An earthquake-triggered fire domino scenario (E-FDS) is an example of a typical multi-hazard coupling event. The seismic damage can affect the fire resistance of engineering structures, leading to significant mutually amplified phenomena. In this work, a two-stage experimental program is designed to expound the earthquake-fire coupling failure mechanism of steel cylindrical tanks (SCTs). Quasi-static tests are adopted to simulate the damage characteristics of SCTs under seismic excitation (Stage I). Fire tests are adopted to investigate the fire-resistance performance of pre-damaged SCTs (Stage II). The influences of seismic damage on the fire resistance of SCTs are particularly of interest. Three potential seismic damage degrees are considered. The experimental results show that tank specimens exhibit typical diamond-shaped buckling after Stage I. The coupling failure analysis of SCTs is conducted through sequential thermodynamic coupling simulations. Due to factors such as geometric deformation, residual stress, and thermal radiation absorption capacity, the fire resistance of SCTs is significantly attenuated by seismic damage. For the three damage states, fire resistance time attenuation coefficients (0.868, 0.716, 0.511) and critical temperature attenuation coefficients (0.910, 0.779, 0.672) were obtained. This work provides pivotal insights into the mutually amplified phenomena in E-FDSs.

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Domino effects are a complex phenomenon of accident escalation with high uncertainty, which could lead to catastrophic consequences. Predicting the probability of domino effects presents a great challenge in the field of process safety. In multi-level domino chains, synergistic effects of accidents would further raise the complexity of probability prediction since escalation vectors emitted from those accidents may be coupled. In this paper, four categories of synergistic effects are classified according to the type of accidents and their place on the domino accident sequence. Subsequently, specific models for estimating escalation probability under different synergistic accident scenarios are proposed based on the widely-used probit models, allowing the analysis of the coupling effects of escalation vectors. A probability prediction method for domino chains is further developed using Bayesian Network. The application of the developed method is demonstrated by a case study, and the domino probability is estimated accounting for the synergistic effects and all possible accident scenarios. The key units for promoting accident propagation are further identified through posterior probability analysis. The method would be helpful for domino risk assessment and management of any chemical industrial area.

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Industrial production intensification greatly enhances resource utilization efficiency and production efficiency within the modern petrochemical industry (MPI). However, densely located hazardous installations pose significant threats to workers, society and environment. Under this impetus, an advanced pareto-based optimization methodology is proposed for chemical tank farm (CTF) design. The objectives of domino risk minimization and land resource utilization efficiency maximization can be achieved through optimizing the locations and dimensions of storage tanks. A simplified quantitative domino risk assessment procedure is developed within a grid-based Cartesian coordinate system, which links the design parameters and risk values. A bi-objective optimization model is developed for problem formulation and a well-designed simulated annealing-based multi-objective particle swarm optimization is proposed for model solving. A CTF with six floating roof diesel tanks is adopted for case study. The simulated annealing-based jumping mechanism can effectively avoid the local optimum, which makes the algorithm easier to obtain the trade-off with great convergence and diversity. The proposed methodology can provide safer and more cost-effective design solutions. Results indicate that the design parameters can significantly affect the regional domino risk distribution. The conflicting nature between safety and economy is discussed. This work is of great significance for the safety and reliability of MPI.

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Earthquake-triggered fire domino scenarios (E-FDSs) arise frequently from the interaction between earthquakes and chemical installations, resulting in catastrophic multi-hazard coupling events. The complicated mutually amplified phenomena between natural disasters and chemical accidents significantly aggravates the escalation of domino accidents, which has posed great challenges for modeling and preventing E-FDSs. Under this impetus, this work proposes an advanced type-2 fuzzy probabilistic methodology to obtain the time-dependent failure probability of steel cylindrical tanks (SCTs) subjected to the earthquake-fire sequence. To cope with the limited prior knowledge on E-FDSs, a basic universal is established to describe the fire resistance attenuation caused by the seismic damage. The coupling failure criterion of SCTs is formulated by a type-2 fuzzy time-dependent limit state equation. A credibility-based stochastic simulation algorithm is developed for the hybrid uncertainty analysis (combining ambiguity and stochasticity). The proposed methodology is validated by case studies of a 5000 m³ fixed roof tank. Compared to the existing accident probability model, the proposed methodology can not only capture the fire resistance attenuation caused by the seismic damage but also provide a dynamic estimation of tank failure probability with respect to the fire exposure time. The proposed methodology can effectively and dynamically capture the accident evolution process, which in turn helps mitigate and prevent the spatiotemporal propagation of domino effects.

