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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.