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Synergistic effects of pool fires in fire-induced domino accidents can result in greater damage than single pool fire. Existing research mainly adopts a superposition method based on simplified assumptions to analyze the contribution of synergistic effect of pool fires for domino effects. Therefore, the synergistic effect of pool fires has not been well understood. In this study, a new CFD-based method is developed to model the synergistic effect of pool fires. Case studies were carried out taking double pool fires as an example. The influence of key factors, including wind speed, vertical fire location, fuel type, and separation distance has been investigated quantitatively. The results demonstrated that the proposed CFD based approach can model the consequences of pool fires more comprehensively and assess the domino effects under synergistic effect more precisely than the traditional superposition method. Compared with the single pool fire, the synergistic effect of double pool fires can increase the probability of domino accidents for the adjacent tanks at the downwind by six orders of magnitude. In addition, it is observed that the received maximum radiation heat flux and escalation probability of the target tank in the downwind direction rise with increased wind speed. While the maximum radiation heat flux received by target tanks and escalation probability reduced with increased separation distance and vertical fire location. Moreover, according to the minimum safety distance recommended by present design standards, the synergistic effect of double pool fires in diesel storage tank farms will lead to a higher escalation probability of near equipment than gasoline storage tank farms. This study can be used to predict accident consequences and assess the domino effect under the synergistic effect of pool fires, and guide the layout optimization of the chemical storage tank area. [ABSTRACT FROM AUTHOR]

[Display omitted] It is crucial for emergency responders to makes a quick and accurate prediction of toxic chemical dispersions, which can lead to massive injuries and casualties. In this study, a toxic dispersion database is constructed by PHAST simulations, which consist of 30,022 toxic release scenarios of 19 chemicals. A quantitative consequence prediction model is then developed based on this database to efficiently and accurately predict dispersion downwind distances. Random forest, gradient boosting, and deep neural network algorithms are implemented and compared to find the best performing method for the model construction. The deep neural network is found to have the highest accuracy with the test set R2 higher than 0.994 and RMSE less than 0.1 for all key dispersion ranges. The developed toxic dispersion prediction models can be used to quickly generate instant toxic dispersion range estimations for any toxic chemicals at much lower computational costs. [ABSTRACT FROM AUTHOR]

Abstract Different causes lead to accidental oil spills from fixed and mobile sources in the marine environment. Therefore, it is essential to have a systematic plan for mitigating oil spill consequences. In this research, a general DSS is proposed for passive and active response planning in Persian Gulf, before and after a spill. The DSS is based on NOAA's advanced oil spill model (GNOME), which is now linked with credible met-ocean datasets of CMEMS and ECMWF. The developed open-source tool converts the results of the Lagrangian oil spill model to quantitative parameters such as mean concentration and time of impact of oil. Using them, two new parameters, emergency response priority number (ERPN) and risk index (RI), are defined and used for response planning. The tool was tested in both deterministic and probabilistic modes, and found to be useful for evaluation of emergency response drills and risk-based prioritization of coastal areas. Graphical abstract Unlabelled Image Highlights • A decision support system (DSS) is proposed for oil spill response planning. • The DSS is based on a fast Lagrangian oil spill model (GNOME). • Deterministic consequence modeling facilitates response drills. • High risk areas are determined by probabilistic risk analysis (PRA). • PRA results are used in optimal siting of emergency response stations. [ABSTRACT FROM AUTHOR]

The gas dispersion simulation in complex urban environment posts challenges on consequence analysis. Though computational fluid dynamics (CFD) are general approaches to provide building-resolving estimates, the time consuming calculation and complex process of modeling limit their application for emergency response. In this paper, a cellular automata dispersion model is prompted to simulate continuous point release of propane in 3-D domain with ground obstructions. An artificial neural network is employed to calculate the temporal state transition of cellular automata. To provide data for the neural network to train, fire dynamic simulator (FDS) code is adopted to simulate 100 scenarios of propane release from a fixed position in pre-specific domain with different combinations of meteorological conditions and source parameters. A proportion of the simulation results is selected to train the artificial neural network with different transition rules derived from the advection-diffusion equation. The dispersion processes are eventually replicated with the proposed approach on the remaining scenarios that the artificial neural network has never encountered. Provided with detailed meteorological field data, the cellular automata model could calculate the gas dispersion process about 1.5 times faster than FDS. As to the model performance, in the long term evolution, decreases in model accuracy are observed due to the nature of cellular automata in explicit evolution and the unavailability of error compensation methods. The transition rule that takes source terms into consideration outperforms in estimating the concentration distributions. [ABSTRACT FROM AUTHOR]

