contours and construct realistic shape databases for fibers and sand grains. Based on these databases, numerical biaxial compression tests are conducted on FSM samples with different FC and FL. The results show that increasing FC and FL significantly enhances the peak and residual stress ratios, leading to increases in peak and residual friction angles of up to 8.5% and 6.2%, respectively. Higher FC values also promote volumetric shrinkage, while longer fibers delay volume contraction by providing additional bridging and rotational restraint. Microscopic analysis reveals that increasing FC reduces sand-sand coordination numbers and increases sand-fiber contacts, while longer fibers contribute to a higher sliding contact ratio and improve internal stability by restricting particle rearrangement. The findings elucidate the micro-mechanisms governing strength improvement and deformation behavior in FSM and provide guidance for optimizing fiber reinforcement strategies in geotechnical engineering applications.

Scientific ReportsVol. 16(1)
Hunan University of Science and Technology (CN), China Nonferrous Metals Changsha Investigation Design Institute (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Geotechnical Engineering and Soil Stabilization
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DEM study on the effect of fiber length and content on the macro-micro mechanical behavior of fiber-sand mixture — Pengpeng Zhao, Fengling Tan, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS