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Chemical plants face safety hazards and security threats that may induce catastrophic scenarios. Safety and security barriers are employed widely to protect chemical plants from accidental and intentional undesired events and mitigate consequences. Managing safety and security barriers effectively and economically is a research topic with practical significance. The analysis of undesired event scenarios, including both accidental and intentional adverse scenarios, and assessing associated safety and security barriers are critical regarding cost-efficient barrier maintenance. This study proposes a novel approach for optimizing safety and security barrier maintenance strategy considering economic constraints. This approach consists of three steps: scenario building and barrier identification, barrier modeling, and determining optimal barrier maintenance intervals. In the proposed approach, accident scenarios in terms of safety and physical security are constructed using the extended bow-tie diagrams. After associated safety and security barriers are identified, a system simulation model is developed to conduct barrier modeling based on MATLAB/Simulink simulations, in which the barrier maintenance, the impacts of human and organizational barriers, and the correlations between barriers caused by shared components are considered. Finally, a combination of cost-effectiveness analysis (CEA) and genetic algorithm (GA) is employed to support the decision-making on barrier maintenance optimization. An illustrative case is employed in this study to validate the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

The present study is to point out the outcomes of the Seminar on the Chemical Weapon Convention and Chemical Safety and Security Management for Member States in the Asia Region held by Organization for the Prohibition of Chemical Weapons in Doha, Qatar, in February 2017. The seminar was aimed at supporting chemical safety and security (CSS) management in the chemical industry in Asian countries. Overall goal was to sensitize States Parties to the new approaches that can be adopted in relation to CSS management, with a particular focus on providing assistance to small and medium‐sized enterprises. This article reflects the observations made by keynote speakers via their interaction with participants from Asian State Parties during presentations' questions & answers sessions and following workshops. The article is an attempt to highlight the challenges in security risk assessment and management of chemical facilities and discuss some new trends for further improvements. © 2017 American Institute of Chemical Engineers Process Saf Prog 37: 211–220, 2018 [ABSTRACT FROM AUTHOR]

In the present study, we have introduced a methodology based on graph theory and multicriteria decision analysis for cost-effective fire protection of chemical plants subject to fire-induced domino effects. By modeling domino effects in chemical plants as a directed graph, the graph centrality measures such as out-closeness and betweenness scores can be used to identify the installations playing a key role in initiating and propagating potential domino effects. It is demonstrated that active fire protection of installations with the highest out-closeness score and passive fire protection of installations with the highest betweenness score are the most effective strategies for reducing the vulnerability of chemical plants to fire-induced domino effects. We have employed a dynamic graph analysis to investigate the impact of both the availability and the degradation of fire protection measures over time on the vulnerability of chemical plants. The results obtained from the graph analysis can further be prioritized using multicriteria decision analysis techniques such as the method of reference point to find the most cost-effective fire protection strategy. [ABSTRACT FROM AUTHOR]

Land-use planning (LUP) has widely been employed as a protective safety measure in risk management of major hazard installations such as chemical plants. In the European Union countries, a majority of relevant work over the past years has been inspired by the Seveso II Directive. The inclusion of LUP in the Seveso II Directive has been with the aim of mitigating off-site damage of major accidents on public via setting criteria for (i) the identification of the location and layout of new installations, (ii) the development of existing installations, and (iii) the land developments in the vicinity of existing installations. We, in the present study, have proposed a methodology based on Bayesian network (BN) for cost-effective allocation of safety measures in chemical plants so that both internal and external risks could effectively be mitigated, particularly in compliance with the requirements of LUP. We first employed BN to calculate risks, and then extended the BN to a limited memory influence diagram using additional decision and utility nodes so that it can be used for multi-attribute decision analysis. The development and application of the methodology have been illustrated via fireproofing of a hypothetical fuel storage plant. [ABSTRACT FROM AUTHOR]

