The domino effect in chemical industrial parks represents a complex phenomenon where accidents such as leaks, fires, and explosions can occur either simultaneously or in sequence. The progression of domino accidents is highly uncertain, making it difficult to anticipate the spatial-temporal development of such accidents. This paper presents a model that aims to forecast the evolution of domino effects by considering the critical thermal dose and utilizing the Probit model to assess the escalation of incidents caused by thermal radiation and overpressure. To tackle the complexities associated with multiple installations, high order, and various accident types in modeling domino effect accidents, the model incorporates Monte Carlo simulation methods. The model validation and case studies have demonstrated the effectiveness of this approach in simulating the progression of domino accidents initiated by a range of primary accidents. This approach enables the prediction of potential accident chains and the dynamic failure probability of hazardous installations, including the identification of the initial installation likely to fail. The insights gained from this research offer guidance for the prevention and mitigation of the domino effect in chemical accidents.

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Seaport infrastructure requires considerable resources and time for a full recovery from accidents caused by hazardous cargo. Despite their severity, the risk to seaport infrastructure from hazardous cargo operations has been insufficiently explored. This study aims to fill that gap by examining the risks to seaport infrastructure from the complex effects of hazardous cargo operations. It draws on literature, incident reports, and expert consultations to identify comprehensive risk factors and their interconnections. The study employs expert judgments alongside logistic regression to develop Conditional Probability Tables (CPTs) and conducts a risk analysis using Bayesian networks (BN). Our findings indicate that, under typical operating conditions, fire and explosion, corrosion, and improper handling are the most significant contributors to seaport infrastructure risk with probabilities of 8.73 %, 5.88 %, and 5.61 % respectively. Inverse propagation indicates that the contribution of improper handling and corrosion is enhanced by 153 % and 96 % respectively towards the increased risk. A sensitivity analysis was carried out to pinpoint critical risk factors. Based on these insights, the study suggests practical measures like the use of tracking and monitoring systems along with third-party audits for effective handling, augmented and virtual reality for advanced training, and automation technology for reduced human roles to subside risks to seaport infrastructure and promote uninterrupted operations.

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Risk is a complex and multi-faceted concept defined and addressed differently across disciplines. Recent years have seen a growing recognition of the need for a more comprehensive and integrated risk perspective combining insights from various disciplines. However, those works have rarely been analyzed in literature reviews. This article explores the possible way of advancing how we assess and manage risks by reviewing the theories, approaches, models, and other fundamental aspects of different disciplines relevant to risk concepts. Additionally, we compare the origins, connections, and differences between state-of-the-art risk science and risk concept research in various disciplines. Some suggestions and future directions are provided for improving risk assessment. This paper helps to deepen the understanding of the risk concept and advance the development of the risk management arena.@en

In the built environment, often too much focus is put on compliance instead of seeking the optimal fire-safety solution for the building. Because of a lack of tangible incentives for building owners, the benefits of implementing fire safety measures and their societal contribution are often not recognized and therefore, not considered. By means of a literature review and a survey, we have indicated necessary fire-safety related attributes and tool features and analyzed the currently available fire risk assessment tools. This study shows that a limited number of these tools can provide a partial fire risk analysis of a building. A total of 26 tools were found. No tools were found that included all the identified fire consequence-related attributes to ensure fire-safe buildings. However, we did identify 11 tools that have the potential to assess between 32 % and 52 % of the found attributes of building fire safety. To stimulate the development of such tools, this paper provides 12 factors by which to assess fire risk assessment tools – quantifying the overall ‘quality’ of the assessment tool – which can incentivize industry to refine the existing ones with enhanced predictability of the potential consequences of fire incidents. @en

Ammonia is a promising fuel for decarbonizing the shipping industry, but its safety compared to traditional maritime fossil fuels remains questionable. As more projects explore ammonia-fueled vessels, safety concerns, particularly the acute toxicity and risks of ammonia release, are paramount. This research focused on the effects of accidental ammonia releases during ship-to-ship collisions, affecting ammonia tank integrity. We examined various release scenarios, considering factors like tank types and locations, breach sizes and positions, weather conditions, and dispersion patterns, using PHAST software for modeling. Results indicated that semipressurized tanks pose greater health risks on human health than fully refrigerated ones. Underwater releases are less hazardous, as a significant amount of ammonia dissolves before surfacing. Mitigation efforts, such as water curtains and containment basins, were evaluated for their effectiveness in minimizing the impact of ammonia releases. These measures significantly reduce risks to nearby populations but are less effective for crew safety onboard. This underscores the challenge of ensuring onboard safety in ammonia-fueled vessels, highlighting the need for innovative and effective safety design.

