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The main objective of this research is to establish a quantitative risk assessment method for fire spread in enclosed building scenarios. The enclosed building fire spread process is divided into three stages: fire fully developed in the fire compartment, failure of weak barrier, and combustibles ignited in the target compartment. The calculation method for fire spread is established, where the time for fire fully developed is calculated based on the t2 fire, the barrier failure time is calculated based on the finite difference method, and the combustible ignition time is calculated based on the zone model. The linear regression model is formulated to ensure computational efficiency for fire spread time prediction. The enclosed building fire spread quantitative risk assessment method is proposed based on the Probit model. The effectiveness of the risk assessment method is validated through the enclosed building fire spread experiment, and the method is applied to assess the risk of fire spread in an office. The results demonstrate that the method could quantitatively assess fire spread risk under different conditions with high computational efficiency and excellent versatility, and it could provide guidance for fire prevention, building fire design, and fire rescue. [ABSTRACT FROM AUTHOR]

The effects of natural hazards triggering technological disaster (NaTech) on a society, economy and the environment is a multi-disciplinary research topic. The novelty of the issue and the lack of a standard procedure for risk assessment of this category of incidents show the need for more research in this area. This article introduces OpenSRANE as an open-source, extensible, flexible and object-oriented software for calculating the quantitative risk of NaTech events in process plants. Implementing the software in the Python programming environment provides high flexibility for the modeling and evaluations desired by users. The possibility of implementing the modifications and developments to the existing software as needed by users allows them to add their desired algorithms, elements and models to it, if needed. The software is based on the Monte Carlo method, but it is possible to implement other algorithms and approaches to it. Object-oriented programming and separation of the different parts of the software can increase the readability of the program, allowing researchers in different disciplines to focus easily on studying or developing the desired part with minimal interference from other parts. The applicability of the software has been demonstrated in a case study as well as the ability of the software to calculate results such as the individual risk, scenarios that consider domino effects and physical effects.

Urban areas are expanding exponentially, leading more species of wildlife living in urban environments. Urban environmental characteristics, such as human disturbance, induce stress for many wildlife and have been shown to affect some cognitive traits, such as innovative problem‐solving performance. However, because different cognitive traits have common cognitive processes, it is possible that urban environmental characteristics may directly and indirectly affect related cognitive traits (the ripple effect hypothesis).We tested the ripple effect hypothesis in urban Eurasian red squirrels residing in 11 urban areas that had different urban environmental characteristics (direct human disturbance, indirect human disturbance, areas of green coverage and squirrel population size). These squirrels were innovators who had previously repeatedly solved a food extraction task (the original task). Here, we examined whether and how urban environmental characteristics would directly and indirectly influence performance in two related cognitive traits, generalisation and (long‐term) memory. The generalisation task required the innovators to apply the learned successful solutions when solving a similar but novel problem. The memory task required them to recall the learned solution of the original task after an extended period of time.Some of the selected urban environmental characteristics directly influenced the task performance, both at the population level (site) and at individual levels. Urban environmental characteristics, such as increased direct and indirect human disturbance, decreased the proportion of success in solving the generalisation task or the memory task at the population (site) level. Increased direct human disturbance and less green coverage increased the solving efficiency at individual levels.We also found an indirect effect in one of the urban environmental characteristics, indirect human disturbance, in the generalisation task, but not the memory task. Such an effect was only seen at the individual level but not at the population level; indirect human disturbance decreased the first original latency, which then decreased the generalisation latency across successes.Our results partially support the ripple effect hypothesis, suggesting that urban environmental characteristics are stressors for squirrels and have a greater impact on shaping cognitive performance than previously shown. Together, these results provide a better understanding of cognitive traits that support wildlife in adapting to urban environments. [ABSTRACT FROM AUTHOR]

