International Journal of Research in Civil Engineering and Technology

P-ISSN: 2707-8264, E-ISSN: 2707-8272
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2024, Vol. 5, Issue 2, Part A

Risk identification and management in mechanized tunneling projects


Author(s): Monika Dadhwal and RS Kesharwani

Abstract: Mechanized tunneling, powered by Tunnel Boring Machines (TBMs), has revolutionized underground construction, delivering efficiency and precision in even the most challenging geological conditions. Yet, beneath the surface lies a web of unpredictable risks—unstable ground, TBM malfunctions, financial pitfalls, and environmental disruptions—all threatening project success. This study dives deep into the art and science of risk management, employing cutting-edge methodologies like Hierarchical Holographic Modeling (HHM), Fuzzy Analytical Hierarchy Process (FAHP), and Fault Tree Analysis (FTA) to dissect, assess, and mitigate threats before they escalate. With a strategic blend of real-time monitoring, geotechnical reinforcements, and AI-driven predictive analytics, this research unveils game-changing solutions for tunneling professionals. The future of underground construction belongs to those who conquer risk, not fear it—and this study is the blueprint to mastering it.

DOI: 10.22271/27078264.2024.v5.i2a.77

Pages: 63-71 | Views: 101 | Downloads: 52

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International Journal of Research in Civil Engineering and Technology
How to cite this article:
Monika Dadhwal, RS Kesharwani. Risk identification and management in mechanized tunneling projects. Int J Res Civ Eng Technol 2024;5(2):63-71. DOI: 10.22271/27078264.2024.v5.i2a.77
International Journal of Research in Civil Engineering and Technology

International Journal of Research in Civil Engineering and Technology

International Journal of Research in Civil Engineering and Technology
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