Chemical Process Systems (CPSs) exhibit complex characteristics and inherent dangers that can lead to serious accidents when disrupted. Accurate quantification and assessment of system resilience are crucial for effectively responding to potential undesired events. To address this, we propose a multiparametric resilience assessment methodology for CPSs that considers system dynamics and Independent Protection Layers (IPLs). This method integrates multiple CPS parameters using the Best Worst Method (BWM) to establish a comprehensive performance indicator. A dynamic simulation model incorporating IPLs is developed to monitor real-time changes in system parameters under disruptive influences. Additionally, a resilience metric is introduced, utilizing time-varying parameters to quantify system resilience under various disruptions. A case study involving a two-column pressure-swing distillation process with top recycling, designed to separate a minimum-boiling azeotrope of tetrahydrofuran and water, demonstrates the applicability of this method to complex CPSs. The results indicate that, compared to traditional resilience assessment methods based on reliability, the proposed approach provides time-dependent process parameters, reducing the uncertainty of reliability data. Furthermore, by considering IPLs, this method offers valuable decision support for the design and optimization of these protective layers.

The evolving energy landscape in Europe is showing concrete signals that hydrogen will play a central role in the energy transition scenario. In this light, a report of the European Hydrogen Backbone pinpoints no less than forty existing projects focused on the commissioning of several kilometers of hydrogen pipelines in the following years. Hence, ensuring a safe operability of these systems represents a topic worthy of investigation and marked by significant challenges, especially given the unique properties that make hydrogen a potentially hazardous substance. Established techniques may prove helpful in supporting the development of dedicated prevention and mitigation strategies for hydrogen systems. Among these, Risk-Based Inspection (RBI) could represent an effective tool to design inspection programs aimed at the detection of hydrogen-induced damages, especially for components working in pressurized environments, including pipeline materials. However, the lack of operational experience associated with emerging technologies may lead to the adoption of over-conservative safety measures, which could impact the economic attractiveness of these systems. Therefore, this study proposes an evolution of conventional RBI planning by implementing concepts of safety economics and optimization modelling, thus building a novel approach named “Cost-Informed Risk-Based Inspection” (CIRBI). The proposed methodology is therefore applied to a case study of inspection techniques potentially suitable for pipeline materials (i.e., API X-series pipeline steels), showcasing its potential as a self-standing approach for inspection planning while also demonstrating the insight that it may provide to ensure a safe operability of hydrogen pipelines.

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.

Decisions in complex systems need support from formal risk management. Traditional risk management, based on a "rational" idea of risk (the actual damage linked with probabilities), often diverges from public perceptions, leading to conflict between expert-led evaluations and societal acceptance. Two research directions have emerged to bridge this gap: enhancing stakeholder participation in risk management and incorporating emotional factors into risk assessment. Building on these efforts, we propose a systematic methodology integrating stakeholders' emotional considerations into formal risk management. Our approach combines a refined risk conceptualization with a structured stakeholder engagement process. An illustrative example involving an ammonia plant site-selection risk problem is presented to demonstrate the applicability of the proposed approach. The proposed approach offers a potential way to resolve conflicts and enhance public trust in risk management.

Pipelines are the most widely used system for transporting liquid and gaseous energy materials, but throughout their lifespan, they are exposed to various detrimental factors, such as corrosion and deviations in process variables. In recent years, the concept of resilience has gained significant attention as a means to analyze infrastructure behavior during failure states. This study introduces a novel metric for assessing pipeline resilience based on reliability. The proposed method involves an aging study of pipelines, considering the interaction of potential failures—such as corrosion, pressure variations, temperature fluctuations, and changes in fluid velocity—and subsequently analyzes ways to restore the system to its original conditions. The method offers an assessment approach for the three phases that constitute a resilience curve: absorption, adaptation, and restoration. This approach not only identifies the system's time to failure, but also through analysis of the resilience curve, facilitates the comparison of the effects of potential preventive, mitigative, and repair actions. A case study is presented to validate the method's efficacy. The results suggest that the proposed approach could be a valuable tool in the decision-making process within the asset integrity management (AIM) framework, aiming to optimize pipeline resilience by implementing the most effective safety solutions.

In recent years, the relationship between academia and the fossil fuel industry has become a focal point of intense debate. This concern arises from the fear that corporate funding might skew research activities. A significant development in this area is the adoption of policies by a Dutch university, and discussions in several others, prohibiting research funded by the fossil fuel industry. These policies aim to safeguard academic freedom and integrity. Despite this, there has been little discussion on the myriad challenges, implications, and possible unintended consequences, particularly in the realm of safety-and-security research. As such, this manuscript delves into the complex transition towards a fossil-fuel-free society, examining it through the lenses of safety science and sociotechnical systems. It emphasizes the vital importance of collective responsibility in ensuring systemic safety and security as we navigate towards achieving the sustainable development goals. This journey requires a delicate balance between the objectives of safety and sustainability, along with a deep understanding of the security implications of decreasing our dependence on the fossil fuel industry. The strategy of distancing academic research from fossil fuel industries, commonly seen as a positive step, also demands a nuanced consideration of its broader impacts, including the setting of precedents for addressing other existential and systemic risks. Instead, we argue for the establishment of robust governance structures rooted in restorative justice principles. Such frameworks can facilitate productive dialogue with underrepresented groups, motivate the fossil fuel industry towards sustainable practices, and safeguard the integrity of scholarly research. This approach not only addresses immediate concerns related to fossil fuels but also lays the groundwork for a more inclusive and equitable model of climate risk research, essential for tackling the multifaceted challenges of our era.

