Showing papers in "Journal of Loss Prevention in The Process Industries in 2020"
TL;DR: In this article, a review of recent applications of CFD for fire, explosion, dispersions of flammable and toxic materials from accidental releases, incident investigations and reconstructions, and other areas of process safety is presented.
Abstract: In recent years, significant progress has been made to ensure that process industries are among the safest workplaces in the world. However, with the increasing complexity of existing technologies and new problems brought about by emerging technologies, a strong need still exists to study the fundamentals of process safety and predict possible scenarios. This is attained by conducting the corresponding consequence modeling and risk assessments. As a result of the continuous advancement of Computational Fluid Dynamics (CFD) tools and exponentially increased computation capabilities along with better understandings of the underlying physics, CFD simulations have been applied widely in the areas of process safety and loss prevention to gain new insights, improve existing models, and assess new hazardous scenarios. In this review, 126 papers from 2010 to 2020 have been included in order to systematically categorize and summarize recent applications of CFD for fires, explosions, dispersions of flammable and toxic materials from accidental releases, incident investigations and reconstructions, and other areas of process safety. The advantages of CFD modeling are discussed and the future of CFD applications in this research area is outlined.
90 citations
TL;DR: A systematic review of the current state-of-the-art research on risk analysis of LNG facilities is presented in this article, where the authors identified, reviewed, and categorized according to risk assessment methods (qualitative, semi-qualitative or quantitative; deterministic or probabilistic; conventional or dynamic).
Abstract: In recent years, the global demand for liquefied natural gas (LNG) as an energy source is increasing at a very fast rate. In order to meet this demand, a large number of facilities such as platforms, FPSO (floating production, storage and offloading), FSRU (floating storage and regasification unit) and LNG ships and terminals are required for the storage, processing and transportation of LNG. Failure of any of these facilities may expose the market, companies, personnel and the environment to hazards, hence making the application of risk analysis to the LNG sector a very topical issue throughout the world. To assess the risk of accidents associated with LNG facilities and carriers, various risk analysis approaches have been employed to identify the potential hazards, calculate the probability of accidents, as well as assessing the severity of consequences. Nonetheless, literature on classification of the risk analysis models applied to LNG facilities is very limited. Therefore, to reveal the holistic issues and future perspectives on risk analysis of LNG facilities, a systematic review of the current state-of-the-art research on LNG risk analysis is necessary. The aim of this paper is to review and categorize the published literature about the problems associated with risk analysis of LNG facilities, so as to improve the understanding of stakeholders (researchers, regulators, and practitioners). To achieve this aim, scholarly articles on LNG risk analysis are identified, reviewed, and then categorized according to risk assessment methods (qualitative, semi-qualitative or quantitative; deterministic or probabilistic; conventional or dynamic), tools (ETA, FTA, FMEA/FMECA, Bayesian network), output/strategy (RBI, RBM, RBIM, facility siting, etc.), data sources (OREDA handbook, published literature, UK HSE databases, regulatory agencies' reports, industry datasets, and experts’ consultations), applications (LNG carriers and LNG fuelled ships, LNG terminals and stations, LNG offshore floating units, LNG plants), etc. Our study will not only be useful to researchers engaged in these areas but will also assist regulators, policy makers, and operators of LNG facilities to find the risk analysis models that fit their specific requirements.
58 citations
TL;DR: In this paper, a self-made device was used to collect gases from Li-ion battery thermal runaway, when the batteries were under different states of charge (SOC), temperatures of the environment and powers of external heating.
Abstract: The thermal runaway of lithium-ion battery (or Li-ion battery, LIB) results in scrap of battery and fire, with the toxic and flammable gases generated. In this work, a self-made device was to collect gases from LIB thermal runaway, when the batteries were under different states of charge (SOC), temperatures of the environment and powers of external heating. Three samples of the collected gases were analyzed to get the results of the composition and content by chromatography-mass spectrometry system (GC-MS). The lower explosion limits (LELs) of the gases was tested by FRTA explosion limit instrument. And then the LEL of three analyzed samples whose composition and content were known by GC-MS were calculated via theoretical formulas. The calculated LELs were compared with those of the instrument test. The errors of the two results of three samples are 2.1%, 1.9%, and 0.4%. The Le Chatelier Formula and empirical formula provide a way to evaluate the LEL of the battery runaway gas more quickly.
57 citations
TL;DR: An integrated framework for coordinating the conventional process design workflow with safety analysis at various levels of detail is introduced, and the need to consider safety as a major component of process sustainability is highlighted.