Firefighting strategies at process plants would include simultaneous extinguishment of burning units and cooling of exposed units if firefighting resources are sufficient. This way, the fire can be contained and its propagation to the exposed units can be prevented, which would otherwise cause fire escalation and result in domino effects. However, when the firefighting resources are not sufficient to handle all the critical units—either burning or exposed—at once, firefighters need to decide which burning units to suppress first and which exposed units to cool first to minimize the risks. Making effective decisions in such situations becomes critical knowing that, by spreading the fire to adjacent units, the number of critical units grows exponentially, making the available firefighting resources even more insufficient. In the present study, after modelling fire spread in a tank terminal as a directed graph, closeness centrality—a graph centrality metric—is used to identify the critical units from the viewpoint of their contribution to potential domino effects. Knowing the critical units and considering available firefighting resources for suppression and cooling of these units, mathematical programming is applied for optimal allocation of firefighting resources. A comparison between the results of the present work and previous studies shows the effectiveness of the developed methodology. [ABSTRACT FROM AUTHOR]

The aim of this current study is to assess the essential role of teacher cognitive presence within the context of the community of inquiry framework in relation to enhancing students’ academic perseverance, more specifically this type of presence influences the most students’ academic perseverance. In order to test this hypothesis, an online questionnaire was created, including the community of inquiry scale and the grit scale. A total of 529 valid and consented answers were collected. We have further analyzed the structure of the variables network with network analysis and then we have employed several sequential mediation analyses testing the impact of cognitive presence triggering events and resolution on the relationship between all the other presences and students’ academic perseverance. A circular structure has emerged in network analysis and eight significant full complementary sequential mediation analysis. Results confirm the domino effect of teacher cognitive presence triggering events and resolution on student’s grit under the community of inquiry framework. [ABSTRACT FROM AUTHOR]

Social media-driven speculations play a crucial role in triggering the collapse of the banking system and stock markets. In this paper, we investigate the effect of Twitter-based investor sentiment on the collapse of Silicon Valley Bank (SVB), the 16th largest bank in the US. Additionally, we examine the spillover effect of the social media-based investor sentiment and SVB collapse on the bank stock indices from twelve countries where Global Systemically Important Banks (G-SIBs) operate. Advanced machine and deep learning models are employed to model the social media-based investors' sentiment regarding SVB implosion and its spillover effect on the G-SIBs' bank stock indices. Our results reveal that social media-based negative investors' sentiment played an important role in SVB implosion. Our results further show that the negative investors' sentiment persisted, and its systemic shock was transmitted to the G-SIBs bank stock indices. Importantly, our results provide a lead and lag relationship between investors' sentiment and returns of G-SIBs bank stock indices. The findings of this study offer crucial insights for policymakers to consider the external shocks associated with social media-based investors' sentiment when devising policies related to bank runs, thus helping to prevent future financial crises and cross-border contagion. [ABSTRACT FROM AUTHOR]

Seismic events can trigger a NaTech disaster, leading to the release of hazardous materials, fires, and explosions. These can occur within industrial complexes and along distribution networks as a result of natural disasters. Industrial plants, composed of structural and non-structural components, may be damaged when subjected to earthquakes of a given magnitude. Some examples of these disasters occurred in Kobe (1995), Kocaeli (1999), and Tohoku (2011). This study aims to assess the local seismic hazard by the implementation of different analytical approaches in a Major-Hazard Industrial Plant (MHIP) triggering a NaTech event. For the Bussi MHIP area, a geodatabase has been designed where geometric and geotechnical parameters have been associated with each geotechnical unit. The local seismic hazard has been simulated using 1D and 2D codes, considering two seismic hazard scenarios limit state SLV - SLC according to the National Building Code (NTC2018). In this study, the amplification factor AF has been calculated within the natural vibration range of an H2O2 storage tank located in the Bussi MHIP facility. This type of structure was chosen as it represents an element able to generate a relevant accident and consequently, a potential NaTech event. [ABSTRACT FROM AUTHOR]