• The optimal allocation of emergency forces in front-line emergency response departments is studied. • The impact of emergency response on the time to failure of installations in the event of a fire accident is considered in the allocation. • A timed colored hybrid Petri-net (TCHPN) approach is proposed to model the emergency response process and analyze the allocation of emergency response forces. • A case study of the emergency response to a tank fire illustrates the proposed approach. Fire is one of the main accident scenarios occurring in chemical and process plants, and it can lead to domino effects due to thermal radiation. Emergency response is necessary to prevent fire escalation, in addition to safety barriers. In major industrial fire accidents, backup is usually required in emergency response, due to the lack of emergency response capacity of a single emergency response department. A method addressing the optimal allocation of emergency response forces, specifically considering the front-line departments, is developed in the present study. The emergency response of the front-line departments can reduce the thermal radiation received by the equipment adjacent to the primary fire and thus prolong the time to failure of the equipment, such that the backups have more time to get to the fire scene. The allocation analysis of emergency response teams is carried out considering the dynamic ttf of an adjacent equipment item resulting from the change in time of the thermal radiation received. A timed colored hybrid Petri-net (TCHPN) approach is proposed to model the emergency response process. The probability of preventing fire escalation is obtained from the TCHPN model and the optimal allocation of firefighting forces is determined. A case study illustrates the proposed approach, two scenarios are compared and results show that if a request for backup can be issued immediately according to the fire state, fewer emergency forces can be deployed on the front line department, such as the reduction from 6 emergency response teams to 3 teams to maintain the success probability of 0.91. The influence of other factors such as the position of fire departments and the layout of tanks on the allocation of emergency forces is also discussed. [ABSTRACT FROM AUTHOR]

Land use planning (LUP) as an effective and crucial safety measure has widely been employed by safety experts and decision makers to mitigate off-site risks posed by major accidents. Accordingly, the concept of LUP in chemical plants has traditionally been considered from two perspectives: (i) land developments around existing chemical plants considering potential off-site risks posed by major accidents and (ii) development of existing chemical plants considering nearby land developments and the level of additional off-site risks the land developments would be exposed to. However, the attempts made to design chemical plants with regard to LUP requirements have been few, most of which have neglected the role of domino effects in risk analysis of major accidents. To overcome the limitations of previous work, first, we developed a Bayesian network methodology to calculate both on-site and off-site risks of major accidents while taking domino effects into account. Second, we combined the results of risk analysis with Analytic Hierarchical Process to design an optimal layout for which the levels of on-site and off-site risks would be minimum. [ABSTRACT FROM AUTHOR]

Process- and chemical plants may constitute a critical target for a terrorist attack. In the present study, the analysis of industrial accidents induced by intentional acts of interference is carried out focusing on accident chains triggered by attacks with home-made (improvised) explosives. The effects of blast waves caused by improvised explosive devices are compared with those expected from a net equivalent charge of TNT by using a specific methodology for the assessment of stand-off distances. It is demonstrated that a home-made explosive device has a TNT efficiency comprised between 0.2 and 0.5. The model was applied to a case study, demonstrating the potentiality of improvised explosives in causing accident escalation sequences and severe effects on population and assets. The analysis of the case-study also allowed obtaining suggestions for an adequate security management. [ABSTRACT FROM AUTHOR]

Dealing with large quantities of flammable and explosive materials, usually at high-pressure high-temperature conditions, makes process plants very vulnerable to cascading effects compared with other infrastructures. The combination of the extremely low frequency of cascading effects and the high complexity and interdependencies of process plants makes risk assessment and vulnerability analysis of process plants very challenging in the context of such events. In the present study, cascading effects were represented as a directed graph; accordingly, the efficacy of a set of graph metrics and measurements was examined in both unit and plant-wide vulnerability analysis of process plants. We demonstrated that vertex-level closeness and betweenness can be used in the unit vulnerability analysis of process plants for the identification of critical units within a process plant. Furthermore, the graph-level closeness metric can be used in the plant-wide vulnerability analysis for the identification of the most vulnerable plant layout with respect to the escalation of cascading effects. Furthermore, the results from the application of the graph metrics have been verified using a Bayesian network methodology. [ABSTRACT FROM AUTHOR]

Abstract: The presented Multi-plant Collaboration Model uses game theory to evaluate different strategic cross-plant precaution collaboration situations. The model first assumes prevention management''s perceptions as a premise to take cross-plant prevention decisions. Second, it employs information from the different plants and aggregates the data to determine possible financial collaboration benefits within the entire industrial area. By doing so, an application of the model by a suggested independent supra-plant council may enhance and realize cross-corporation precaution in chemical clusters. [Copyright &y& Elsevier]

Industrial sectors are nowadays extensively confronted with anti-terrorism security. Chemical plants, in particular, face the necessity for increased terrorism prevention. This article discusses organizational security measures as they relate to chemical facilities in general, and to four chemical enterprises in particular. Furthermore, a general overview (used in the chemical industry as well as in other industrial sectors) of physical security components used to fight terrorism is provided. Four security hypotheses based on professional and academic literature and on internal documents with reference to the chemical industry are validated via in-depth interviews carried out in four chemical multinationals. Furthermore, recommendations are given to consider when striving for improvement in installing and continuously improving security measures in the chemicals sector. [ABSTRACT FROM AUTHOR]