Abstract: This paper reviews principal concepts, tools, and metrics for risk management and Inherently Safer Design (ISD) during the conceptual stage of process design. Even though there has been a profusion of papers regarding ISD, the targeted audience has typically been safety engineers, not process engineers. Thus, the goal of this paper is to enable process engineers to use all the available design degrees of freedom to mitigate risk early enough in the design process. Mainly, this paper analyzes ISD and inherent safety assessment tools (ISATs) from the perspective of inclusion in conceptual process design. The paper also highlights the need to consider safety as a major component of process sustainability. In this paper, 73 ISATs were selected, and these tools were categorized into three groups: hazard-based inherent safety assessment tools (H-ISATs) for 22 tools, risk-based inherent safety assessment tools (R-ISATs) for 33 tools, and cost-optimal inherent safety assessment tools (CO-ISATs) for 18 tools. This paper also introduces an integrated framework for coordinating the conventional process design workflow with safety analysis at various levels of detail.
54 citations
TL;DR: This paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach, and the effectiveness and feasibility of the proposed model are validated.
Abstract: Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.
43 citations
TL;DR: The results indicate that remodeling of these systems and simultaneous construction activities are the most important factors in the failure of the fire alarm system.
Abstract: In almost all industries, fire alarm systems play a vital role in the reducing the risks associated with fires and damages. Therefore, it is necessary to evaluate their reliability and performance in emergency situations. The present study aimed to use fault tree analysis (FTA) to determine the root causes involved in the failure of fire alarm systems, to use Fuzzy set theory and expert elicitation to determine relative probabilities, and finally, to evaluate the reliability of a fire alarm system using dynamic Bayesian networks (BNs) during a thirty-six months period. A total of 29 basic events were detected from the FT. The reliability of the fire alarm system was estimated at 0.954 according to the FT and 0.957 according to conventional BNs. The reliability of the fire alarm system after 36 months was estimated at 0.375 according to dynamic BNs. All the events involved in the failure of fire alarm systems were drawn in the fault tree diagram. The results indicate that remodeling of these systems and simultaneous construction activities are the most important factors in the failure of the fire alarm system. System reliability can also be increased to 0.965 by providing preventive and control measures to reduce the probability of critical events.
40 citations
TL;DR: In this article, a methodology was developed for the quantitative assessment of risk due to domino effects caused by Natech accidents triggered by lightning, and the results of the case-study showed that an increase up to two orders of magnitude with respect to risk calculated for conventional scenarios is possible when considering lightning-induced Natech primary scenarios and their escalation.
Abstract: Lightning strike is the natural event more frequency causing Natech accidents involving atmospheric storage tanks. Despite the resulting fires have usually limited severity and only local effects, domino effect may cause the escalation of these primary events, possibly affecting nearby pressurized storages and process equipment, thus resulting in relevant increase in the potential area impacted. A methodology was developed for the quantitative assessment of risk due to domino effects caused by Natech accidents triggered by lightning. A comprehensive procedure was obtained, tailoring lightning risk assessment to include probabilistic models for domino escalation based on probit approach and combinatorial analysis. The methodology was applied to a case-study to evidence the shift in risk figures due to domino effect and the credibility of the secondary domino scenarios. The results of the case-study show that an increase up to two orders of magnitude with respect to risk calculated for conventional scenarios is possible when considering lightning-induced Natech primary scenarios and their escalation.
39 citations
TL;DR: In this article, the authors investigated the inhibition effects of Al(OH)3 and Mg(OH)-2 powders on Al-Mg alloy explosion and found that when 80% Mg-OH-2 powder was added, the explosion pressure was reduced to less than 1 MPa, and the explosion was restrained.
Abstract: To identify a superior explosion suppressant for Al-Mg alloy dust explosion, the inhibition effects of Al(OH)3 and Mg(OH)2 powders on Al-Mg alloy explosion were investigated A flame propagation suppression experiment was carried out using a modified Hartmann tube experimental system, an explosion pressure suppression experiment was carried out using a 20-L spherical explosion experimental system, and the suppression mechanisms of the two kinds of powders on Al-Mg alloy dust explosion were further investigated The results demonstrate that by increasing the mass percentages of Al(OH)3 and Mg(OH)2, the flame height, flame propagation speed and explosion pressure of deflagration can be effectively reduced When 80% Mg(OH)2 powder was added, the explosion pressure was reduced to less than 01 MPa, and the explosion was restrained Due to the strong polarity of the surface of Mg(OH)2, agglomeration easily occurs; hence, when the added quantity is small, the inhibition effect is weaker than that of Al(OH)3 Because the Mg(OH)2 decomposition temperature is higher, the same quantity absorbs more heat and exhibits stronger adsorption of free radicals Therefore, to fully suppress Al-Mg alloy explosion, the suppression effect of Mg(OH)2 powder is better
37 citations
TL;DR: The developed forecast model successfully predicts future fault occurrences rate followed by dissimilarity rate from clustering results holds the validity of 91.9% when applied to the historical pressure datasets.