One challenge in accounting for process safety incidents is that accurate modeling is complex, time-intensive, and requires many inputs. Process safety consequence modeling using first principles can be complicated. At the same time, setting up experiments is not always practical. This work proposes an artificial neural network (ANN) framework to predict process safety metrics to prevent overpressure during tube rupture scenarios with reasonable accuracy. Specifically, we apply a feed forward neural network to predict heat exchanger safety rating that is proportional to the heat exchanger pressure normalized with respect to the maximum allowable pressure. By training ANN to a set of tube rupture simulation data, we are able to bypasses the need for solving tedious dynamic and non-smooth system of equations. The ANN-based models yield safety rating predictions that comply with API 521 overpressure standards. We further demonstrate how these predictions can be used to perform real-time monitoring for a network of heat exchangers in a plant setting. • ANN framework introduced for detecting overpressure severity in heat exchangers. • Detailed algorithm serves as basis for consequence modeling predictions. • Single high fidelity and generalized safety rating predictions models were developed. • ANN models successfully bypassed rigorous dynamic overpressure models. • Real-time overpressure monitoring demonstrated for heat exchanger network. [ABSTRACT FROM AUTHOR]

The economic viability of industrial processes strongly depends on their safe and reliable operation. The method of inherent safe process design enables systematic consideration of safety measures in order to ensure process safe operation at the early stages of process design. The challenge is that the economic measures that are often considered for the design of industrial processes are often incommensurable with the safety measures. In the present research, a novel framework is proposed in which the safety criteria are quantified based on consequence modeling and aggregated with the economic performance using multi-objective optimization programming. The developed methodology was applied to the design of a simple refrigeration cycle. The optimization algorithm was NSGA-II. The results suggested a strong trade-off between the competing economic and safety objectives in terms of Pareto frontiers that clearly quantified the required compromise. It was observed that only with a minor increase in the capital investment, it is possible to significantly improve the safety. While the case of the refrigeration cycle was selected as a demonstrating case, the research methodology is to large extend general and deemed to be acceptable to design and operation of other industrial processes. [ABSTRACT FROM AUTHOR]

The main objectives of any drilling companies are drilling safely, providing usable well completion and minimizing costs. Among all, health, safety and environment (HSE) consideration supersedes. Also, oil and gas well-drilling industry is an industry with high level of risks concerning HSE. Not only does each factor of these risks need to be analyzed but also need to be adjusted by the appropriate risk modeling. This project is assigned to model risk and consequence assessment for some aspects of blowout. The consequences should be formulated but require some adjustment. Proper Delphi group for risk assessment is made to localized risk factors. As there is uncertainty during data collection, the fuzzy approach is used. Finally, prioritizing the assets according to their criticality demonstrate significance of the risk. In the case study, the blowout in onshore Iranian drilling industry is studied. The results show that the risk of blowouts according to the reason of shallow gas in exploration well is the highest. Human failure, attack, natural event, lost circulation in development well and human failure in workover well, are another risks for Iranian drilling industry, respectively. [ABSTRACT FROM AUTHOR]

There are different well-established strategies for making a process plant inherently safer. The benefits of applying these strategies on reducing the overall risk inside a plant are obvious. However, some of these changes are rejected many times because they appear to be too costly. But if the effects of applying inherently safer design strategies are investigated not only on the processing costs of a plant but also on the potential accident costs, the decision would in fact be different. In this paper an optimization procedure is proposed which integrates both processing and accident costs for different design schemes. In this procedure, some of the design variables are chosen with regard to inherently safer design strategies. The objective function is the sum of accident costs and plant lifecycle processing costs. For assessing accident costs, consequence modeling techniques and probit functions are applied. Consequence modeling formulas and an objective function are codified in an optimizer package (MATLAB) and to accomplish the optimization process a process simulator (called HYSYS) is coupled with this package. The application of the proposed procedure is demonstrated by selecting an optimum process scheme for a Refrigeration plant as a case study. [ABSTRACT FROM AUTHOR]

