Identifying and Ranking of Mechanized Tunneling Project's Risks by Using A Fuzzy Multi-Criteria Decision Making Technique

Document Type : Regular Article

Authors

1 Ph.D. Candidate, Department of Civil Engineering, University of Calabria, 87036 Rende, Italy

2 M.Sc., Department of Civil Engineering, University of Calabria, 87036 Rende, Italy

3 M.Sc., Department of Mechanical, Energy and Management Engineering, University of Calabria, Rende, Italy

4 Associate Professor, Department of Mining and Engineering, Faculty of Environment, Urmia University of Technology, Urmia, Iran

Abstract

A tunneling project is one of the most significant infrastructure projects. Its implementation requires access to adequate data and use of unique proceedings; hence it has a special position among civil engineering projects. Unexpected and uncertain conditions in tunneling projects lead to an increase of potential risks during project implementation. Identifying and evaluating risks in tunneling projects are considered one of the significant challenges among civil engineers, which can cause proper risk management during tunnel construction. Therefore, this study aims to evaluate and rank the risks of the second part of the Emamzadeh Hashem tunnel in the north of Iran which was considered as a case study. For this purpose, twelve potential risks were identified by using geological studies and experts. Then, they were evaluated and ranked using effective fuzzy multi-criteria decision-making (FMCDM) techniques, namely fuzzy analytical hierarchical process (FAHP). The three decision variables were considered, including repeat chance, occurrence possibility, and efficacy. The results obtained indicated that the occurrence possibility was the most effective among the decision variables in this case study. In addition, Instability of the wall and lack of contractor’s experiences had the highest and lowest ranks with 0.103 and 0.052, respectively.

Keywords

Main Subjects

References

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  • Receive Date: 20 September 2021
  • Revise Date: 03 December 2021
  • Accept Date: 01 January 2022

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