Abstract: The world of oil pipelines is subjected to serious issues due to occurrences of toxic spills, explosions and deformations like particle deposition, corrosions and cracks due to the contact of oil particles with the pipeline surface Hence, the structural integrity of these pipelines is of great interest due to the probable environmental, infrastructural and financial losses in case of structural failure Based on the existing technology, it is difficult to analyze the risks at the initial stage, since traditional methods are only appropriate for static accident analyses Nevertheless, most of these models have used corrosion features alone to assess the condition of pipelines To sort out the above problem in the oil pipelines, fault identification and prediction methods based on K-means clustering and Time-series forecasting incorporated with linear regression algorithm using multiple pressure data are proposed in this paper The real-time validation of the proposed technique is validated using a scaled-down experimental hardware lab setup resembling characteristics exhibited by onshore unburied pipeline in India In the proposed work, crack and blockages are identified by taking pressure rise and pressure drop inferred from two cluster assignment The obtained numerical results from K-means clustering unveils that maximum datasets accumulated range of multiple pressures are within 16147–10638 kg/cm2, 14922–121674 kg/cm2, 27645–12063 kg/cm2 correspondingly Hence by this final cluster center data, inspection engineers able to estimate the normal and abnormal performance of oil transportation in a simple-robust manner The developed forecast model successfully predicts future fault occurrences rate followed by dissimilarity rate from clustering results holds the validity of 919% when applied to the historical pressure datasets The models are expected to help pipeline operators without complex computation processing to assess and predict the condition of existing oil pipelines and hence prioritize the planning of their inspection and rehabilitation
35 citations
TL;DR: The obtained results are very close to the results from pre-existing approaches which confirm that the proposed approach is a more realistic alternative for the study of system reliability in intuitionistic fuzzy environment when quantitative failure data of system components are not known.
Abstract: In quantitative fault tree analysis of a system, exact failure probability values of components are utilized to calculate the failure probability of the system. However, in many real world problems, it is problematic to get precise and sufficient failure data of system components due to insufficient or imprecise information about components, changing environment or new components. A methodology has already been developed by employing fuzzy set theory for the system reliability evaluation by utilizing qualitative failure data of system components when quantitative failure data of components are inaccessible or insufficient. This paper extends the concept of fuzzy set to intuitionistic fuzzy set and proposes a novel approach to evaluate system failure probability using intuitionistic fuzzy fault tree analysis with qualitative failure data of system components. The qualitative failure data such as expert opinions are collected as linguistic terms. These linguistic terms are then quantified by triangular intuitionistic fuzzy numbers in form of membership function and non-membership function. Additionally, a method is developed for combining the different opinions of experts. To illustrate the applicability of proposed approach, a case study of the crude oil tank fire and explosion accident is performed. The obtained results are very close to the results from pre-existing approaches which confirm that the proposed approach is a more realistic alternative for the study of system reliability in intuitionistic fuzzy environment when quantitative failure data of system components are not known. To help decision makers for improving the security execution of the crude oil tank system, importance measures including Fussell-Vesely importance and cut sets importance are also executed.
35 citations
TL;DR: In this article, a systematic review of the Natech events literature with single and multi-hazard approaches was developed by searching the Science Direct, Web of Science, and Scopus databases for scientific documents.
Abstract: Natech events (Natural Hazard Triggering Technological Disasters) are industrial accidents caused by natural events such as hurricanes, floods, earthquakes, tsunamis, and so on. In recent decades, the probability of these events occurring has increased, activating the interest of researchers in the study of new methods of risk analysis to prevent and mitigate possible damage to people, the environment, and processing facilities. On the other hand, the concept of multi-hazard is summarized in the combination of two or more threat factors manifested in isolated, simultaneous manner, or by chain reaction, to produce a trigger event of a disaster, where hazardous events can be one or more natural events. Considering that, it is essential to know the progress in risk analysis for Natech events, to identify the gaps for future research. Therefore, in this paper, a systematic review of the Natech events literature with single and multi-hazard approaches was developed. The review was conducted by searching the Science Direct, Web of Science, and Scopus databases for scientific documents. Subsequently, the words Natech and Multi-hazard were taken as keywords, and 208 results were obtained. Then, some management documents were consulted in international organizations to compare academic literature and industrial risk management. In conclusion, the risk analysis methods revised are specific to a particular hazard and apply mainly to earthquakes, floods, and lightning. Regarding a multi-hazard approach, the methods focus on risk mitigation in urban areas without taking into account Natech risk. In the case of industrial risk assessment, some methodologies were found that briefly consider Natech risk in risk assessment processes in industry.
TL;DR: In this article, the authors presented numerical study on the estimation of the near-field and far-field blast waves from Boiling Liquid Expanding Vapour Explosion (BLEVE).