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Liquid storage tanks play a vital role in the modern chemical process industry (CPI). The strong ground motion caused by large-scale earthquakes may easily impose severe structural damage on liquid storage tanks, leading to a series of catastrophic cascaded events. The seismic damage estimation of liquid storage tanks is a challenging problem, as the fluid-structure interaction exhibits extremely complicated and non-stationary response behavior. This study develops a novel data-driven methodology to estimate the seismic damage state probability distribution of liquid storage tanks in the contexts of label ambiguity and data imbalance. With the support of the advanced deep learning framework, synthetic oversampling methods, and label enhancement techniques, a hybrid deep belief network-based label distribution learning system (HDBN-LDLS) is proposed for probability distribution learning. The proposed HDBN-LDLS is evaluated on the widely used ALA database. Simulation results indicate that HDBN-LDLS can achieve a balanced estimation for all damage states while maintaining sufficient robustness to cope with label ambiguity. The reliability of the obtained data-driven model is validated by a damaged tank in the 2006 Silakhor earthquake. For practical applications, a more natural way to estimate a seismic damaged tank is to assign a membership degree to each possible damage state. The proposed methodology can quickly obtain the seismic damage state probability curves of a specific liquid storage tank, which can be used to support quantitative risk assessment and seismic design.@en

In chemical industrial areas, technological accidents triggered by natural events (Natech events) may escalate. Complex cascading multi-hazard scenarios with high uncertainties may be caused. Resilience is an essential property of a system to withstand and recover from disruptive events. The present study focuses on the change of the resilience level due to (possible) interactions between cascading hazards, chemical installations and safety barriers during the dynamic evolution of fire escalations triggered by a natural hazard (certain cascading multi-hazard scenarios). A quantitative resilience assessment method is developed to this end. The state transition of a system facing accidents in the context of resilience is explored. Moreover, the uncertainties accompanying an accident evolution are quantified using a Dynamic Bayesian Network, allowing a detailed analysis of the system performance in different time steps. System resilience is measured as a time-dependent function with respect to the change of system performance. The applicability of the proposed methodology is demonstrated by a case study, and the effects of different configurations of safety barriers on improving resilience are discussed. The results are valuable to support disaster prevention within chemical industrial areas.@en

A domino effect triggered by a natural event (a so-called Natech domino effect) represents a typical high-impact low-probability (HILP) event, which may lead to catastrophic consequences. The presence of safety barriers could have an impact on the effects by impeding propagation patterns and mitigating potential consequences. However, coordinating and maintaining safety measures to establish an effective barrier system against Natech domino effects is complicated. In this paper, the concept of what constitutes a safety barrier and the principles of barrier management are reviewed. Subsequently, the complex phenomenon of Natech domino effects is studied at the individual installation level, while the propagation pattern is explored at the system level. The application of safety barriers is discussed with the aim of coping with potential Natech domino effects. A systematic framework of barrier management is developed to establish and improve the barrier system in the whole cycle (design & construction, operation, accident, recovery & improvement) of a chemical industrial area. The challenges are discussed to highlight future study needs.@en

Natural hazards may rapidly lead to a massive domino chain in chemical industrial parks (CIPs). This work develops a high-efficiency and systematic analytical framework that is applicable to a broad range of uncertain and time-varying factors related to the evolution process of natural hazard-induced domino chain (NHDC). Specifically, the evolution mechanism of NHDC is revealed from a macro-systemic perspective. An event-driven disaster chain evolution system is developed, of which the system state transition is formulated by a Markov decision process and a temporal-difference learning algorithm. A system dynamic risk model is proposed to analyze the dynamic risk associated with NHDC. An earthquake-induced Na-tech scenario is adopted to demonstrate the methodology. Computational results indicate that the proposed methodology is competitive in simulating large-scale system state transition spaces. The involvement of natural hazards would lead to a more complex and severe evolution pattern. Five distinctive stages of the whole NHDC were identified. We found that the value of system dynamic risk is likely to surge in the deterioration stage. Our methodology can dynamically identify the critical system temporal intervals and units at each evolution stage, which has the potential to support the prevention and mitigation of such catastrophic chain events.@en