Abstract: Every company situated within a chemical cluster faces important security risks from neighbouring companies. Investing in reciprocal security preventive measures is therefore necessary to avoid major accidents. These investments do not, however, provide a direct return on investment for the investor-company and thus plants are hesitative to invest. Moreover, there is likelihood that even if a company has fully invested in reciprocal security prevention, its neighbour has not, and as a result the company can experience a major accident caused by an initial (minor or major) accident that occurred in an adjacent chemical enterprise. In this article we employ a game-theoretic approach to interpret and model behaviour of two neighbouring chemical plants while negotiating and deciding on reciprocal security prevention investments. [Copyright &y& Elsevier]

Every company situated within a chemical cluster faces domino effect risks, whose magnitude depends on every company''s own risk management strategies and on those of all others. Preventing domino effects is therefore very important to avoid catastrophes in the chemical process industry. Given that chemical companies are interlinked by domino effect accident links, there is some likelihood that even if certain companies fully invest in domino effects prevention measures, they can nonetheless experience an external domino effect caused by an accident which occurred in another chemical enterprise of the cluster. In this article a game-theoretic approach to interpret and model behaviour of chemical plants within chemical clusters while negotiating and deciding on domino effects prevention investments is employed. [Copyright &y& Elsevier]

• A multi-agent method is developed for modeling multi-hazard in chemical plants. • The method is based on dynamic graph and Monte Carlo simulation (DGMC). • The spatial-temporal evolution of hazards arising from toxic release are considered. • The vulnerability of humans and installations subject to multi-hazard can be obtained. • Different personal protective equipment may be formulated for different people. In the chemical industry, multi-hazard (toxic, flammable, and explosive) materials such as acrylonitrile are stored, transported, and processed in large quantities. A release of multi-hazard materials can simultaneously or sequentially lead to acute toxicity, fire and explosion. The spatial-temporal evolution of hazards may also result in cascading effects. In this study, a dynamic methodology called "Dynamic Graph Monte Carlo" (DGMC) is developed to model the evolution of multi-hazard accident scenarios and assess the vulnerability of humans and installations exposed to such hazards. In the DGMC model, chemical plants are modeled as a multi-agent system with three kinds of agents: hazardous installations, ignition sources, and humans while considering the uncertainties and interdependencies among the agents and their impacts on the evolution of hazards and possible escalation effects. A case study is analyzed using the DGMC methodology, demonstrating that the risk can be underestimated if the spatial-temporal evolution of multi-hazard scenarios is neglected. Vapor cloud explosion (VCEs) may lead to more severe damage than fire, and the safety distances which are implemented only based on fire hazards are not sufficient to prevent from the damage of VCEs. Image, graphical abstract [ABSTRACT FROM AUTHOR]

• The research on modeling and managing of domino effects were reviewed. • The methods for modeling and managing domino effects were classified and analyzed. • The current research trends and the needs of the future were discussed. • This study considered domino effects caused by accident events, Natechs and attacks. Recent catastrophic accidents in China and the USA urge and justify a thorough study on current & future research trends in the development of modeling methods and protection strategies for prevention and mitigation of large-scale escalating events or so-called domino effects in the process and chemical industries. This paper firstly provides an overview of what constitutes domino effects based on the definition and features, characterizing domino effect studies according to different research issues and approaches. The modeling approaches are grouped into three types while the protection strategies are divided into five categories, followed by detailed descriptions of representative modeling approaches and management strategies in chemical plants and clusters. The current research trends in this field are obtained based on the analysis of research work on domino effects caused by accidental events, natural events, and intentional attacks over a period of the past 30 years. A comparison analysis is conducted for the current modeling approaches and management strategies to pose their applications. Finally, this paper offers future research directions and identifies critical challenges in the field, aiming at improving the safety and security of chemical industrial areas so as to prevent and mitigate domino effects. [ABSTRACT FROM AUTHOR]

• Review of knowledge development on complex domino accident processes. • Research is dominated by quantitative risk analyses, and models to calculate probabilities. • Research is closely related to political, and private decision making. • Research on barrier quality and quality of risk management is in its infancy. • Research on initiating scenarios as a starting point for domino-effects is necessary. Major accidents in Western countries, receiving a lot of media attention in the 1970s, are starting point for research into internal and external domino effects in the chemical and petrochemical sectors and clusters. Initially, these reports are published by government institutions and government-related research centres. With the upcoming quantitative risk analyses in the 1970s and 1980s, the so-called öcoloured books', published in the Netherlands, play a prominent role in quantifying these domino effects. Since the mid 1990s, the second European Seveso Directive encourages scientific research on domino effects, shown in substantially growth of academic publications on the topic. Research in Western countries is dominated by risk assessments, probabilities, and failure mechanisms are calculated for the complex phenomenon of domino effects and its consequences. Previous works are closely related to political, official and private decision-making. A transition towards risk management is still in its infancy. A future transition is necessary to understand initial scenarios as starting points for domino effects. In India a wake-up call for domino effects occurs in the mid-1990s. Chinese publications on domino effects in the international scientific press appear from the mid-2000s onwards. Due to a rapid industrialisation, the numbers in China country are overwhelming, versus chemical companies, as versus of many major accidents in this sector. This article will discuss results of research on domino effects, conducted in the period 1966–2018, as well as major determinants of these accident processes. Also present, and future transition in this research domain will be discussed. [ABSTRACT FROM AUTHOR]