Abstract: So far, the prediction of blast wave generated from the Boiling Liquid Expanding Vapour Explosion (BLEVE) has been already broadly investigated. However, only a few validations of these blast wave prediction models have been made, and some well-established methods are available to predict BLEVE overpressure in the open space only. This paper presents numerical study on the estimation of the near-field and far-field blast waves from BLEVEs. The scale effect is taken into account by conducting two different scale BLEVE simulations. The expansion of pressurized vapour and evaporation of liquid in BLEVE are both modelled by using CFD method. Two approaches are proposed to determine the initial pressure of BLEVE source. The vapour evaporation and liquid flashing are simulated separately in these two approaches. Satisfactory agreement between the CFD simulation results and experimental data is achieved. With the validated CFD model, the results predicted by the proposed approaches can be used to predict explosion loads for better assessment of explosion effects on structures.
TL;DR: The combination of the BN and a Noisy-OR gate is an alternative method for evaluating the reliability of gas pipelines, and this approach can provide a relatively realistic analysis in other evaluation fields because it considers other influencing factors.
Abstract: We propose a method based on the Noisy-OR gate Bayesian network to address cases of insufficient sample data. First, a fault tree model of gas pipelines was established. Mapping this model to the Bayesian network (BN), the failure probability was 0.074 according to a traditional BN and fault tree analysis (FTA). By applying the Noisy-OR gate to determine the conditional probability of related nodes, the failure probability of the system was 0.058. Compared with FTA and the BN, this approach could more precisely determine minimum cut sets and diagnose risky factors. The combination of the BN and a Noisy-OR gate is an alternative method for evaluating the reliability of gas pipelines, and this approach can provide a relatively realistic analysis in other evaluation fields because it considers other influencing factors. The findings of this study can aid decision-making and prevent accidents from occurring.
TL;DR: A dynamic Bayesian network (DBN)-based approach to the probabilistic assessment of the system resilience by incorporating temporal processes of adaption and recovery into the analysis of system functionality is developed.
Abstract: Traditional risk assessment approaches mainly focus on the pre-failure scenarios with certain information. For complex systems, the scope of risk assessment needs to be extended to include the post-failure phase; because the emerging hazards of these systems cannot be wholly identified and are usually highly uncertain. Thus, resilience assessment needs to be investigated. Most of the existing literature quantify resilience based on a system's performance loss caused by disruptions. These studies fail to assess the probability of a system to sustain or restore to a normal operational state after disruptions occur, how this probability changes with time, and how fast the system can be restored. The dynamic and probabilistic characteristics of resilience must be considered in systemic resilience assessment, in which the engineered system, human and organizational factors, and external disruptions are considered. This paper aims to develop a dynamic Bayesian network (DBN)-based approach to the probabilistic assessment of the system resilience by incorporating temporal processes of adaption and recovery into the analysis of system functionality. The proposed method also provides a new way to define resilience in terms of the probability of system functionality change during and after a disruption. A case study on the Chevron refinery accident is used to demonstrate the applicability of the proposed methodology.
TL;DR: After repair and maintenance, the performance of subsea tree system has been significantly improved, and the improvement of the system performance by preventive maintenance is more obvious.
Abstract: Subsea Xmas tree is a vital equipment for offshore oil and gas development. Aiming at the fault mode of subsea Christmas tree system under production conditions, the fault tree of subsea tree system was established, which was transformed into Dynamic Bayesian network, and the reliability and availability of subsea tree system with different repair states are quantitatively analyzed. In this paper, the DBNs are partially verified by the method based on three axes. The results show that the reliability of subsea vertical tree system is slightly higher than that of subsea horizontal tree system. After repair and maintenance, the performance of subsea tree system has been significantly improved, and the improvement of the system performance by preventive maintenance is more obvious. Compared with the perfect repair, the performance of the system with imperfect repair is not significantly reduced. Compared with perfect repair & preventive maintenance, the performance of the system with imperfect repair & preventive maintenance is slightly reduced. In addition, the influence of failure rates and degradation probability on reliability and availability is analyzed. By comparing the influence of failure rates on the system performance of non-maintenance and maintenance, it is found that the change of failure rates has the greatest influence on the reliability and the least influence on the availability of perfect repair & preventive maintenance. By comparing the performance of each component in the subsea tree system, it is found that the failure rates has the most obvious influence on the chock module, and gate valve and tree cap have the most significant influence on the reliability of the system. In order to improve the reliability of subsea tree system, it is necessary to improve the reliability of chock module, gate valve and tree cap.
TL;DR: In this article, three inhibitors (inert gas with 8.0 vol% CO2, 0.25 ǫg/L Mg(OH)2 particles, and 0.5 ǔg/ǫ NH4H2PO4 particles) were prepared.