Effective firefighting and evacuation are integral parts of emergency response plans in process plants, which play a key role in protecting human lives and assets in the event of major fires. Given sufficient firefighting resources, firefighters would suppress all the burning vessels and cool off all the exposed vessels in order to contain the fire and prevent a fire‐induced domino effect. However, when the number of critical units—whether on fire or exposed to fire—exceeds the firefighting resources, firefighters should decide how to optimally allocate the resources so as to best satisfy the safety goals. To facilitate such decisions, the present work aims to develop a methodology for effective firefighting under insufficient resources. The methodology seeks out two safety goals via optimal firefighting strategies: (1) providing for the safety of evacuees, and (2) reducing the risk of domino effects. Although both safety goals are attempted to be satisfied at the same time, a higher priority is assigned to the first goal as long as the evacuation is underway. When the evacuation is complete, all the resources are focused on the second goal. The study shows that a multi‐objective optimization approach to identifying firefighting plans outdoes single‐objective optimization approaches in that several safety goals could be met at once. Although only two safety goals are considered in the present study, the methodology is flexible enough to accommodate several goals such as safety of offsite people and assets. [ABSTRACT FROM AUTHOR]

We examine the effects of thermal radiation on the meteorological conditions and layout of flammable liquid storage tanks. Currently, the separation distances between the tanks are dictated by regulations to prevent the domino effect of fire accidents. Although thermal radiation leads to the domino effect, it is questionable whether thermal radiation is considered in the current Korean regulations. In this study, three cases—one based on a regulation and two others associated with meteorological conditions—are considered, for which the radiation effects and tank layouts are calculated. A software program and an optimization algorithm, namely ALOHA and sequential least‐squares programming, respectively, are employed for hazard analysis and optimization, respectively. The results indicate that the current regulation is appropriate under normal meteorological conditions but may not ensure prevention of the domino effect under the worst conditions. [ABSTRACT FROM AUTHOR]

The domino effect that occurs among the concepts that affect Supply Chain Resilience has only been marginally analysed, and no conceptual models have been proposed in the literature. In this work, a conceptual model for analysing this domino effect is developed. The method aims to identify which supply chain concepts can support the containment of disruptions and how these concepts affect one another. The proposed methodology is based on Fuzzy Cognitive Maps. The Cognitive Maps tool enables us to connect multidimensional and multidisciplinary concepts (e.g. sources of risk, disruption factors, supply chain management practices and other aspects). Moreover, this tool allows company managers to develop a detailed understanding of a system's behaviour and to explicitly consider the mind models of different players in the supply chain. A case study of the fashion industry supply chain is used to illustrate the application of the proposed method in an operating context. The proposed method enables a company to evaluate the hidden chain reaction of causes behind the most important factors that, from a single trigger event, are able to harm the entire Supply Chain. Through analysis of the causal relationships that this methodology highlights, decision makers can examine the domino effect among the concepts that influence Supply Chain Resilience in a step-by-step manner. [ABSTRACT FROM AUTHOR]

The synergistic effect of explosion and fire (SEEF) is one of the challenges of domino effect risk assessment for petrochemical storage tank farms. However, the domino effect probabilities at different orders and accident propagation patterns in storage tank farms under the SEEF are still unclear. An approach based on Bayesian networks is developed to model the propagation of domino effects in storage tank farms under the SEEF. The method accounts for the temporal and spatial synergistic effects of blast wave and fire thermal radiation in multiple accidents during domino accident escalation and the damage enhancement effect caused by the SEEF on the target units. Application of the method to a real tank farm highlights that the SEEF has a significant impact on the domino effect probabilities. Compared with only considering a single accident type, the SEEF leads to an increase in the domino effect probabilities of the tank farm. Installing water deluge systems and blast walls for all tanks at the same time is an effective safety measure to mitigate domino effects due to the SEEF. When safety resources are limited, the priority to equip critical tanks with water deluge systems and blast walls can also mitigate the domino effects. [ABSTRACT FROM AUTHOR]

