Hybrid deep learning and isogeometric analysis for bearing capacity assessment of sand over clay
Article
Article Title | Hybrid deep learning and isogeometric analysis for bearing capacity assessment of sand over clay |
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ERA Journal ID | 201130 |
Article Category | Article |
Authors | Nguyen-Minh, Toan, Bui-Ngoc, Tram, Shiau, Jim, Nguyen, Tan and Nguyen-Thoi, Trung |
Journal Title | Journal of Rock Mechanics and Geotechnical Engineering |
Year | 2024 |
Publisher | Kexue Chubanshe,Science Press |
Elsevier | |
Place of Publication | China |
ISSN | 1674-7755 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.jrmge.2024.10.012 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1674775524005237 |
Abstract | In this paper, Isogeometric analysis (IGA) is effectively integrated with machine learning (ML) to investigate the bearing capacity of strip footings in layered soil profiles, with a focus on a sand-over-clay configuration. The study begins with the generation of a comprehensive dataset of 10,000 samples from IGA upper bound (UB) limit analyses, facilitating an in-depth examination of various material and geometric conditions. A hybrid deep neural network, specifically the Whale Optimization Algorithm-Deep Neural Network (WOA-DNN), is then employed to utilize these 10,000 outputs for precise bearing capacity predictions. Notably, the WOA-DNN model outperforms conventional ML techniques, offering a robust and accurate prediction tool. This innovative approach explores a broad range of design parameters, including sand layer depth, load-to-soil unit weight ratio, internal friction angle, cohesion, and footing roughness. A detailed analysis of the dataset reveals the significant influence of these parameters on bearing capacity, providing valuable insights for practical foundation design. This research demonstrates the usefulness of data-driven techniques in optimizing the design of shallow foundations within layered soil profiles, marking a significant stride in geotechnical engineering advancements. |
Keywords | UB limit analysis; Isogeometric analysis (IGA); hybrid deep neural network; Whale optimization algorithm |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 400502. Civil geotechnical engineering |
Byline Affiliations | Ton Duc Thang University, Vietnam |
Van Lang University, Viet Nam | |
School of Engineering |
https://research.usq.edu.au/item/zq883/hybrid-deep-learning-and-isogeometric-analysis-for-bearing-capacity-assessment-of-sand-over-clay
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