Industrial accidents triggered by natural disasters (Natech events) pose huge threats to chemical clusters. Flood is a significant cause of Natech events, the interactions between flood and chemical installations may lead to complex accident scenarios. However, the chemical clusters are often not well prepared for flood Natech events due to the lack of guidance on how to implement prevention and mitigation measures. In this paper, the characteristics of flood Natech events are firstly discussed, which provide a clear understanding of accident evolution. Based on the review of several Chinese standards related to flood prevention in chemical clusters, corresponding requirements are summarized. The requirements mainly focus on the planning and design stages. To cope with flood Natech events in a long-term vision, a comprehensive safety framework for chemical clusters is proposed in this article considering a resilient viewpoint, in which different roles of government, chemical cluster, and chemical plant are discussed. Moreover, three sub-models are divided to manage safety measures before, during, and after accidents, contributing to improving the resisting ability, adaptability, and recoverability of chemical clusters to flood Natech events, respectively.@en

Flood events impose great distress on chemical industrial areas, since they may cause Natech accidents involving multiple units. Furthermore, escalation vectors exerted by major accidents can trigger knock-on events, so-called domino effects, causing very severe consequences. In the present study, a methodology is proposed to include domino effects triggered by floods in a quantitative risk assessment, by addressing the frequency assessment of flood-induced domino scenarios. A comprehensive procedure is developed, combining the fragility model for unit damage due to floods, probability estimation for domino escalation, and combinatorial analysis for overall scenarios. Moreover, the flow interference due to the layout of chemical industrial areas is explored to calculate the damage probability more accurately. The methodology has been demonstrated by a case study, the changes in risk indexes and damage zones due to Natech domino effects are discussed. The results show that the overall risk significantly increases with respect to conventional scenarios when considering flood-induced Natech events and domino effects, evidencing the importance of risk analysis of Natech-related domino effects. Finally, some prevention measures have been proposed for chemical industrial areas to make them more resilient and safer when it comes to floods.

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While chemical industrial development in China is growing rapidly, the corresponding safety training resources remain inadequate, which may often lead to increased risk of chemical accidents. These accidents are often associated with the negligence of safety management, poor safety hazard awareness, and lack of safety practice. In order to alleviate these prominent risk factors in chemical industries in China, our study develops a talent training model related to chemical process safety. First, we propose an approach for establishing the “talent training model” related to chemical process safety, consisting of three steps: analyzing the current status and existing problems of talent training related to chemical process safety, determining the theoretical basis and training objectives for developing interdisciplinary talents, and designing a new talent training model. Second, we establish a talent training model using the proposed method, which includes a comprehensive curriculum system, a diversified teaching pattern, and a quintuple evaluation method. Furtherly, we determine the expected outcomes of the talent training model. The research results provide an innovative chemical process safety training method that is applicable nationwide, also it works as a reference for other rapidly developing countries in the chemical process industry to improve safety within the chemical industry.

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Suppressing the dendrite formation and managing the volume change of lithium (Li) metal anode have been global challenges in the lithium batteries community. Herein, a duplex copper (Cu) foil with an ant-nest-like network and a dense substrate is reported for an ultrastable Li metal anode. The duplex Cu is fabricated by sulfurization of thick Cu foil with a subsequent skeleton self-welding procedure. Uniform Li deposition is achieved by the 3D interconnected architecture and lithiophilic surface of self-welded Cu skeleton. The sufficient space in the porous layer enables a large areal capacity for Li and significantly improves the electrode–electrolyte interface. Simulations reveal that the structure allows proper electric field penetration into the connected tunnels. The assembled Li anodes exhibit high coulombic efficiency (97.3% over 300 cycles) and long lifespan (>880 h) at a current density of 1 mA cm⁻² with a capacity of 1 mAh cm⁻². Stable and deep cycling can be maintained up to 50 times at a high capacity of 10 mAh cm⁻².