Abstract: Cryogenic compressed hydrogen tank may open new possibilities for onboard storage due to its high energy density and acceptable thermal endurance. As promising hydrogen storage for commercial use, its hazards need comprehensive investigation. This paper studies the consequences of accidental hydrogen releases from cryo-compressed storage and evaluates the cold effects, thermal effects, and overpressure and missile effects. Two typical storage conditions for a fuel cell car are considered, including driving condition and quasi-venting condition after a long-term of parking. Results show that flash fire and vapor cloud explosion can be considered as the leading consequences. Without ignition, catastrophic rupture may be more dangerous than leakages but with ignition the results may vary for different release diameters. For leakages, quasi-venting condition may be more dangerous than driving condition. However, for catastrophic rupture, the results may be not uniformed but depend on whether and when the hydrogen is ignited. Moreover, the influences of wind velocity and atmospheric pressure are also investigated. [Copyright &y& Elsevier]

Abstract: The accidental releases of hydrogen from liquid storage and the subsequent consequences are studied from a harm perspective rather than a standpoint of risk. The cold, thermal and overpressure effects from hydrogen cold cloud, fireball, jet fire, flash fire, and vapor cloud explosion are evaluated in terms of two kinds of effect distances based on lethal and harmful criteria. Results show that for instantaneous release, the sequence of effect distances is vapor cloud explosion > flash fire > cold cloud > fireball, and for continuous release, the sequence is vapor cloud explosion > flash fire > jet fire > cold cloud. An overall comparison between instantaneous and continuous release reveals that the catastrophic rupture, rather than leakages, is the dominant event. Besides, the effect distances of liquid hydrogen tank are compared with those of 70 MPa gaseous storage with equivalent mass. Compared with 70 MPa gaseous storage, the liquid hydrogen storage may be safer under leak scenarios but more dangerous under catastrophic rupture scenario. [Copyright &y& Elsevier]

Abstract: With the development of large-scale fell cell vehicle demonstration project worldwide, the global number of hydrogen refueling stations has increased rapidly in recent years. The external safety of hydrogen refueling stations has always been a public concern for its further development. This paper examines the harm effect distances of severe accidents for a gaseous hydrogen refueling station. First, different accident scenarios are assumed and their subsequent consequences are calculated, including physical explosion, jet fire, flash fire and confined vapor cloud explosion. Results show that physical explosion and worst case of confined vapor cloud explosion produce the longest harm effect distances for instantaneous release and continuous release, respectively. This indicates that they may be used as decisive consequences to the determination of safe distances. Second, the influences of different factors on harm effect distances are investigated, including those of release inventory, release pressure, release height, release angle, release diameter and wind velocity. Then, based on these results, several potential hazard mitigation measures are proposed such as elevating hydrogen equipment, using smaller vessel and adopting smaller pipe work, if reasonably practicable. [Copyright &y& Elsevier]

Abstract: Risk assessment in chemical process industry is a very important issue for safeguarding human and the ecosystem from damages caused to them. Consequence assessment is an integral part of risk assessment. However, the commonly used consequence estimation methods involve time-consuming complex mathematical models and simple assimilation of losses without considering all the consequence factors. This lead to the deterioration of quality of estimated risk value. So, the consequence modeling has to be performed in detail considering all major losses with optimal time to improve the decisive value of risk. The losses can be broadly categorized into production loss, assets loss, human health and safety loss, and environment loss. In this paper, a conceptual framework is developed to assess the overall consequence considering all the important components of major losses. Secondly, a methodology is developed for the calculation of all the major losses, which are normalized to yield the overall consequence. Finally, as an illustration, the proposed methodology is applied to a case study plant involving benzene extraction. The case study result using the proposed consequence assessment scheme is compared with that from the existing methodologies. [Copyright &y& Elsevier]

Liquefied natural gas (LNG) project modeling focuses on two primary issues, facility siting and the physical layout of element spacing. Modeling often begins with an analysis of these issues, while ensuring code compliance and sound engineering practice. The most commonly performed analysis involves verifying compliance with the siting provisions of NFPA 59A, which primarily concern property-line spacing (offsite hazard impacts). If the facility is located in the US, compliance with 49 CFR 193 is also required. Other consequence modeling is often performed to determine the spacing of elements within the facility (onsite hazard impacts). Often, many issues concerning in-plant spacing are addressed with the guidance provided in Europe''s LNG standard, EN-1473. Spacing of plant buildings in relation to process areas is also a concern as analyzed using the approach given in API RP 752. Studies may also include probabilistic analysis, depending on the perceived risk and cost of mitigation. [Copyright &y& Elsevier]