CV


Mahdi Naseri

Mahdi Naseri

Assistant Professor

Faculty: Engineering

Department: Civil Engineering

Degree: Ph.D

CV
Mahdi Naseri

Assistant Professor Mahdi Naseri

Faculty: Engineering - Department: Civil Engineering Degree: Ph.D |

Risk Assessment of Water Structure Projects Using Fuzzy Multi-Attribute Decision-Making Methods: Fuzzy OWA and Fuzzy SAW (Case Study: S1 Wellhead Platform in the Salman Oil Field)

AuthorsMahdi Naseri,ali khazaee
Journalwater harvesting research
Page number334-348
Serial number7
Volume number2
Paper TypeFull Paper
Published At2024
Journal TypeTypographic
Journal CountryIran, Islamic Republic Of
Journal Indexisc

Abstract

Civil engineering projects, including the construction of oil platforms, are inherently associated with various types of risks from different perspectives. Risk management in large-scale water and marine structure projects, such as the construction of oil platforms, is essential due to the multiple uncertainties and extensive environmental and human factors involved. Identifying, assessing, and prioritizing risks are critical steps in managing these projects effectively. This study aims to identify and rank key risks in the construction of an oil platform using fuzzy multi-attribute decision-making models. In this research, risks in the areas of engineering, execution, passive defense, and the environment were identified through a literature review and expert consultation using brainstorming techniques. Subsequently, a risk management team identified 21 key risks and established 8 evaluation criteria through focused group discussions. To achieve the research objectives, two questionnaires were developed. The first questionnaire was used to form a pairwise comparison matrix and determine the weights of the criteria using the Fuzzy Buckley method, while the second questionnaire assessed the importance of the risks. The collected data were analyzed using the Fuzzy Simple Additive Weighting (SAW) and Ordered Weighted Averaging (OWA) methods. The results indicated that the primary risks were related to the execution phase, highlighting the need for special attention to these risks to improve project outcomes. Unlike many traditional methods, the fuzzy OWA method effectively incorporates the subjective characteristics, risk appetite, and risk aversion of decision-makers, proving to be efficient in risk evaluation.

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