Stability of rectangular tunnels in cohesive-frictional soil under surcharge loading using isogeometric analysis and Bayesian neural networks

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software Pub Date : 2024-12-30 DOI:10.1016/j.advengsoft.2024.103861

Minh-Toan Nguyen , Tram-Ngoc Bui , Jim Shiau , Tan Nguyen , Thoi-Trung Nguyen

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Abstract

This study evaluates the stability of rectangular tunnels in cohesive-frictional soils under surcharge loading using a combination of IsoGeometric Analysis and artificial neural networks. A dataset of 12,946 samples was generated automatically to analyze a wide range of soil profiles and tunnel geometries. Stability solutions were derived using IsoGeometric Analysis coupled with second-order cone programming, enabling precise and efficient assessments of ultimate surcharge loading. A key contribution of this study is the development of a closed-form solution through a Bayesian regularized neural network, which significantly improves accuracy compared to existing methods. Advanced data visualization techniques, including two- and three-dimensional partial dependency plots, were used to reveal complex relationships among design parameters. Sensitivity analyses provided valuable insights for optimizing tunnel designs, enhancing decision-making processes in geotechnical engineering. This study aims to equip engineers with practical tools for designing rectangular tunnels in real-world applications.

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本研究采用等几何分析和人工神经网络相结合的方法，评估了粘性摩擦土中矩形隧道在附加荷载作用下的稳定性。研究自动生成了一个包含 12,946 个样本的数据集，用于分析各种土壤剖面和隧道几何形状。利用等几何分析法和二阶圆锥编程法得出了稳定性解决方案，从而能够对极限附加荷载进行精确有效的评估。本研究的一个主要贡献是通过贝叶斯正则化神经网络开发了闭式解决方案，与现有方法相比，该方法显著提高了准确性。先进的数据可视化技术，包括二维和三维部分依赖图，用于揭示设计参数之间的复杂关系。敏感性分析为优化隧道设计提供了有价值的见解，改进了岩土工程的决策过程。这项研究旨在为工程师在实际应用中设计矩形隧道提供实用工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in Engineering Software 工程技术-计算机：跨学科应用

CiteScore

7.70

自引率

4.20%

发文量

169

审稿时长

37 days

期刊介绍： The objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving. The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliability.