Predicting the uplift capacity of circular anchors in frictional-cohesive soils using Kolmogorov-Arnold networks
Article
Vu-Hoang, Tran, Nguyen, Tan, Shiau, Jim, Pham-Tran-Hung, Thinh and Nguyen-Thoi, Trung. 2025. "Predicting the uplift capacity of circular anchors in frictional-cohesive soils using Kolmogorov-Arnold networks." Scientific Reports. 15 (1). https://doi.org/10.1038/s41598-025-98945-6
| Article Title | Predicting the uplift capacity of circular anchors in frictional-cohesive soils using Kolmogorov-Arnold networks |
|---|---|
| ERA Journal ID | 201487 |
| Article Category | Article |
| Authors | Vu-Hoang, Tran, Nguyen, Tan, Shiau, Jim, Pham-Tran-Hung, Thinh and Nguyen-Thoi, Trung |
| Journal Title | Scientific Reports |
| Journal Citation | 15 (1) |
| Article Number | 14549 |
| Number of Pages | 26 |
| Year | 2025 |
| Publisher | Nature Publishing Group |
| Place of Publication | United Kingdom |
| ISSN | 2045-2322 |
| Digital Object Identifier (DOI) | https://doi.org/10.1038/s41598-025-98945-6 |
| Web Address (URL) | https://www.nature.com/articles/s41598-025-98945-6 |
| Abstract | This study investigates the uplift capacity of circular anchors embedded in frictional-cohesive soils under surcharge. The analysis focuses on three critical stability factors Fc, Fq, and Fγ using Terzaghi’s principle of superposition to evaluate ultimate bearing capacity. These factors are influenced by the soil’s internal friction angle, the geometric ratio of anchor depth to diameter, and the interface roughness between the anchor and soil. Three predictive models for these stability factors are developed using advanced computational methods, including finite element limit analysis (FELA) with adaptive meshing and Kolmogorov-Arnold Networks (KAN). This research is the first to apply KAN in anchor behavior studies, demonstrating its enhanced ability to model complex data relationships compared to artificial neural networks (ANN). Additionally, a closed-form solution for stability factors is derived through KAN, providing an efficient method for predicting bearing capacity. The optimized models exhibit high coefficient of determination (R²) values and low root mean square errors (RMSE) for training and testing datasets. Sensitivity analysis validates the robustness of the proposed models. These findings advance the understanding of circular anchors’ bearing capacity in frictional-cohesive soils, offering practical design insights for various soil conditions. |
| Keywords | Closed-form solution; Uplift capacity; Frictional-cohesive soils; Terzaghi stability factors; Kolmogorov-Arnold networks (KAN); Sensitivity analysis |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 400502. Civil geotechnical engineering |
| Byline Affiliations | Ton Duc Thang University, Vietnam |
| School of Engineering | |
| Van Lang University, Viet Nam |
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