Figure 1
![LPG Cylinder filling installation layout and nearby surroundings. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]](profile/Esmaeil-Zarei-2/publication/260406066/figure/fig6/AS:281688459497475@1444171170177/LPG-Cylinder-filling-installation-layout-and-nearby-surroundings-Color-figure-can-be.png)
LPG Cylinder filling installation layout and nearby surroundings. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]
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![Figure 3: Flow diagram of the procedure used for QRA [10, 11]. [Color...](profile/Esmaeil-Zarei-2/publication/260406066/figure/fig3/AS:281688392388673@1444171154737/Flow-diagram-of-the-procedure-used-for-QRA-10-11-Color-figure-can-be-viewed-in-the_Q320.jpg)
In recent years in the process industries much attention has been paid to the quantitative risk analysis (QRA). This study describes a QRA evaluating the risk from the operation of an LPG installation. Both individual and societal risks to the installation personnel, customers, and neighbors/passer-bys are evaluated. The study showed that the large...
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Citations
... IR(x, y) denotes the total probability of fatality at a specific location (x, y) and can be expressed as in Equation (17). The total IR at each location represents the sum of the IR for all possible accident scenarios that can occur at that location, as calculated and expressed in Equation (18) [41]. ...
... SR is expressed as a relationship between the frequency of occurrences and the number of fatalities. It is determined based on the sum of total IR for the facilities within the accident scenarios, considering the number of fatalities [41]. The SR for the case with the shutoff valve is shown in Figure 7. ...
Hydrogen refueling stations (HRS) operating at high pressures pose a higher risk of leakage than conventional gas stations. Therefore, in this study, a quantitative risk assessment (QRA) was conducted using DNV-GL SAFETI v.8.9. The impact of the shutoff valve was quantitatively assessed, and step-by-step mitigation was applied to propose the minimum installation requirements for the valve necessary to achieve broadly acceptable risk levels. The QRA includes sequence analysis (CA), individual risk (IR), and societal risk (SR), with accident scenarios consisting of catastrophic ruptures and three leak scenarios. The research results indicate that the application of a dual shutoff valve system resulted in an IR of 7.48 × 10−5, effectively controlling the risk below the as low as reasonably practicable (ALARP) criteria of the Health and Safety Executive (HSE). The SR was analyzed based on the ALARP criteria in the Netherlands, and the application of the dual shutoff valve system effectively controlled the risk below the ALARP criteria. Consequently, this study suggests that applying a dual shutoff valve system with a mitigation value exceeding 1.21 × 10−2 can successfully mitigate the risk of urban hydrogen refueling stations to broadly acceptable levels.
... Since LPG occupies more volume at normal conditions and is more prone to fire and explosion hazards, it is stored in fully refrigerated conditions. Mechanical failures, weld failure, or rupture of LPG cylinders may lead to a loss of containment [2]. Small vapour leaks from LPG cylinders and rapid vaporization of tons of LPG are some of the hazards in LPG plants [3]. ...
The accidental release of toxic gases leads to fire, explosion, and acute toxicity, and may result in severe problems for people and the environment. The risk analysis of hazardous chemicals using consequence modelling is essential to improve the process reliability and safety of the liquefied petroleum gas (LPG) terminal. The previous researchers focused on single-mode failure for risk assessment. No study exists on LPG plant multimode risk analysis and threat zone prediction using machine learning. This study aims to evaluate the fire and explosion hazard potential of one of Asia’s biggest LPG terminals in India. Areal locations of hazardous atmospheres (ALOHA) software simulations are used to generate threat zones for the worst scenarios. The same dataset is used to develop the artificial neural network (ANN) prediction model. The threats of flammable vapour cloud, thermal radiations from fire, and overpressure blast waves are estimated in two different weather conditions. A total of 14 LPG leak scenarios involving a 19 kg capacity cylinder, 21 tons capacity tank truck, 600 tons capacity mounded bullet, and 1350 tons capacity Horton sphere in the terminal are considered. Amongst all scenarios, the catastrophic rupture of the Horton sphere of 1350 MT capacity presented the most significant risk to life safety. Thermal flux of 37.5 kW/ m2 from flames will damage nearby structures and equipment and spread fire by the domino effect. A novel soft computing technique called a threat and risk analysis-based ANN model has been developed to predict threat zone distances for LPG leaks. Based on the significance of incidents in the LPG terminal, 160 attributes were collected for the ANN modelling. The developed ANN model predicted the threat zone distance with an accuracy of R2 value being 0.9958, and MSE being 202.9061 in testing. These results are evident in the reliability of the proposed framework for safety distance prediction. The LPG plant authorities can adopt this model to assess the safety distance from the hazardous chemical explosion based on the prior forecasted atmosphere conditions from the weather department.