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Domino effects are typically high impact low probability (HILP) accidents, whereby escalation effects triggered by fires are most frequent. The evolution of fire-related domino effects depends on synergistic effects and the performance of safety barriers, but those factors usually are time-dependent. In the present study, a methodology is developed to provide more accurate probabilities related to domino effects, by considering the temporal evolution of escalation vectors caused by time-dependent factors. The Dynamic Bayesian Network (DBN) approach is applied both to model the spatial-temporal propagation pattern of domino effects and to estimate the dynamic probabilities of domino chains. The methodology is illustrated with a case study to determine the dynamic aspect of the probabilities of domino effects considering the impact of add-on (active and passive) safety barriers and taking into account synergistic effects. The critical units for facilitating domino propagation have been identified by the analysis of posterior probabilities, and further validated using graph theory. The methodology will be helpful for risk management and emergency decision-making of any chemical industrial area.

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Earthquakes, floods and other natural disasters can lead to serious fires, explosions and other technical disasters, called Natech events, possibly triggering domino effects in chemical industrial parks. However, current studies only look at Natech events or domino effects separately, and don't consider domino effects triggered by Natech events with multiple primary accidents and with higher order accidents. This paper presents a method aiming to obtain all possible paths and probabilities of domino effects triggered by Natech events. Firstly, our suggested method is obtained by integrating conventional assessment frameworks for Natech events and domino effects. Secondly, the method is solved by a Matlab program based on (i) the scenario matrix, (ii) the scenario escalation matrix, and (iii) the path cell array. Finally, the method is illustrated and its availability is verified by a real chemical tank farm which suffered from a flood. The results show that this method can obtain and rank all the possible paths and their probabilities. Furthermore, the cumulative probabilities of each higher order level of domino effect and each tank can be obtained for a subsequent quantitative risk assessment considering both Natech events and their resulting domino effects.@en

Target equipment damage is a key factor in the quantitative risk assessment of domino effects caused by blast fragments. However, the damage process of target equipment caused by blast fragments in domino effect accidents has not been studied clearly. In this paper, a finite element (FE) model of large vertical storage tanks impacted by blast fragments is built to study the damage process. A small-scaled fragment impact experiment is carried out to validate the FE modeling approach. Based on accident statistical data and empirical formulas, the reasonable ranges of blast fragment parameters are obtained. The comparison between the rigid and the elastic–plastic fragment impact is conducted. The effects of filling degree, tank volume, impact height, roof-impact angle, fragment type, impact velocity and impact angle on the damage process are discussed. It can be concluded that: (1) The “added mass” effect of the inner liquid on the impact process increases with the filling degree. The fragment deformation has important effects on the impact process. (2) The impact process includes multiple collisions rather than only one collision. (3) The reduction of tank volume and the increase of impact height on tank wall can increase the damage degree. The impact on roof edge can make the fragment penetration easier. (4) End-caps for identical kinetic energy are more harmful to tanks than plates. The end-cap impact with horizontal impact angle of 35° causes the most serious deformation. This study provides insights into the damage mechanism and prevention of domino effects caused by blast fragments.

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Along with the expansion of China's chemical industry, a series of catastrophic chemical accidents have occurred, often with severe human casualties, resulting in adverse effects on the sustainable development. In line with these developments, process safety research is also developing rapidly in China. This paper aims to present insights in the progress of process safety research in China using bibliometric analysis. The results indicate that in China the most productive authors, institutions, and provinces are located in economically developed coastal areas and in areas with more universities specializing in safety science and engineering. As for the international cooperation, the most significant collaborating countries are economically developed countries or China's neighbors, and these countries have published a large number of papers important in this field. The citation analysis shows that Chinese process safety research currently still has a relatively limited international impact. The analysis of hot topics shows that there currently are very few new methods or research topics introduced in recent years, and there is still significant room for the Chinese research community to improve in some subdomains of the research field. Based on these trends and apparent shortcomings in the literature, future research directions are proposed. The results contribute to understanding the overall situation of process safety research in China, and can serve as a high-level synthesis of the research field. This information is useful for developing research and development policies and industrial strategies, and benefits the safety and sustainability of China's chemical industries.