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Emergency response is a procedural safety barrier of paramount importance for the mitigation of fire scenarios and the prevention of escalation. However, in Natech scenarios, emergency response may be affected by the natural event impacting the site. Indeed, when contrasting Natech accidents, emergency responders have to face both the natural event and the cascading technological scenario. Despite the criticality of the issue, limited attention was devoted to date to the analysis of emergency response in cascading sequences triggered by natural events. The present study provides a novel and technically sound methodology to assess the performance of emergency response and the required intervention time in Natech scenarios. An expert survey combined with a Bayesian Network model was used to assess the performance of the emergency response. The routing and setup phases were identified as those mostly affected by natural events. Monte Carlo simulations were used to obtain baseline data and specific probability distributions for the time required to carry out the emergency response considering the factors that may hinder the response during natural events. In Natech accidents, the time for effective mitigation resulted higher of at least a factor 2 with respect to that expected in the case of conventional accidents. The methodology developed may be used to support the improvement of the emergency management of Natech scenarios, allowing for a detailed definition of site-specific emergency response plans. Moreover, the results may be used to provide a more accurate assessment of the fire-driven escalation probability in Natech events.

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Ammonia is a promising fuel for marine propulsion and generation, yet its acute toxicity and associated safety challenges necessitate careful consideration. Current regulations recognize the hazards of ammonia, introducing numerous technical safety measures in response. However, the effectiveness of these measures in ensuring acceptable risk levels for future vessels remains to be fully assessed. This study estimates the risk level onboard ammonia-powered ships, identifying the aspects with the largest and controllable influence on it. Three hypothetical concepts of ammonia fuel supply were developed in this study on an example tanker vessel and analyzed using the quantitative risk assessment (QRA) methodology. The obtained risk profiles were evaluated against the risks by an equivalent liquefied natural gas-fueled system, serving as a benchmark. The results demonstrate that ammonia-fueled ships exhibit individual risk levels for engineering crew with periodic duties in fuel preparation rooms (FPR), or similar compartments, which are 1–1.5 orders of magnitude higher than those observed for a conventional gas-fueled alternative. An analogous increase has been noted for the public potentially present onboard or in proximity. The study underscores the importance of managing human-machine interactions, enhancing the reliability of supply systems, and managing the systems’ complexity to mitigate risks in FPRs. Regarding public safety, the analysis highlights new risk mechanisms introduced by ammonia and examines how storage conditions affect exposure levels. By offering a detailed QRA framework, this research contributes to the development of effective risk management strategies for ammonia-powered ships.

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Domino effects are high-impact low-probability events that can have catastrophic consequences. To prevent and to reduce risks related to such events, safety barriers (SBs) are crucial. However, the initiation, propagation, and stopping processes of domino effects are characterized with complexity and uncertainties and hence they are unpredictable. This makes it challenging to allocate SBs based on predicted probabilities. In this study, a multi-objective optimization model which integrates graph theory with Non-dominated Sorting Genetic Algorithm II (NSGA-II) was proposed to allocate add-on SBs effectively. Graph metrics were used to quantify the escalation risks related to storage tanks and to optimize the allocation of add-on SBs, thereby minimizing the consequences of a domino effect under a budget constraint. The results of the case study demonstrate great efficiency in finding globally optimal strategies with a largest reduction of 94.3% in the out-closeness score due to the implementation of add-on SBs, allowing decision-makers to choose the most preferable investment strategy in face of domino effect risk. Our study therefore provides a novel approach to achieve an optimal allocation of add-on SBs globally and can be useful in preventing domino effects in large-scale chemical clusters equipped with a large number of storage tanks.

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System resilience denotes the capacity to uphold desired system performance in the face of disruptions. Evaluating the resilience of a process system necessitates a thorough consideration of the intricate interplay between its components and the pivotal role of process parameters in reflecting the repercussions of disruptions on the system. This paper introduces an integrated methodology that takes into account component interactions and leverages process data for the resilience assessment of a process system. The proposed methodology comprises four key components: system structure analysis, disruption impacts analysis, process simulation, and resilience assessment. Firstly, the system structure is meticulously scrutinized using a P-graph model. This analysis encompasses the assessment of the significance and interplay of components, as well as the evaluation of how component failures affect the system's overall processes. Secondly, a Markov model is devised to examine the state transition process of components and quantifies the maintenance time needed for failed components. Subsequently, a simulation model is formulated to acquire real-time process parameters in the presence of disruptive events. Finally, the system's performance response function (PRF) is derived from the normalization of these process parameters. Building upon this foundation, a resilience assessment is conducted with a focus on the PRF. To illustrate the effectiveness of this methodology, an LNG terminal system is employed as an exemplar.