... Between 1975 and 2019, 27,795 catastrophic accidents occurred due to failures in the RTHM in the US, killing 2946 people (Bureau of Transportation, 2017). In urban areas, due to high population density and congested environment, any Hazmat (hazardous material) leakage can have far more severe effects, as evidenced by past accidents (Dormohammadi et al., 2014). For example, an LPG leak in 2000 at a gas distribution center in Mexico City led to the explosion of 10 LPG tankers. ...
Rail transport of hazardous material (RTHM) plays a vital role in the supply chain of raw materials and products. However, RTHM can pose severe risks due to the large quantities of flammable and explosive chemicals transported over rail tracks crossing residential and industrial areas and possible human and technical failures. Among the potential safety issues, the domino effect is one of the most feared events, which can have devastating consequences despite its relatively low probability. As the first study, the present investigation develops a dynamic risk analysis model for analyzing domino effects in RTHM based on Dynamic Bayesian Network. Accident scenarios such as pool fire, flash fire, fire ball, vapor cloud explosion, and BLEVE are considered to analyze domino effects. The model performance is tested on a real RTHM (i.e., gasoline transportation), demonstrating the effectiveness of the proposed model in simulating the domino-driven effects in terms of both consequences and probability escalation and in dealing with the parameter and model uncertainties.
... Identifying hazards is a vital step in quantitative risk analysis, which aims to identify hazard sources, release causes, and contribute to the development of accident scenarios (SFPE, 2006), (Xin et al., 2017). For this purpose, we use the structured hazard identification technique (HAZID), which is a capable technique in hazard identification and risk analysis studies (Lee, 2020), (Ali et al., 2006). An accident scenario is a description of the expected situation, which may include a single event or a series of consecutive events (Khan and Abbasi, 2002). ...
Pool fires are considered catastrophic events in hydrocarbon liquid process pipelines. There is much research performed on fire risk analysis of liquid pipelines; however, probabilistic-quantitative methods that are based on the leak size are yet to be further developed. This paper develops a framework for quantitative fire risk analysis in liquid process pipelines based on probabilistic analysis and computational fluid dynamics. The significance of leaked volume and its dependency on the leak size, here the pipeline failure frequency is distributed into the frequencies of different leak sizes using historical data and the Bayesian network. The frequency of fire occurrence is then determined by combining the ignition probability of each leakage rate, the flammability specification of released materials, and the frequency of each leak size. In the vulnerability assessment, the thermal dose received by individuals is modified to account for the possibility of escape. The developed framework is next employed in a gasoline pipeline with a 1 km length. Results show that the pool fire scenario resulting from the rupture of the pipeline, with a frequency of 1.18 × 10⁻⁷ (km⁻¹. y⁻¹) and an area of exposure of 5498.4 m², is the maximum-credible scenario. Two separate escape routes with different distances to the fire center are defined. As well, two escape speeds of 4 and 6 m/s are considered. The results show that the initial radiation and the escape speed can significantly affect the sustained damage to individuals. This study is a step forward in dynamic-quantitative individual risk analysis in pool fires of hydrocarbon liquid pipelines.
