Rising concerns over carbon emissions from fossil fuels have fueled interest in renewable energies. Hydrogen, as a clean energy source, stands out for its free of pollution and high calorific value. However, challenges in safely storing and transporting hydrogen, such as embrittlement, fire and explosion risks, are critical. This study reviews hydrogen storage and transportation safety research through a bibliometric approach, analyzing 948 relevant publications obtained from the Web of Science Core Collection, SCOPUS, and Science Direct literature databases since 2007. Then, a bibliometric analysis is conducted to obtain the publication's distribution, organization, source, and cooperation networks. Besides, the research hotspots in different periods are identified, and the evolution trend of hot topics is analyzed. Moreover, this paper proposes the possible future research needs in this field. The main hot topics in the field of hydrogen storage and transportation safety research include microstructure, crack, susceptibility, and hydrogen embrittlement and they change over time. In the future, research topics such as hydrogen damage in materials, compatibility of hydrogen in natural gas pipelines, and risk assessment should obtain more attention.

In the post-disruption phase, the resilience of LNG terminal system largely depends on maintenance resources—the more maintenance resources there are, the stronger the system's restoration capability and resilience. However, as maintenance resources increase, so do the associated maintenance costs. To enhance system resilience while controlling costs, a well-formulated optimization methodology is crucial. A process parameter-driven resilience optimization method for LNG terminal system considering the resilience enhancement rate (RER), cost and the maximum acceptable restoration time (MART) is proposed. The system resilience and RER are assessed by system performance curve, which is determined by time-dependent process parameters obtained from process simulations. The maintenance resources are represented by the number of maintenance team, including human resources, necessary equipment and materials, etc. A cost function model considering inherent cost, the cost of maintenance resources secondment and operating costs is established to represent the cost factors involved in the entire maintenance activity. According to derived results of the resilience assessment and cost analysis, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to solve the multi-objective optimization model developed in this study. The resilience enhancement optimization for the LNG terminal system is utilized to demonstrate the proposed methodology.

Deviations of process parameters from their normal ranges are the primary causes of accidents in chemical process systems. Traditional risk assessment methods largely rely on static probability analysis based on historical data, which struggles to capture the dynamic influence of real-time parameter variations on risk and lacks the capability to predict risk evolution trends. This paper proposes a dynamic risk prediction method for chemical process systems based on enhanced feature engineering and XGBoost. First, key process parameters (KPPs), including temperature, liquid level and flow rate are identified through process analysis. A comprehensive risk indicator is then constructed using Dempster-Shafer (D-S) evidence theory to achieve dynamic quantification of system risk. Second, a dynamic simulation model is established using Aspen Plus, simulating operations under normal, disturbed, and extreme conditions to generate time-series data of KPPs. On this basis, multi-scale sliding window techniques are employed to extract enhanced features, including temporal, statistical, trend, and disturbance features. Finally, an XGBoost-based risk prediction model is developed. A continuous stirred-tank reactor (CSTR) is employed to demonstrate the proposed methodology. The results indicate that the proposed methodology achieves an RMSE of 0.159, MAE of 0.122 and an R² of 0.7237, outperforming traditional methods by significant margins. The results validate the effectiveness of combining enhanced feature engineering with XGBoost for risk prediction in chemical processes.

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.

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.

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 conflicts 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.

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.

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.

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.

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.

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.

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.

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.

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.

Background: Human errors are widely acknowledged as the primary cause of structural failures in the construction industry. Research has found that such errors arise from the situation created by human factors and organizational factors embedded in the task context. However, these contextual factors have not been adequately addressed in the construction industry. Therefore, this study aims to identify the critical Human and Organizational Factors (HOFs) that influence structural safety in frequently performed tasks in structural design and construction. Methods: Through a comprehensive literature review, a framework consisting of potential critical factors called the HOPE framework, is presented. To identify the most critical HOFs that contribute to human error occurrences, a questionnaire survey to experts in the Dutch construction industry was conducted. Finally, the resulting framework was compared with three actual structural failures for validation. Results: This study shows that the HOFs should be extended with project-related factors (P) and working environment-related factors (E) due to the fact that these task contextual conditions play a significant role in shaping professionals' on-the-job performance. Furthermore, a survey identified 14 HOFs as critical in contributing to an error-prone situation in the structural design and construction tasks. Conclusion: The presented HOPE framework and the identified critical HOFs for structural safety can assist engineers with better hazard identification and quality assurance in practice.

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.

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.

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.