Mehri Mangeli Kamsefidi, Alireza Shahraki, Faranak Hosseinzadeh Saljooghi,
Volume 12, Issue 4 (12-2022)
Abstract
Introduction: Failure Mode and Effects Analysis (FMEA) is a structured way to find and understand the states of a system’s failure and to calculate the resulting effects. In this method, which has been criticized by many researchers, the risk priority number is obtained for each failure mode based on the multiplication of the three parameters of occurrence (O), severity (S) and detection (D). In order to overcome the disadvantages of the traditional method of FMEA, such as ranking the failure and weighting the parameters, this research proposes a model in the fuzzy set.
Material and Methods: The model proposed in this paper is a nonlinear model for weighting the parameters of the FMEA and the revised TOPSIS method for ranking the failures, which is used for the first time to improve the FMEA method.
Results: The proposed model was presented in the Copper Complex of Shahr-e-Babak to assess safety risks. Based on the results of the study, it was found that in this proposed model, the weights of severity and detection were 0.479 and 0.186, respectively, and the results of the ranking showed that the risks of falling from height and getting stuck between objects had the highest and lowest priorities, respectively.
Conclusion: In the proposed model, based on Logarithmic Fuzzy Preference Programming and the revised TOPSIS method, the definite weights of the parameters were presented without any fuzzy number ranking and risk ranking with more criteria, respectively. Therefore, the proposed model has a higher ability compared to the traditional FMEA, and its application can be recommended to determine the ranking of risks.
Towhid Delshad, Farhad Shahraki, Mohammad Reza Sardashti Birjandi, Bahareh Bidar,
Volume 15, Issue 4 (12-2025)
Abstract
Introduction: Industrial units, such as oil refineries, face significant hazards due to the release of toxic and flammable gases. Hydrogen sulfide (H₂S), due to its high toxicity and environmental impact, is among the most dangerous pollutants. This study aimed to model and assess the consequences of H₂S release in the Sulfur Recovery Unit (SRU) of Abadan Refinery using PHAST software to support safety planning and risk reduction strategies.
Material and Methods: Consequence modeling was conducted using PHAST version 8.4. Process data, including temperature, pressure, flow rate, and feed composition, along with meteorological conditions (average temperature, relative humidity, and wind speed based on Pasquill stability classification), were used to define probable scenarios. Scenarios included partial pipeline rupture, variable leak flow, short pipe release, and catastrophic reactor tank rupture. Key damage criteria, including thermal radiation threshold, explosion overpressure, and toxic dose, were used to determine hazard zones.
Results: Thermal radiation up to 71.027 kW/m² can cause instant death within a 70-meter radius, while overpressure exceeding 0.206 bar can destroy equipment and structures up to 35 meters in summer conditions. The H₂S cloud can spread up to 120 meters downwind, causing immediate fatalities among exposed personnel. These findings identify high-risk zones in and around the SRU, emphasizing the need to relocate shelters, install gas monitoring systems, and provide protective equipment. Results are limited to the defined scenarios and PHAST assumptions.
Conclusion: Due to the lack of risk assessment studies in early phases and during operation, identifying safe points and high-risk zones, along with prioritizing risk reduction, is essential to ensure workplace and public safety. Comprehensive risk assessment, including probability analysis (using software such as SAFETI) and application of advanced models (CFD and AI-based methods), is recommended for future research.