... Previous studies have shown that the quantitative risk analysis (QRA) approach can be used as a reliable and highprecision technique for determining safety zones on transportation routes [19][20][21] and hazardous material storages [22,23]. For example, Ahmadi et al. used the new Fuzzy-Bayesian network approach for risk assessment in the process industries [24]. ...
... In addition, the new fuzzy approach was used by Miri Lavasani et al. to assess the oil and gas industries [28]. Dormohammadi et al. used the QRA approach to model the potential safety risks and consequences of LPG [23]. Other recent QRA studies were on hydrogen release [29,30] and the dynamic QRA on hydrogen infrastructure [31]. ...
e hazardous nature of the chemical materials is of significant concern in the economic viability of rail transportation globally. e potential risks of these materials to cause severe health impairments and catastrophic accidents have been widely studied and reported. Moreover, several models have been employed for assessing the risks associated with transporting hazardous materials by rail. However, a more holistic, quantitative, and robust model should incorporate more potential risk-triggered criteria, especially those causing severe health loss and devastating consequences like vapor cloud explosion. is study develops a risk assessment model by incorporating potential health risk factors and the obstacle circumstances. e potential risk factors are population density, route distance from residential areas, and the availability of sensitive third parties for health consequences. e proposed model utilizes Bayesian networks for causality modeling of the material release scenarios and fuzzy set theory for estimating the health effects and severity impact coefficient. Finally, individual risk curves and safe distances from the railway are developed. A real rail system for gasoline transportation in Tehran is investigated to evaluate the model's effectiveness. e study provides panoramic leverages for risk-managed decision-making for safely transporting hazardous material by rail.
... The findings of the present research were confirmed by other studies. For instance, Ramos et al. (2020) recently argued that the most well-known HRA techniques have been proposed and utilized in NPPs, whereas the process industry has mainly concentrated on process safety in terms of technical aspects of the operation and equipment as well as quantitative risk analysis (QRA) [14,15]. Considering the human role as the factor most contributing to major accidents, there is therefore, an urgent call for leading researchers and academic centers to pay more attention to this domain. ...
Chemical process industries (CPIs) work with a variety of hazardous materials in quantities which have the potential to have large health, environmental and financial impacts and as such are exposed to the risk of major accidents. The experience with accidents in this domain shows many cases which involve complex human-machine interactions. Human Reliability Analysis (HRA) has been utilized as a proactive approach to identify, model, and quantify human error highlighted as the leading cause of accidents. Consequently, researchers have actively worked on enhancing process safety and risk engineering since the '70s. However, despite its importance and practical implications for improving human reliability, there has not been a review of human reliability related to processing systems. The present study is aimed at presenting a systematic attempt to identify the needs, gaps, and challenges of HRA in CPI. An in-depth analysis of the literature in Web of Science core collection and Scopus databases from 1975 to August 2020 is conducted. This analysis focuses on human factors in three critical elements of CPIs: maintenance operations, emergency operations, and control room operations. The analysis synthesizes the theoretical and empirical findings, shedding light on the strengths and shortcomings of current literature and identifying research opportunities. A comparison of HRA in CPIs is undertaken with nuclear power plants (NPPs) to better understand the current stage of research and research challenges and opportunities.
... Tasnim (2016) reported that the extent of the damage was estimated to be around 94 million euros and it was nominated as the most serious fire accident in the history of the Iranian petrochemical industry. Thus, applying risk assessment techniques to assign suitable safety measures to keep potential risks below the acceptance level is essential in chemical process plants (Dormohammadi et al., 2014;Yazdi, 2019). The final outcomes from applying these techniques significantly depend on the probabilities of the root events. ...
