Risk analysis by means of a QRA approach on a LPG cylinder filling installation

Dormohammadi, Ali; Zarei, Esmaeil; Delkhosh, Mohammad Bagher; Gholami, Ali

doi:10.1002/prs.11623

Cited by 18 publications

(17 citation statements)

References 6 publications

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“…The study by Kariznovi et al, (2017) (7) as well as a research by Dormohammadi et al, (2014) (6) showed that the weather condition has an impact on the severity of eruptive and abrupt fire (6,7), which is consistent with the results of this study.…”

Section: Discussionsupporting

confidence: 91%

“…Furthermore, the release of chemical substances from the process plants is a significant hazard in process industries, which may endanger the staff and public health within the vicinity of such facilities. A brief review of the history of refinery incidents reveals that gas -related disasters have frequently occurred over the previous decades (6)(7)(8). Given the above -mentioned examples, it must be noted that consequence evaluation of hazards such as fire and discharge of substances from the oil and gas reservoirs is a crucial step in order to enhance the level of safety in existing or developing units (9).…”

Section: Introductionmentioning

confidence: 99%

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Consequence Analysis of Fire and Release of Mercaptan Spills in Pressure Reducing Station of a Provincial Gas Company

Kordmiri

Kesmati

Jodakinia

et al. 2018

Jundishapur J Health Sci

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Background: Mercaptans are the highly flammable and malodorous natural gas odorants in the urban gas distribution network and are used to detect gas leakage. Exposure to high concentrations of this substance has deleterious impacts on human health. Objectives: The purpose of this study was to determine the hazard distance and to examine the consequences of fire and the distribution of Mercaptans spills in its containing station in a specific provincial gas company. Methods: Modeling scenarios were defined based on the valid existing events and related consequences with respect to the gas pressure reducing station. To determine the safe distances of hazardous areas, applicable data and criteria were used in accordance with total GS SF 253. These criteria include the amount of flammable radiation in the event of Mercaptan fire, the amount of LFL (low flammable level) Mercaptan distribution, and the distribution rate of various concentrations of Mercaptan (0.5, 10 and 100 ppm). Subsequently, modeling was performed using input parameters and via PHAST software. Finally, the consequence evaluation of scenario occurrence and hazard distance were identified through the modeling results. Results: The distribution and pool fire caused by Mercaptan spill from containers were considered as the worst scenario at the respective gas station. Results from the modeling indicated a large distance distribution (3997 m) from the concentration of 0.5 ppm of Mercaptan (concentration of respiratory tract burning threshold) in case of a spill. Furthermore, according to the results of modeling in the event of a fire, the maximum radiation distance is 4.7 kW/m 2 in the 10/D climate class, which extends up to 28

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Consequence Analysis of Fire and Release of Mercaptan Spills in Pressure Reducing Station of a Provincial Gas Company

Kordmiri

Kesmati

Jodakinia

et al. 2018

Jundishapur J Health Sci

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“…PHAST is a professional simulator used for CM in chemical process risk assessments . More description of CM that is used in this work may be find in previous work of the authors . At the end, risk has been estimated by multiply of occurrence probability and severity (lethality numbers in this work) of a given scenario.…”

Section: Proposed Methodologymentioning

confidence: 99%

Dynamic safety risk modeling of process systems using bayesian network

Zarei

Azadeh

Aliabadi

et al. 2017

Process Safety Progress

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Process complex systems in particular oil and gas plants due to dealing with hazardous materials at severe process conditions are much prone to catastrophic accidents. In this context, safety risk analysis is a crucial tool to develop effective strategies to prevent accident and provide mitigative measures. Dynamic risk analysis (DRA) is one of the most practical approaches for risk analysis that helps provide safer operations of complex process systems. The present work is aimed at demonstrating the application of an integrated DRA approach to comprehensive quantitative modeling and analysis of the both aspects of risk, that is, probability and consequence assessments. In this approach, first, the worst case scenario is identified and then a robust tool is developed for dynamic accident scenario modeling and risk assessment by means of Bayesian Network. This approach is applied to risk analysis of a flammable liquid storage system at a gas refinery. The work provides valuable information on the identification and comprehensive analysis of worst case accident scenarios, their main consequences, critical basic events, and minimal cut sets which lead to accident scenarios and also for dynamic updating of probabilities and risk. The obtained results are more appropriate and rigorous to developing preventive and mitigative strategies for potential accident scenarios and thus increase the safety level in the complex process systems. © 2017 American Institute of Chemical Engineers Process Saf Prog 36: 399–407, 2017

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“…This simulator is specially validated for the release of hydrogen [27] and it is one of the most accurate and precise tool for QRA and consequence modeling [28,29]. It is capable to simulate the progress of a potential incident from its initial leakage to the final possible consequences [23,26]. For the purpose of simulating accident outcomes by PHAST, several assumptions were adopted that include:…”

Section: Consequence Analysismentioning

confidence: 99%

“…In addition, the traditional risk assessment is not adequate to analyze risks in complex systems [22]. The QRA methodology is a proper tool that can be applied to achieve this objective [23].…”

Section: Introductionmentioning

confidence: 99%