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Predicting Maximum Settlement Induced by EPB Shield Tunneling Through Image Processing and an Intelligent … – Springer

Abstract

In today’s urban development, Earth Pressure Balance (EPB) Tunnel Boring Machines (TBMs) play a vital role. It’s crucial to design a comprehensive monitoring system to control surface settlement and prevent damage to surface structures. This study focuses on creating prediction models for estimating ground surface settlement. Two soft computing techniques, namely ANN-CFB and ANN-BP, were used for this purpose. The models were validated using operational data from the Qom metro Line A, specifically the section between A14 and A10 stations. Additional input parameters were incorporated using an image processing approach to include soil properties for each segment. As a result, the most accurate ANN technique was employed to predict ground surface settlements for the mentioned project. The correlation coefficients for training, testing, validation, and the overall result were found to be 0.99439, 0.97873, 0.96381, and 0.98824, respectively. Through sensitivity analysis, the study explored the connections between different parameters and ground surface settlement. The outcomes reveal strong agreement between predicted values and real data. Notably, the parameter ‘cutter head torque’ exhibited the highest impact on surface settlement (8.48%), while ‘Pressiometric Modulus (Ep)’ had the least impact (4.24%).

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Acknowledgments

We would like to express our sincere gratitude to all the individuals that have contributed to the publication of this research paper. We would also like to thank Behro Comprehensive Consulting Engineers for their support throughout the research process. In particular, we would like to thank S. Gravand for their valuable insights and suggestions.

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Authors and Affiliations

  1. Dept. of Mining Engineering, Amirkabir University of Technology, Tehran, Iran

    Mehdi Yazdanparast

  2. Dept. of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Hossein Ayyab Koushkgozar

  3. School of Geology, College of Science, University of Tehran, Tehran, Iran

    Jafar Hassanpour

  4. Dept. of Engineering Geology, Isfahan University, Isfahan, Iran

    Abolfazl Kahaki

  5. Dept. of Engineering Geology, Islamic Azad University Science and Research Branch, Tehran, Iran

    Mohsen Khodagholi

Corresponding author

Correspondence to Mehdi Yazdanparast.

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Yazdanparast, M., Koushkgozar, H.A., Hassanpour, J. et al. Predicting Maximum Settlement Induced by EPB Shield Tunneling Through Image Processing and an Intelligent Approach. KSCE J Civ Eng (2024). https://doi.org/10.1007/s12205-024-2086-0

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  • DOI: https://doi.org/10.1007/s12205-024-2086-0

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