Abstract: The main risk factors from methane explosion are the associated shock waves, flames, and harmful gases. Inert gases and inhibiting powders are commonly used to prevent and mitigate the damage caused by an explosion. In this study, three inhibitors (inert gas with 8.0 vol% CO2, 0.25 g/L Mg(OH)2 particles, and 0.25 g/L NH4H2PO4 particles) were prepared. Their inhibiting effects on methane explosions with various concentrations of methane were tested in a nearly spherical 20-L explosion vessel. Both single-component inhibitors and gas–particle mixtures can substantially suppress methane explosions with varying degrees of success. However, various inhibitors exhibited distinct reaction mechanisms for methane gas, which indicated that their inhibiting effects for methane explosion varied. To alleviate amplitude, the ranking of single-component inhibitors for both explosion pressure (Pex) and the rate of explosion pressure rise [(dP/dt)ex] was as follows: CO2, NH4H2PO4 particles, and Mg(OH)2 particles. In order of decreasing amplitude, the ranking of gas‒particle mixtures for both Pex and (dP/dt)ex was as follows: CO2–NH4H2PO4 mixture, CO2‒Mg(OH)2 mixture, and pure CO2. Overall, the optimal suppression effect was observed in the system with the CO2–NH4H2PO4 mixture, which exhibited an eminent synergistic effect on methane explosions. The amplitudes of Pex with methane concentrations of 7.0, 9.5, and 11.0 vol% decreased by 37.1%, 42.5%, and 98.6%, respectively, when using the CO2–NH4H2PO4 mixture. In addition, an antagonistic effect was observed with CO2‒Mg(OH)2 mixtures because MgO, which was generated by the thermal decomposition of Mg(OH)2, can chemically react with water vapor and CO2 to produce basic magnesium carbonate (xMgCO3·yMg(OH)2·zH2O), thereby reducing the CO2 concentration in a reaction system. This research revealed the inhibiting effects of gas‒particle mixtures (including CO2, Mg(OH)2 particles, and NH4H2PO4 particles) on methane explosions and provided primary experimental data.
TL;DR: In this article, the effect of methane concentration and ignition position on pressure buildup and flame behavior was investigated in a 1m3 vessel with a top vent to investigate the effect on pressure.
Abstract: Experiments were conducted in a 1 m3 vessel with a top vent to investigate the effect of methane concentration and ignition position on pressure buildup and flame behavior. Three pressure peaks (p1, p2, and Pext) and two types of pressure oscillations (Helmholtz and acoustic oscillations) were observed. The rupture of vent cover results in p1 that is insensitive to methane concentration and ignition position. Owing to the interaction between acoustic wave and the flame, p2 forms in the central and top ignition explosions when the methane–air mixture is near–stoichiometric. When the methane–air mixture is centrally ignited, p2 first increases and then decreases with an increase in the methane concentration. The external explosion-induced Pext is observed only in the bottom ignition explosions with an amplitude of several kilopascals. Under the current experimental conditions, flame–acoustic interaction leads to the most serious explosions in central ignition tests. Methane concentration and ignition position have little effect on the frequency of Helmholtz and acoustic oscillations; however, the Helmholtz oscillation lasts longer and first decreases and then increases as the methane concentration increases for top ignition cases. The ignition position significantly affects the Taylor instability of the flame front resulting from the Helmholtz oscillation.
TL;DR: In this paper, a risk-based methodology for assessing and reducing the vulnerability of atmospheric storage tanks to hurricanes is presented, considering shell buckling, flotation, sliding, and roof sinking as dominant failure modes of storage tanks during hurricanes.
Abstract: Hurricane as one of the most destructive natural hazards can make a devastating impact on the industrial equipment, especially atmospheric storage tanks, leading to the release of stored chemicals and disastrous safety and environmental issues. These catastrophic consequences are caused not only by strong winds but also by the torrential rainfall and inundating floods. The objective of this study is to present a risk-based methodology for assessing and reducing the vulnerability of atmospheric storage tanks to hurricanes. Considering the shell buckling, flotation, sliding, and roof sinking as dominant failure modes of atmospheric storage tanks during hurricanes, Bayesian network (BN) has been employed to combine the failure modes while considering their conditional dependencies. The probability updating feature of the developed BN was employed to indicate that the flood is the most critical hazard during hurricanes while the impact of wind and rainfall cannot be neglected. Extending the developed BN to an influence diagram, the cost-benefit filling of storage tanks with water prior to the advent of hurricanes was shown as a viable measure for reducing the damage probability. The results show that the proposed methodology can be used as an effective decision support tool for assessing and reducing the vulnerability of atmospheric storage tanks to natural hazards.
TL;DR: A CM-BJS-DS model based on the cloud model, the Belief Jensen-Shannon (BJS) divergence and Dempster-Shafer(D-S) evidence theory is proposed to improve the reliability of risk prevention and control based on multi-source sensor data.
