ArticleScientific reports2025
Triaxial test investigation of the reinforcement effect of Acacia dealbata roots on mountain red soil.
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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Abstract
Vegetation roots play a pivotal role in enhancing the shear resistance and stability of degraded mountain red soils, yet the quantitative effects of root density and orientation remain poorly constrained. In this study, unconsolidated undrained triaxial tests were conducted on red soil reinforced with Acacia dealbata roots to examine the influence of root area ratio (RAR), spatial arrangement, and confining pressure on stress-strain behaviour and shear strength. Shear strength parameters were derived from Mohr-Coulomb envelopes, and the increments in cohesion (Δc) and internal friction angle (Δφ) were analytically related to the increment of the major principal stress (Δσ₁). The results indicate that the presence of root systems enhanced both peak strength and the reinforcement index. The configuration with high RAR and horizontal root distribution achieved up to 64.80% higher deviator stress than the unreinforced control, whereas sparse vertical roots could weaken the composite under low confinement. Reinforcement efficiency was governed by the combined effects of root density and orientation, with dense, horizontally distributed networks most effectively mobilising interfacial friction and tensile resistance. Strength envelopes indicated simultaneous increases in apparent cohesion and internal friction angle, where Δc contributed nearly linearly to Δσ₁, while Δφ induced a quadratic amplification; their synergistic effect was further enhanced at higher confining pressures. This study provides robust experimental evidence and a quantitative framework to inform eco-engineering and slope stabilisation practices in mountain red soils, highlighting the importance of root system density and architecture in maximising vegetation-based reinforcement.
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