Quantitative risk assessment (QRA) techniques methodically assess the likelihood, impact, and subsequently the risk of adverse events. In a typical QRA method, one of the main intentions is to identify the critical root events which mostly contribute to the risk of the top event (TE) and requiring subsequent corrective actions (CAs). Finding the critical events which contribute to the risk is significantly dependent on the assumptions and methods applied to integrate the probabilities of different events and these events may have really low probability of occurrence. Thus, the probability reduction of the critical root events and subsequently the system’s failure does not lead to an optimal solution. For this reason, ranking the CAs without consideration of several aspects such as their influence on root events probability, inter-relationships, and direct/indirect cost, is not an appropriate approach. This study aims to introduce an approach to deal with the aforementioned situations. A novel extension to DEMATEL (decision making trial and evaluation laboratory) named Pythagorean fuzzy DEMATEL is proposed on a common probabilistic safety analysis. As a case study, a collapse in an offshore facility platform (including 42 basic events and corresponding 30 CAs) is considered to illustrate the effectiveness of the presented approach. The application of the model confirms its robustness in prioritizing critical root events and CAs compared with a conventional model, consideration of the influencing factors, and a dynamic and flexible structure.
... Chemical process plants are more susceptible to catastrophic disasters due to handling various and huge amounts of hazardous materials which are stored or processed under severe conditions (Khan and Abbasi, 1998). Therefore, safety assessment is very crucial in order to measure risk and to design preventive and mitigative safety strategies in chemical process plants (Dormohammadi et al., 2014;Zarei et al., 2013). Different methods have been proposed to safety analysis and each of them have specific applications. ...
Risk analysis in process systems is very important to design effective strategies for preventing and mitigating potential major accidents. Although conventional techniques as Bow-tie (BT) have widely been used in risk assessment of process systems, they fall short in effectively modelling epistemic uncertainty which is prevailing in risk assessment of process systems. The present study is aimed at alleviating this shortcoming by incorporating fuzzy set theory into BT, developing a so-called fuzzy extended Bow tie (FEBT) model. FEBT, compared with previous fuzzy BT methods, uses the intuitionistic fuzzy numbers and thus provides a more accurate cause-consequence model of accident scenarios. A natural gas transmission network is used to demonstrate the application of FEBT.
... Normally IR was defined as the probability of death to an individual at any particular location due to all undesired events [8,9]. The total IR at each point was equal to the sum of the IR of all scenarios effects at that point [10], whereas SR expressed the cumulative risk to groups of people who might be affected by such accident scenarios [11]. This paper will focus on the IR inside the process plants since the individuals may be facing a more direct exposure to toxic gases under release conditions. ...
... The IR evaluation is also in the scope of quantitative risk analysis (QRA) [10]. QRA is the prevailed risk assessment method and has been widely used in process safety related areas, including design of safety measures [12], safety management and decision making [11,13,14], developing risk-based maintenance and inspection strategies [15][16][17], and so forth. ...
Individuals working in process facilities containing toxic gases may face gas releases and poisoning risks. Many studies regarding individual risk (IR) have been carried out on a worst scenario basis. However, the worst scenario‐based approach cannot represent realistic release risks and may overestimate the IR. In this study, an approach based on complete accident scenario set (CASS) and computational fluid dynamics (CFD) is proposed to quantitatively assess IR of toxic gas release in process facilities. By combining the gas leakage probability and joint distribution probability of the wind direction and speed, a CASS can be built. The CFD method is used to predict the concentration field of gas release and dispersion. Then, the toxic gas concentration can be converted to poisoning fatality probabilities according to the dose–response model. A virtual IR contour can finally be defined by the accumulative assessment of all release scenarios. A case study of an IR area classification in a natural gas process and carbon dioxide recycle terminal processing facility that contains an ammonia refrigeration system is also investigated. With the proposed methodology, the quantitatively classified IR level in process facilities can provide scientific references for safety decision makers. © 2018 American Institute of Chemical Engineers Process Process Saf Prog 38: 52–60, 2019
... The study by Kariznovi et al., (2017), as well as a research by DorMohammadi et al., (2014), 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. ...
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 Process hazard analysis software Tools (PHAS) 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/m2 in the 10/D climate class, which extends up to 28 meters.
Conclusions
Given the distribution of Mercaptan at long distances and the proximity of gas pressure reduction stations of the respective gas company to the residential and medical facilities, it is strongly recommended that the location of these barrels be moved away from residential areas.