Abstract: At present, enterprises have introduced the Internet of Things (IoT) technology to monitor and evaluate the safety status of oil depots, allowing for the collection of a substantial amount of multi-source monitoring data from factories. However, sensor monitoring data is often inaccurate and fuzzy. To improve the reliability of risk prevention and control based on multi-source sensor data, this study proposed a CM-BJS-DS model based on the cloud model (CM), the Belief Jensen-Shannon (BJS) divergence and Dempster-Shafer(D-S) evidence theory. First, the relevant evaluation factors of the accident and their threshold intervals of different risk levels were determined, and the fuzzy cloud membership functions (FCMFs) corresponding to different risk levels were constructed. Then, the sensor monitoring data were processed using the correlation measurement of the FCMF, and basic probability assignments (BPAs) were generated under the risk assessment frame of discernment. Finally, the BPAs were pre-processed by the improved evidence fusion model and the accident risk level was evaluated. Based on the monitoring data, a case study was performed to assess the risk level of vapor cloud explosion (VCE) accidents due to liquid petroleum gas (LPG) tank leaks. The results show that the proposed method presents the following characteristics: (i) The BPAs were constructed based on the monitoring data, which reduced the subjectivity of the construction process; (ii) Compared with single sensors, the multiple sensor fusion evaluation yielded more specific results; (iii) When dealing with highly conflicting evidence, the evaluation results of the proposed method exhibited a higher belief degree. This method can be used as a decision-making tool to detect potential risks and identify critical risk spots to improve the specificity and efficiency of emergency response.
TL;DR: A GIS based methodology is proposed which uses computer aided hazard modelling tools and technical guidelines to model accidents and assesses population vulnerability and a composite risk map is expected to be of help for effective community response, emergency response planning and allocation of medical and support services during emergencies.
Abstract: Chemical accidents in the vicinity of densely populated areas can cause colossal damage. Close proximity of chemical facilities to the general public has been identified as a major issue for increased human exposure in 43% of the accidents investigated by the U.S. Chemical Safety Board (CSB). This emphasises the need for incorporating societal factors in risk assessment to plan actions in order to minimise exposure during accidents. The purpose of this research is to develop a model for the assessment of human vulnerability and risk due to chemical accidents. A GIS based methodology is proposed which uses computer aided hazard modelling tools and technical guidelines to model accidents and assesses population vulnerability. The population vulnerability is determined based on a set of societal indicators derived from relevant research work, expert opinions and suggestions by World Bank. Risk is defined as the probable magnitude of harm to humans and dependent on both the degrees of hazard and vulnerability. A case study is carried out by applying the methodology to Meghnaghat Industrial Area in Bangladesh. Accident scenarios are built and hazard modelling software ALOHA is used to spatially display accident footprints. Vulnerability of population is assessed using data from Bangladesh Bureau of Statistics (BBS) and field survey. The hazard footprints and vulnerability map are superimposed using mapping software ArcGIS to generate a composite risk map. The risk map is used to assess existing land use and recommendations are made for future land use planning. The composite risk map is expected to be of help for effective community response, emergency response planning and allocation of medical and support services during emergencies.
TL;DR: In this paper, a structural equation model was employed to investigate the interactions of safety performance and unsafe behavior for front-line oil workers from the PetroChina Huabei Oilfield Company in China.
Abstract: Safety performance is comprised of two components, safety compliance and safety participation. However, relationships between safety performance and unsafe behavior have not been thoroughly investigated. In this work, scales for safety compliance and safety participation were revised for use in the oil industry, and job burnout scale was developed on the basis of the Maslach Burnout Inventory-General Survey (MBI-GS). A structural equation model was then employed to investigate the interactions of these factors for 238 front-line oil workers from the PetroChina Huabei Oilfield Company in China. From the results, it was determined that workers' unsafe behavior could not be reduced significantly solely from these two dimensions of safety performance. Compared with safety participation, safety compliance was found to have a greater influence on unsafe behavior. However, job burnout was found to be a significant moderator between these two components and unsafe behavior. Furthermore, it was determined that oil workers' occupational psychological health conditions must be taken into account to improve organizational safety management and reduce workers’ unsafe behavior.
TL;DR: In this article, a dynamic approach considering the gas dispersion and behavior evacuation modelling has been proposed to evaluate the consequences of these accidents, a new concept of average probability of mortality (APM) was proposed to quantify the consequences.
Abstract: Accidental releases of toxic gas in the chemical plants have caused significant harm to the exposed occupants. To evaluate the consequences of these accidents, a dynamic approach considering the gas dispersion and behavior evacuation modelling has been proposed in this paper. This approach is applied to a hypothetical scenario including an accidental chlorine release in a chemical plant. CFD technique is utilized to calculate the time-varying concentration filed and evacuation modelling is used to obtain the evacuation routes. The exposure concentrations in the evacuation routes are calculated by using the code of data query. The integrated concentration toxic load model and probit model are used to calculate the probability of mortality of each occupant by using the exposure concentrations. Based on this dynamic approach, a new concept of average probability of mortality (APM) has been proposed to quantify the consequences of different accidental scenarios. The results show that APM decreases when the required detection time decreases or emergency evacuation mode is implemented. The impact of the detection time on APM becomes small as the wind speed increases. The effect of emergency evacuation mode is more obvious when the release occurs in an outdoor space.
