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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

When considering a quantitative risk assessment of domino effects in chemical process facilities, the Damage Probability of equipment exposed to Fire (DPF) is a key element. In this paper, an innovative framework is proposed to determine the DPF, and the approach is demonstrated using a vertical plate. Being different from the current Probit model, structural reliability methods are applied to a pre-established lumped temperature model to obtain the DPF. Moreover, the static and dynamic DPF are distinguished, where the static one is obtained through the first-order reliability method and response surface method with an innovation in the pre-analysis of stable state to derive the limit state equation, while the dynamic one is obtained solving the Kolmogorov backward equation using the finite difference method based on stochastic diffusion process and first passage failure theories. The vertical plate demonstration shows the feasibility and availability of the proposed framework. A more practical case study with a horizontal LPG tank is also discussed to validate the suggested approach.

The primary event, damage vector, escalation scenario and escalation network are the fundamental components of any domino effect, and in literature, quantitative risk assessment (QRA) is the main topic of investigation for such escalating accidents. However, a QRA's implementation and application are complicated, and its results are currently not very useful in industrial practice for implementing prevention, protection and control measures. In this paper, the use of an equipment vulnerability assessment (EVA) focusing on the probability of escalation scenario occurrence is suggested, which could provide a deep understanding at the elemental level, while QRA is used at the system level. Specifically, the outline, methods and programme for EVA are discussed. In addition, a five-level hierarchical framework (FLHF) is proposed to prevent and control domino effects comprehensively and systematically, which includes Level 1–Prevention of loss of containment (LOC); Level 2–Safety distance, safety inventory and layout optimization; Level 3–EVA and safety design, safety improvement; Level 4–Reengineering of layer-of-protection analysis (LOPA); and Level 5–QRA of the domino effect. The quantification and implementation of each level are also discussed in detail.