Harnessing fuzzy logic for building structural health during large diameter tunnelling in urban area

Pierre Guy Atangana Njock, Shui Long Shen, Annan Zhou, Zhen Yu Yin, Yi Zeng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Building structural health is constantly jeopardized by tunnel construction, which thus is in a sustained demand for holistic risk assessment and management approaches. In this study, we propose an enhanced consulting fuzzy model with limited information losses to evaluate the static and dynamic risks of building health deterioration during tunnelling. The model integrates three main strategies including, (i) reducing influence of experts’ bias in the ranking processes; (ii) expanding the space of uncertainties in fuzzy environment, and (iii) controlling risk aversion settings through the prospect theory. The construction of the largest diameter (15.3 m) tunnel in China is adopted as a case study to demonstrate the application of the proposed model in assessing the risk statuses of surrounding buildings. Through the proposed model, the risk index can indicate beneficial or detrimental effects of tunnelling and the degree of risk factors delineates priority actions for risk management. The results enable the development of operational risk abatement procedures to enhance the state of practice of large diameter tunnel construction in complex geological conditions.

Original languageEnglish
Article number108519
JournalEngineering Applications of Artificial Intelligence
Volume133
DOIs
Publication statusPublished - Jul 2024

Keywords

  • Building structural health
  • Fuzzy logic
  • Large diameter
  • Risk assessment
  • Risk management
  • Tunnelling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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