An analysis of intuitionistic fuzzy sets in risk-based inspection: A case study of hydrogen crack damage in steel tanks under gas pressure

The present study examined and analyzed risks in oil and gas industries according to API RP 580 and 581 standards and the theory of Intuitionistic fuzzy sets (IFSs) for stakeholders’ decisions and implementation in the risk-based inspection program. In this study, time risk analysis is performed concerning the significance of time risk in a risk-based inspection (RBI) program, as well as risk calculations. This approach is critical for calculating inspection time intervals and lowering relevant expenditures. The studied case examples were three steel tanks under the pressure of sour gas and gas condensate exposed to hydrogen cracking (HIC) damage. After examining the mechanism of damage and obtaining information from the test results and Fitness for Service (FFS), risks were ranked and prioritized. The obtained risk information forms the basis of RBI. The results indicated the high financial risk of all three tanks. The risk of environmental damage was medium to Tanks 1 (V1000) and 2 (T2020), and high to Tank 3 (T2320). The highest time risk was assigned to T2320 and the lowest time risk was assigned to V1000. The findings indicate that is in critical condition of Tank 3 compared to the other tanks. Additionally, the data was evaluated using the RBI qualitative method to compare the proposed approach’s outcomes. An analysis of the outcomes from both methods indicates that the proposed method demonstrated superior accuracy and clarity. The findings can be used in the RBI program.

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Publication Details

Journal
Cleaner Engineering and Technology
Published
2024-12-01
DOI
https://doi.org/10.1016/j.clet.2024.100855
Citations
7
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
3.43
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article

An analysis of intuitionistic fuzzy sets in risk-based inspection: A case study of hydrogen crack damage in steel tanks under gas pressure

Sh. Zangeneh, Adel Fatemi, Jalal Sadeghi, Hadi Sarvari et al.
7 citations
Cleaner Engineering and Technology
Multi-Criteria Decision Making
3.43
article

An analysis of intuitionistic fuzzy sets in risk-based inspection: A case study of hydrogen crack damage in steel tanks under gas pressure

Sh. Zangeneh, Adel Fatemi, Jalal Sadeghi, Hadi Sarvari, David John Edwards
article en
7 citations

Abstract

The present study examined and analyzed risks in oil and gas industries according to API RP 580 and 581 standards and the theory of Intuitionistic fuzzy sets (IFSs) for stakeholders’ decisions and implementation in the risk-based inspection program. In this study, time risk analysis is performed concerning the significance of time risk in a risk-based inspection (RBI) program, as well as risk calculations. This approach is critical for calculating inspection time intervals and lowering relevant expenditures. The studied case examples were three steel tanks under the pressure of sour gas and gas condensate exposed to hydrogen cracking (HIC) damage. After examining the mechanism of damage and obtaining information from the test results and Fitness for Service (FFS), risks were ranked and prioritized. The obtained risk information forms the basis of RBI. The results indicated the high financial risk of all three tanks. The risk of environmental damage was medium to Tanks 1 (V1000) and 2 (T2020), and high to Tank 3 (T2320). The highest time risk was assigned to T2320 and the lowest time risk was assigned to V1000. The findings indicate that is in critical condition of Tank 3 compared to the other tanks. Additionally, the data was evaluated using the RBI qualitative method to compare the proposed approach’s outcomes. An analysis of the outcomes from both methods indicates that the proposed method demonstrated superior accuracy and clarity. The findings can be used in the RBI program.

Cleaner Engineering and TechnologyVol. 23
Razi University (IR), Birmingham City University (GB), University of Johannesburg (ZA), Islamic Azad University Sanandaj Branch (IR)
Openalex Percentile: Top 7%
Multi-Criteria Decision Making
3.43
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