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Fire accidents in oil tank farms can trigger domino effects, leading to multiple tank fires with catastrophic consequences. Preventing losses in large-scale tank farms requires a dynamic assessment of fire-induced domino accidents. Existing research often focuses on calculating the time to failure (TTF) of storage tanks but overlooks the influence of failure modes. This study develops numerical models to explore failure modes of oil storage tanks with uniform and stepwise walls exposed to thermal radiation. Factors such as the flame heights of combustion tank, adjacent spacings, wall thickness, and tank volumes are considered. The numerical model employs a solid double-layer flame model to determine thermal radiation intensity and temperature, followed by a dynamic stress–strain and buckling analysis to obtain time to buckling (TTB) and time to yielding (TTY). If TTB < TTY, the failure model is buckling; otherwise, the failure model is yielding. Results indicate that failure modes in nonuniform thermal fields include buckling and yielding, with stepwise walls favoring buckling and uniform walls favoring yielding. When the wall thickness is below the critical value, failure is yielding; otherwise, it is buckling. These findings support risk management and emergency response for fire-induced domino effects in oil tank farms.

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Chemical process systems are becoming more automated and complex, which leads to increased interaction and interdependence between the human and technical elements of process systems. This urges the need for updating the safety assessment method by treating “safety” as an emergent property of a system. Uncertainty comes together with complexity. To enhance system ability of dealing with uncertain disruptions, this paper proposes a quantitative resilience assessment method by modeling the failure propagation (initiated by a disruption) across the functional units of a system. The Functional Resonance Analysis Method (FRAM) is utilized to model the system operation to represent the relationship among its function units and to consider the interactions among human-technical factors. Then, a Cascading Failure Propagation Model (CFPM) is developed to quantify the fault propagation process and reflect the system functionality changes over time for resilience assessment. The proposed method is applied to a propane-feeding control system. The results show that it can help practitioners understand the process of fault propagation and risk increase, identify potential ways to design a more resilient system to respond to uncertain disruptions/attacks, and provide a real-time dynamic resilience profile to support decision-making.

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This paper presents a systematic literature review of risk assessment methods in the chemical process industry (CPI), focusing on process safety, process security, and resilience. We analyzed peer-reviewed articles from 2000 to 2022 using the PRISMA methodology and identified twelve predominant methods. Our findings reveal a shift towards dynamic, systemic-based assessments like the Functional Resonance Analysis Method (FRAM) and System-Theoretic Accident Model and Processes (STAMP). These methods are particularly effective at capturing the complexities of sociotechnical systems in the CPI. However, a significant observation from our review is the limited emphasis on the resilience paradigm within many existing methods when addressing both process safety and process security risks, which is crucial for preventing and recovering from disruptions. Given the evolving challenges in system safety and security threats, there is an urgent need for holistic methods that integrate process safety, process security, and resilience. Our review highlights the opportunity for further research to better prepare the industry for future challenges, ensuring safer, more secure, reliable, and resilient operations.

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Recent increases in climate-induced natural disasters have amplified the risk of Natech (natural hazard-triggered technological) accidents, particularly in the chemical industry. These emergencies, characterized by their urgency and resource constraints, pose significant challenges for emergency planning. The Functional Resonance Analysis Method (FRAM) offers a systematic approach to enhance emergency response strategies. This study introduces a FRAM-based methodology specifically designed for fuel storage tank farms, structured into four critical stages: understanding, designing, analyzing, and enhancing the response process. It promotes a cycle of continuous improvement. A case study on a seismic Natech incident at a fuel storage facility demonstrates the methodology's effectiveness and its potential to boost the resilience of emergency response systems against Natech challenges.

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Major accidents in the chemical process industry occur with low frequency but may lead to severe damages affecting a myriad of stakeholders. Managing major accident risks of chemical industrial systems is regulated in the Seveso Directive of the European Union. However, the conventional risk assessment mainly focuses on the objective aspects of risks and lacks in incorporating public concerns and context-related issues. Aiming to overcome this limitation and enhance the public’s engagement and trust in risk assessment and management, the present study built an integrated risk index for ranking risks considering both technical aspects and societal concerns. A hypothetical case-study is used to demonstrate the application of the proposed risk index. At last, the outcomes of using the integrated risk index and the conventional risk assessment approach are compared and discussed.@en

