ArticleScientific reports2024
Estimation of the wetting induced settlement of loess soils from the wetting soil-water characteristic curve.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Integrating experimental data and machine learning to predict collapse potential of loessic and lacustrine-alluvial soils using suction and SWCC parameters.Scientific reports · 2026Article
- Correlation analysis between the collapsibility of loess and physicomechanical indices in Longdong region and prediction of the collapsibility coefficient based on machine learning.Scientific reports · 2026Article
- Using deep learning to capture gravel soil microstructure and hydraulic characteristics.Scientific reports · 2025Article
- An innovative modelling technique for bimodal soil water characteristic curve under wetting process.Scientific reports · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
Collapsible loess soils, known for their significant volume reduction upon the wetting, pose critical challenges in the geotechnical engineering. The estimation of the wetting-induced settlement is crucial for the foundation design and the determination of the negative skin friction on the pile. In this paper, a new method is proposed to estimate the wetting induced collapse from the wetting soil-water characteristic curve (SWCC) and the index properties of the loess soils. In the proposed model, both the water-entry value (WEV) and constant water content suction (ψ
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