TL;DR: Challenges associated with the system design, reliability analysis, testing, deployment as well as operability and maintainability are explored, and then the areas requiring further research and development will be identified.
Abstract: Subsea blowout preventer (BOP) is a safety-related instrumented system that is used in underwater oil drilling to prevent the well to blowout. As oil and gas exploration moves into deeper waters and harsher environments, the setbacks related to reliable functioning of the BOP system and its subsystems remain a major concern for researchers and practitioners. This study aims to systematically review the current state-of-the-art and present a detailed description about some of the recently developed methodologies for through-life management of the BOP system. Challenges associated with the system design, reliability analysis, testing, deployment as well as operability and maintainability are explored, and then the areas requiring further research and development will be identified. A total of 82 documents published since 1980's are critically reviewed and classified according to two proposed frameworks. The first framework categorises the literature based on the depth of water in which the BOP systems operate, with a sub-categorization based on the Macondo disaster. The second framework categorises the literature based on the techniques applied for the reliability analysis of BOP systems, including Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Reliability Block Diagram (RBD), Petri Net (PN), Markov modelling, Bayesian Network (BN), Monte Carlo Simulation (MCS), etc. Our review analysis reveals that the reliability analysis and testing of BOP has received the most attention in the literature, whereas the design, deployment, and operation and maintenance (O&M) of BOPs received the least.
TL;DR: The game theory was applied to analyze roles that government and companies act in the China-Qingdao urban pipeline accident to show that current punishment and incentive systems are incomplete, lacking of the driving force and constraining force for the stakeholders involved in the accident.
Abstract: Urban pipeline accidents are caused by complex social-technical factors, in which urban communities and pipeline systems are involved. Such accidents can thus be investigated from the viewpoint of system engineering. System-Theoretic Accident Model and Processes (STAMP) is a systemic method for safety assessment, which has been adopted in many domains. This approach can provide deep insights of accident causes by considering direct and indirect factors. Meanwhile, competition and cooperation between stakeholders in accidents are observed. Therefore, these parties can also be analyzed with the game theory. That is, stakeholders in STAMP can be regarded as players in game. The aim of this paper is to provide a new insight to analyze urban pipeline accidents by considering both STAMP and game theory. In this paper, we proposed an accident model for urban pipelines, with a case study of China-Qingdao pipeline accident occurred in 2013. We concluded that accident reasons can be investigated in-depth and lessons can be learned from analyzing causal factors by using STAMP. Based on results generated from STAMP, we applied the game theory to analyze roles that government and companies act in the China-Qingdao urban pipeline accident. The results show that current punishment and incentive systems are incomplete, lacking of the driving force and constraining force for the stakeholders involved in the accident.
TL;DR: In this paper, a study aimed to assess crisis management systems of five petrochemical plants in terms of three aspects, including organizational aspects, human aspects, and technical aspects, encompassing 34 items to cover all three aspects at both management and staff levels.
Abstract: Crisis management systems should be assessed and updated in petrochemical industries due to hazards, such as fire and explosion. Successful crisis management systems can protect both personnel and property in the petrochemical industries. The present study aimed to assess crisis management systems of five petrochemical plants in terms of three aspects, including organizational aspects, human aspects, and technical aspects. A questionnaire was designed, encompassing 34 items to cover all three aspects at both management and staff levels. A multi-criteria decision making (MCDM) approach, including the entropy method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), was used to analyze the collected data. The outcomes of the entropy method indicated that organizational and human aspects had the greatest influence on crisis management systems of the plants with 58% and 49% importance at management and staff levels, respectively. The crisis management systems of the investigated plants were ranked and analyzed using the TOPSIS approach. The findings of this study could assist managers and other decision-makers to address the issues of crisis management systems in petrochemical industries.
TL;DR: In this paper, a review of the literature in the domain of safety barriers in the recent decade, and categorizes these studies into barrier theory, barrier engineering and barrier management are presented.
Abstract: Safety barriers include physical and non-physical means in different industries for preventing the occurrences of hazardous events and mitigating the consequences in case they have occurred. After clarifying the relevant terminologies, this article reviews the literature in the domain of safety barriers in the recent decade, and categorizes these studies into barrier theory, barrier engineering and barrier management. Classifications of barriers, performance measures, modeling approaches and data-driven analysis for safety barriers are reviewed as parts of barrier theories. In the engineering section, the research advances are presented in accordance with design for reliability and safety, test and maintenance strategies, responses to dependent failures, and diagnosis and prognosis of degradations. Then, project and process management, human and organizational factors, and standardization and compliance management of safety barriers are summarized. Based on the review of literature, research perspectives on safety barriers for resilience, digital safety, security of barriers, utilizing data, and dealing with intelligence, are highlighted and potential challenges are mentioned. This study is therefore expected to be beneficial to the researchers of system and safety engineering, with systematically streamlining and innovatively categorizing the recent findings and insights.