The propagation of fire in chemical plants – also known as fire domino effects - largely depends on the performance of add-on passive and active protection systems such as sprinkler systems, water deluge systems, emergency shut down and emergency blow down systems, fireproofing, and emergency response. Although such safety barriers are widely employed to prevent or delay the initiation or escalation of fire domino effects, their inclusion in the modeling and risk assessment of fire domino effects has hardly been taken into account. In the present study, the dynamic evolution of fire protection systems has been investigated qualitatively using event tree analysis. To quantify the temporal changes and their impact on the escalation of fire domino effects, a dynamic Bayesian network methodology has been developed. The application of the methodology has been demonstrated using an illustrative case study, considering a variety of fire scenarios, target installations, and firefighting systems. [ABSTRACT FROM AUTHOR]

• The paper provides a systematic review of research work on safety barriers in the chemical process industries. • A novel classification of safety barriers, based on the identification and management of performance indicators, is proposed. • Safety barrier functions are identified and illustrated using the resilience engineering concepts. • The roadmap for future studies to develop integrated management of safety and security barriers for assurance of the resilience of chemical plants is suggested. Barriers are used in various forms to assure the safety of chemical plants. A deep understanding of the literature related to safety barriers is essential to tackle the challenges in improving their design and management. This paper first provides an overview of the history of the development of the safety barrier concept. Subsequently, this paper elaborates a systematic review of the definition, classification, evaluation, performance assessment, and management of safety barriers in the chemical process industries. Based on the literature review, this study proposes a practical classification of safety barriers benefiting the identification of performance indicators and the collection of indicator-related data for safety barriers. The safety barrier functions are extended and illustrated by involving the resilience concept. Performance assessment criteria are proposed corresponding to the adaptability and recoverability of the safety barriers. Finally, the management of safety barriers is discussed. The roadmap for future studies to develop integrated management of safety and security barriers to ensure the resilience of chemical plants is suggested. [ABSTRACT FROM AUTHOR]

The propagation of fire-induced domino effects in chemical plants largely depends on the primary fire scenario, on separation distances between the units, and on the presence of fire protection barriers. Passive and active safety barriers are widely employed to prevent or delay the initiation or propagation of domino effects. In the present study, a methodology has been developed based on Bayesian network to account for the impact of such safety barriers on the propagation of fire domino scenarios. The Bayesian network has been extended to a limited memory influence diagram in order to identify a cost-effective allocation of additional safety barriers to further mitigate the fire propagation. The application of the methodology has been demonstrated using a chemical tank farm. The results are in good agreement with the results of a graph theoretic approach developed in a previous study, proving the reliability of the developed methodology in cost-effective protection of process plants. [ABSTRACT FROM AUTHOR]

The threat originating from deliberate attacks against process and chemical sites where relevant quantities of hazardous substances are stored or processed is a credible one, as confirmed by the attacks carried out in France in the summer of 2015. Although such chemical sites implement multiple layers of protection to address safety-related accidents, they often get behind with providing adequate attention and resources to the protection of assets against external adversaries or, in other words, terrorist threats. The lack of a consolidated practice in the risk-informed implementation of security countermeasures goes hand in hand with the existence of very few rigorous approaches to the effectiveness assessment of security systems, and in particular of physical protection systems (PPSs). The present study addresses the issue of quantitatively assessing the effectiveness of physical security systems adopted to protect process and storage facilities, recognized as high-consequence loss physical assets. To this purpose, the security functions of PPSs were analyzed to guide the selection of performance parameters. Experts from the industry were involved to identify variables and influencing factors relevant to the successful accomplishment of security functions. Experience-based judgments on performance, to be expressed in terms of probabilistic estimates, were also obtained. An insight into the belief that experts hold on the probability of PPSs effectively preventing the success of an external attack and in the identification of critical elements was obtained. The application of the results to the quantitative assessment of the contribution of security controls in reducing vulnerability was also addressed. [ABSTRACT FROM AUTHOR]