Chemical facilities face threats from accidental and intentional events, including the rising concern of cyber-physical (C2P) attacks in the digitized industrial control system era. Addressing major accident risks from safety hazards and C2P attacks requires an immediate unified framework for safety and security barrier management. This study presents a systematic risk-based approach to integrate conventional safety risks with emerging C2P attack risks. Adverse scenarios are identified, integrated into an attack-tree-bow-tie diagram, and modelled using a Bayesian network (BN). A vulnerability assessment model is developed to quantify industrial control system vulnerability to C2P attacks, considering uncertainties in attackers' knowledge levels. Monte Carlo simulations are used to handle uncertainty propagation in risk assessment, allowing the use of probability distributions for BN root nodes. Sensitivity analysis identifies critical factors/events, guiding the proposal of candidate strategies for barrier improvements. Combining cost-effectiveness analysis with a risk matrix yields the optimal strategy for safety and security barrier enhancements based on risk estimations. A hypothetical case study demonstrates the proposed approach's effectiveness in integrated safety and security barrier management, considering security vulnerability patching and safety barrier maintenance scheduling from a cost-effective perspective.@en

To maintain continuous production, chemical plant operators may ignore faults or handle faults online rather than shutting down process systems. However, interaction and interdependence links between components in a digitalized process system are substantial. Thus, faults will be propagated to downstream nodes, potentially leading to risk accumulation and major accidents. However, limited attention has been paid to this type of risk. To model the risk accumulation process, a dynamic risk assessment method is proposed by integrating the system-theoretic accident model and process approach (STAMP) and the cascading failure propagation model (CFPM). Firstly, STAMP is used to model and analyze the system safety of a process system. Two CFPMs are then proposed to measure risk accumulation under two different engineering situations. The proposed method is applied to the Chevron Richmond refinery crude unit and its associated upstream process. The results show that the proposed approach can effectively quantify the process of risk accumulation. This method can generate a real-time dynamic risk profile to support auxiliary decision-making.

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The estimation of failure probability is challenging in hydrogen embrittlement in steel pipelines due to the complexity of the synergistic effect of multiple factors. The present study proposed a hybrid methodology to estimate the failure probability of steel pipelines due to hydrogen embrittlement. The methodology integrates the fault tree analysis with a fuzzy comprehensive evaluation. Fault tree analysis captures the logical relationships between influencing indicators to develop a new assessment model of hydrogen embrittlement in steel pipelines. An improved fuzzy fault tree analysis method was proposed to process aleatoric and epistemic uncertainties to estimate the probability of each basic event due to the difficulty in obtaining the actual probabilities. The failure probability of blended hydrogen natural gas pipelines was estimated by considering the correlation of events. A case study demonstrated the applicability of the proposed method. Maintenance measures can be implemented according to the evaluation results to ensure pipeline safety.

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Fire-induced domino effect is one of the main threats to hazardous material storage tanks, and many attempts have been conducted to assess the vulnerability of storage tanks exposed to fire to evaluate domino effect risk. However, past research ignored the influence of wind load on the thermal buckling behavior of storage tanks exposed to fire, which may underestimate the risk of exposed tanks. This paper thus conducts a numerical simulation of the thermal buckling behavior of steel vertical dome storage tanks under the synergistic effect of static wind loads and thermal effects. The effects of wind parameters and heat radiation parameters on the thermal post-buckling behavior and the time to failure (ttf) of storage tanks are investigated to analyze the synergistic effects of fire and wind loads. By comparing the circumferential and meridional stresses before and after the thermal post-buckling stage, it is found that under the disturbing effect of the positive wind pressure load, the thermal post-buckling of the tanks on downwind occurs earlier and more severe. Besides, the effects of wind angle, fire location height, and diameter on buckling damage were investigated. The comparative analysis of different scenarios shows that the tanks in the windy scenario are more prone to thermal post-buckling, and the deformation is intensified, with an increased likelihood of failure.

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This research explores how process safety and process security risk management methods may be integrated into a unified framework, thereby considering the resilience engineering paradigm. Employing a systematic literature review and expert surveys with industrial practitioners alongside representatives from key regulatory bodies to understand the complexities and opportunities of such integration. The interactions that result from a mixed-method study ensure the gaining of insights into the practical challenges and opportunities of integration in diverse operational and regulatory environments. Utilizing Microsoft Forms analytics tools and ATLAS.ti for qualitative analysis, the research identifies patterns and conditions, as well as the context, which is pivotal for constructing a comprehensive, adaptable risk management framework. This paper introduces a novel, holistic risk management perspective, advocating for the amalgamation of process safety and process security within the chemical industry, adopting the System-Theoretic Accident Model and Processes (STAMP) model underscored by resilience principles.

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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.@en