Undrained sinkhole stability of circular cavity: a comprehensive approach based on isogeometric analysis coupled with machine learning
Article
Article Title | Undrained sinkhole stability of circular cavity: a comprehensive approach based on isogeometric analysis coupled with machine learning |
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ERA Journal ID | 40357 |
Article Category | Article |
Authors | Nguyen-Minh, Toan, Bui-Ngoc, Tram, Shiau, Jim, Nguyen, Tan and Nguyen-Thoi, Trung |
Journal Title | Acta Geotechnica |
Journal Citation | 19 (8), pp. 5561-5583 |
Number of Pages | 23 |
Year | 2024 |
Publisher | Springer |
Place of Publication | Germany |
ISSN | 1861-1125 |
1861-1133 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s11440-024-02266-3 |
Web Address (URL) | https://link.springer.com/article/10.1007/s11440-024-02266-3 |
Abstract | An innovative approach that combines isogeometric analysis (IGA), limit analysis, machine learning, and the multivariate adaptive regression splines (MARS) model is presented in this paper to investigate sinkhole stability of circular cavity. The upper bound limit analysis method using IGA and second-order cone programming (SOCP) is employed to analyze circular cavity stability. Based on Bézier extraction, the non-uniform rational B-spline (NURBS) is used to generate a set of NURBS surfaces that define the boundary of the soil domain. The proposed approach is validated through comparative analysis with previous studies, demonstrating its effectiveness in accurately predicting soil stability. A large dataset consisting of 5000 randomly generated runs is used to train the machine learning algorithm that is integrated with the MARS model. The results show high accuracy, with a small mean squared error of 10–3, in predicting the undrained stability of circular cavities. The integration of IGA, limit analysis, machine learning, and the MARS model contributes significantly to advancing computational techniques for assessing soil stability. The proposed approach offers a comprehensive and precise tool for engineers and researchers, providing an accurate design formula for evaluating the undrained stability of circular cavities. |
Keywords | Circular cavity; Isogeometric analysis; Limit analysis; Machine learning; Multivariate adaptive regression splines (MARS); Sinkhole; Undrained stability |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 400502. Civil geotechnical engineering |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Engineering |
Ton Duc Thang University, Vietnam | |
Van Lang University, Viet Nam |
https://research.usq.edu.au/item/z57q8/undrained-sinkhole-stability-of-circular-cavity-a-comprehensive-approach-based-on-isogeometric-analysis-coupled-with-machine-learning
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