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Atmospheric storage tanks damaged by floods may lead to severe NaTech accident scenarios, and the vulnerability assessment of process equipment suffered by natural events is a crucial point in NaTech risk analysis. In the present study, limit state equations for failure modes of displacement and buckling are introduced based on load-resistance relationships. The parameterized fragility models that can be used in a wide variety of atmospheric unanchored storage tanks and floods have been developed based on logistic regression (LR), and moreover, the models are assessed and validated by receiver operating characteristic (ROC) curves and available accident data in literature. The effects of filling level and density of storaged liquid, the diameter and height of tank, and the inundation height and velocity of flood on the vulnerability of different failure modes are analyzed using fragility curves. Furthermore, fragility magic cubes are first proposed to obtain critical disaster conditions and critical filling levels in different cases. Finally, corresponding quantitative mitigation measures in different stages such as site selection, design, and operation are proposed based on the results of vulnerability assessment.

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The increasing demand for chemical products has driven the construction and development of chemical industrial areas, or so-called 'chemical industrial parks' (CIPs), but this has intrinsically raised the risk of major accidents. Therefore, it is significant and urgent to summarize the state of art and research needs in the field of CIP safety. In this paper, a keyword co-occurrence analysis of 116 scientific articles was conducted to support the classification of research topics in this field, then an overview of those research topics was presented to investigate the evolution of safety research with respect to CIPs. Specifically, the way that safety assessments are conducted, as well as how safety management and safety technology in such areas are classified and investigated, followed by detailed descriptions of representative methods and their contributions to CIP safety, are discussed. An integrated safety framework for CIPs is proposed to organize safety approaches and measures systematically. Based on the classification and analysis of studies on management, assessment, and technology related to CIP safety, the research trends and future directions and challenges are discussed and outlined. Those results are useful for improving theoretical method and industrial strategies, and can advance the safety and sustainability development of CIPs.

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Although there is a growing field of research focusing on university laboratory safety, accidents in such contexts still occur relatively frequently. Therefore, it is significant to summarize current research status and gaps, and to propose future research directions in the field of university laboratory safety. In this paper, a bibliometric analysis method was applied to gain an overall view of the developments, focus areas, and trends in this field of safety research. A total of 219 scientific publications on university laboratory safety were identified and screened from the database of Web of Science, covering 44 countries or regions, 254 research institutions, 575 authors, 126 publication sources, and 70 subject categories. Bibliometric data such as annual growth trend and distribution of subject categories were analyzed by using descriptive statistics. The most productive and influential countries, institutions, authors, and their cooperation networks were identified from co-citation maps created by VOSviewer. Further analysis was carried out to find out the core publications and publication sources in this field. Insights in the focus areas and research topics over time were obtained through terms co-occurrence analysis. The results indicate that university laboratory safety is a highly multidisciplinary research field. However, it is still a young discipline and belongs to the minority research field when compared with other safety domains. Several avenues for future research are identified to advance and make progress in this field.

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A major chemical accident has the characteristics of being destructive, and potentially provoking a great loss of lives and property damage in any Chemical Industrial Park (CIP). Emergency rescue and evacuation are essential parts of emergency decision-making for enhancing the capacity and effectiveness of emergency handling and reducing the potential loss of accidents. Most of current literature concentrates on one-way route planning of emergency rescue and evacuation, and applies different models, optimization objectives and algorithms. However, when applying the one-way route planning model in a CIP, a road conflict is possible due to the inherent weak traffic capacity. Therefore, a new method of two-way route planning of emergency rescue and emergency evacuation which considers intelligent obstacle avoidance, is proposed in the paper. The method we developed integrates three modeling components: (i) a dynamic grid environment model to simulate the interaction between the road network and the time-varying location of emergency rescue and evacuation. (ii) a two-way route planning model to simultaneously optimize routes of emergency rescue and routes of emergency evacuation. (iii) an intelligent obstacle avoidance model to prevent potential road conflicts. The results illustrate that the proposed model is able to generate a set of two-way optimum routes and overcomes possible road conflicts successfully.

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