TL;DR: In this paper, a STE model with the combination of gas transport model, Bayesian inference and slice sampling method is proposed to estimate the source parameters of natural gas leakage in underground utility tunnels.
Abstract: As an effective way to construct and maintain various life pipelines in urban areas and industrial parks, the underground utility tunnel has been developed rapidly in China in recent years. However, the natural gas pipeline leakage in a utility tunnel may cause fire, explosion or other coupling disastrous accidents that could result in fatal consequences. The effective source term estimation (STE) of natural gas leakage can provide technical supports for emergency response during natural gas leakage accidents in utility tunnels. In this paper, a STE model with the combination of gas transport model, Bayesian inference and slice sampling method is proposed to estimate the source parameters of natural gas leakage in underground utility tunnels. The observed data can be integrated into the gas transport model and realize the inversion of natural gas leakage location and release rates. The parameter sensitivity analysis is presented to evaluate the robustness of the proposed model with good practicability, and the gas sensor layouts in the utility tunnel are analyzed and optimized. The spatio-temporal distribution of the leaked gas could be well predicted based on the estimation source parameters by the proposed STE model. The results show that the proposed model is an alternative and effective tool to provide technical supports for loss prevention and mitigation for natural gas leakage accidents in urban utility tunnels.
TL;DR: A fault tree analysis and event tree analysis framework has been developed and the calculated risk has the unit of cost per year which allows the decision makers to discern the benefit of their investment in safety measures and risk mitigation.
Abstract: Fire is the most prevalent accident in natural gas facilities. In order to assess the risk of fire in a gas processing plant, a fault tree analysis (FTA) and event tree analysis (ETA) has been developed in this paper. By utilizing FTA and ETA, the paths leading to an outcome event would be visually demonstrated. The framework was applied to a case study of processing plant in South Pars gas complex. All major underlying causes of fire accident in a gas processing facility determined through a process hazard analysis (PHA). Fuzzy logic has been employed to derive likelihood of basic events in FTA from uncertain opinion of experts. The outcome events in event tree has been simulated by computer model to evaluate their severity. In the proposed methodology the calculated risk has the unit of cost per year which allows the decision makers to discern the benefit of their investment in safety measures and risk mitigation.
TL;DR: In this paper, a semi-vented deflagration chamber with a porous media plate was constructed, taking account of effects of obstacles and porous media materials on the flame quenching process.
Abstract: This article reports experimental investigation of deflagration flame quenching behavior by porous media. In this study, a semi-vented deflagration chamber with a porous media plate was constructed, taking account of effects of obstacles and porous media materials on the flame quenching process. A high speed video camera was used to image the process and behavior of flame propagation, meanwhile, the gas-phase temperatures and ion currents, upstream, within, and downstream of the porous media, were measured using micro-thermocouples and ion probes, respectively. Results show that methane/air deflagration flame can be quenched by the Al2O3 porous media with thickness of 20 mm and pore density of 10 ppi. However, the presence of obstacles along the flame path may lead to significant increase of flame speed, thereby both the decreases of gas-phase temperature and ion current when the flame passes through the porous medium in the case with continuous obstacles are less, eventually the unburnt gases downstream the porous media may be reignited. Compared to Al2O3, Al porous media shows superior flame quenching performance because this metallic material has higher thermal conductivity, which makes combusting flame release more heat to the pore walls and adjoining structures of the porous media.
TL;DR: In this article, the influence of coal dust components on the explosibility of hybrid mixture of methane and coal dust was studied, and the authors concluded that coal dust with lower volatile content has better applicability than Le Chatelier model and Jiang model.
Abstract: In order to study the influences of coal dust components on the explosibility of hybrid mixture of methane and coal dust, four kinds of coal dust with different components were selected in this study. Using the standard 20 L sphere, the maximum explosion pressure, explosion index and lower explosion limits of methane/coal dust mixtures were measured. The results show that the addition of methane to different kinds of coal dust can all clearly increase their maximum explosion pressure and explosion index and decrease their minimum explosion concentration. However, the increase in the maximum explosion pressure and explosion index is more significant for coal dust with lower volatile content, while the decrease in the minimum explosion concentration is more significant for coal dust with higher volatile content. It is concluded that the influence of methane on the explosion severity is more pronounced for coal dust with lower volatile content, but on ignition sensitivity it is more pronounced for coal dust with higher volatile content. Bartknecht model for predicting the lower explosion limits of methane/coal dust mixture has better applicability than Le Chatelier model and Jiang model. Especially, it is more suitable for hybrid mixtures of methane and high volatile coal dust.