Chemical process industries are threatened by accidental and intentional major events that may lead to catastrophic consequences due to hazardous materials' production, operation, and storage. Remarkably, the digitalization of industrial facilities brings emerging cyber-physical attack risks, which calls for a holistic and integrated safety and security risk assessment and management. Considering the dynamic aspects of risks, the continuous monitoring and assessment of risk-related variations plays a vital role in making timely adaptions to risk treatment strategies and, therefore, accommodating increasing risks. To this end, this study proposes a comprehensive framework for risk-based safety and security barrier management, handling challenges in assessing integrated safety and security risks and deriving timely and cost-efficient barrier improvement strategies in case undesired risks are increasing to unacceptable levels. The fundamental ideas and applicable procedures are elaborated before a case study is demonstrated to offer insights into its feasibility. The case study shows that implementing this framework holds advantages in managing safety and security risks in a unified way, considering the interplays between safety and security and making continuous risk-treatment adaptions to sustain the safety and security of digitalized chemical process systems. Furthermore, the principles and precautionary considerations pertinent to this new framework are discussed to foster its application in real-world settings.

Integrating process safety and process security risk management is increasingly essential for enhancing resilience in the chemical process industry. This study addresses how practitioners perceive the integration of these two domains, identifying key benefits, barriers, and strategies for effective implementation. A mixed-methods approach was applied, combining quantitative survey data from 47 industry professionals with qualitative insights from open-ended responses. The findings highlight significant advantages of integration, such as optimized resource use, reduced operational redundancies, and improved risk management. However, barriers such as knowledge gaps, resource constraints, and communication silos were identified. Respondents emphasized the importance of adopting a resilience-oriented approach involving proactive risk management, continuous improvement, and adaptability in both safety and security practices. Critical enablers for integration include strong leadership, alignment of societal values, cross-disciplinary training, and integrated risk assessment methodologies. Emerging technologies and regulatory alignment were also identified as critical factors in facilitating integration. The study contributes to the theoretical understanding of integrated risk management by supporting resilience engineering and systems theory. It offers actionable strategies for overcoming barriers and leveraging enablers, laying the groundwork for developing a resilience-oriented framework for process safety and process security risk management.

Corrosion is a deterioration phenomenon of buried long-distance pipelines involving complex dynamic processes. The complexity poses challenges to addressing the safety concerns caused by corrosion. In recent years, the concept of resilience has been introduced into the assessment of engineering systems. However, there is a limited effort in quantitatively assessing the resilience of a pipeline's response to corrosion. This work aims to develop a novel framework to quantify the resilience of pipelines against corrosion while considering the resilience evolution induced by future corrosion growth, dynamic in-line inspection (ILI) plans, and distinct repair strategies (re-coating, composite material reinforcements, and pipe replacement). Pipeline Service Resilience (PSR) is modeled as a function of absorption, adaptability, and restoration capabilities based on the time-dependent burst pressure metric. Dynamic Monte Carlo Simulation technique is employed to model the potential resilience evolution scenarios to predict the PSR. The proposed framework is demonstrated on an in-service pipeline. The case results show that the PSR value ranges from 0.8943 to 1 due to the uncertainty of the resilience evolution process. Noteworthy impacts on PSR include repair time, ILI intervals, anti-corrosion ability, decision-making time, corrosion depth growth rate, and corrosion length growth rate (in decreasing order of sensitivity). The proposed methodology can potentially emerge as a significant tool for evaluating pipeline resilience under corrosion.

Understanding and enhancing the resilience of transport networks against climate-induced extreme events, such as wildfires, is critical to minimizing disruptions and their societal impacts. In this context, resilience is essential for effectively coping with these hazards, as road disruptions can hinder evacuation efforts, reduce accessibility, and lead to significant economic losses. Despite scientific progress, existing resilience assessment frameworks have limitations, including scenario-specific results and limited consideration of the underlying resilience concepts. To address these limitations, this paper introduces a resilience framework based on dynamic thresholds and characteristic curves to evaluate system recovery capacity. The framework incorporates a temporal dimension, allowing for the analysis of recovery time and recovery rate, which depend on the resources available for recovery activities. The characteristic curves illustrate system resilience by capturing key information on the preparedness, response, and recovery capacities inherent in each network. Consequently, the framework offers a more comprehensive view of system behavior during the recovery stage, as demonstrated through its application to a Portuguese case study. The insights gained can assist stakeholders in determining the feasibility of strengthening system resilience through enhanced response and recovery efforts, as well as in identifying when it is critical to reinforce resilience at earlier stages through adaptation measures.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.