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In order to select the location of fire stations more scientifically and improve the efficiency of emergency management in chemical industry parks (CIPs), an improved risk calculation model for hazardous chemicals has been proposed by taking the domino effect and the identification of major hazardous installations for hazardous chemicals into account. In the analysis of the domino effect, the Monte Carlo simulation was used. Then, a location model of the fire stations was established with the optimization objectives of minimizing total cost and maximizing total risk coverage. The solving procedure of the location model is based on the augmented ε -constraint method combined with the TOPSIS method. Finally, a green chemical industry park was used as a case study for the validation and analysis of the location model. The results showed that the improved model could protect the high-risk areas, which is beneficial for the location decisions of fire stations. [ABSTRACT FROM AUTHOR]

Compared with safety assessment, security risk assessment in chemical and process plants is more challenging. On top of uncertain environmental and operational parameters and interdependent failures, which are common in the safety risk assessment of complex systems and infrastructures, there are other uncertain parameters such as the likelihood of attack scenarios and attackers' expected outcomes. As such, the application of probabilistic risk assessment (PRA) techniques, which have long been applied to safety risk assessment and management, to security risk management may result in nonoptimal or suboptimal decisions. In the present study, we will demonstrate how a combination of PRA and game theory may outperform PRA and lead to a more cost‐effective allocation of security measures. For this purpose, the outcome of a dynamic Bayesian network—as a PRA technique—is used as input to the minimax strategy—as a game theoretic strategy—for security risk management of a tank terminal under attacks with a homemade bomb. The proposed risk‐based minimax strategy alleviates the need for estimation of attack likelihoods or attacker payoffs, which would have otherwise been too challenging to estimate if the analyst solely depended on a PRA technique. [ABSTRACT FROM AUTHOR]

Along with global climate change and industrialization, domino effects caused by Natech events occurred frequently in chemical industrial parks over the past decades. Previous research has not yet proposed a reliable method to obtain all possible paths of Natech domino effects, and moreover, a risk assessment and mitigation system has not been established. The present work aims to develop a quantitative framework for propagation paths of Natech domino effects, which can effectively safeguard the sustainable development of chemical industrial parks. The presentation of this work is divided into two parts: Part I (current paper) proposes a path probability calculation method that can simultaneously consider multiple primary accident scenarios and multi-level domino effects triggered by natural disasters. The proposed method transforms the propagation paths of domino effects into the paths of directed graph by constructing the equipment failure state transition matrix and the equipment failure state transition probability matrix. The depth-first traversal algorithm is used to obtain all possible propagation paths and their propagation probabilities, providing data support for the quantitative risk assessment and prevention and control measures presented in the accompanying paper (Part II). The case study shows that the probability of equipment failure caused by multi-level domino effects triggered by Natech accidents is higher than that of conventional accidents. However, the present work only considers the spatial propagation of domino effects, while their spatio-temporal propagation remains as a further direction for this area of inquiry. [ABSTRACT FROM AUTHOR]

This is the second part of the quantitative framework for the propagation paths of Natech domino effects in chemical industrial parks, which focuses on risk assessment and a mitigation system based on the propagation path probabilities obtained from Part I. In this paper, the risk assessment model for the propagation paths of the domino effects induced by natural disasters are developed, and the risk level is quantitatively analyzed using individual risk and social risk indexes and compared with the risk acceptance standard to determine whether the risk in the plant area is at the risk acceptance level. Furthermore, the chain-cutting disaster mitigation model for domino effects induced by Natech events and the full-life-cycle mitigation system are proposed, and the effectiveness of mitigation measures is also evaluated. The case analysis results show that Natech events and multi-level domino effects can increase the risk to an unacceptable level, and taking corresponding mitigation measures could reduce the risk to an acceptable level. [ABSTRACT FROM AUTHOR]

Hydrogen–gasoline hybrid refueling stations can minimize construction and management costs and save land resources and are gradually becoming one of the primary modes for hydrogen refueling stations. However, catastrophic consequences may be caused as both hydrogen and gasoline are flammable and explosive. It is crucial to perform an effective risk assessment to prevent fire and explosion accidents at hybrid refueling stations. This study conducted a risk assessment of the refueling area of a hydrogen–gasoline hybrid refueling station based on the improved Accident Risk Assessment Method for Industrial Systems (ARAMIS). An improved probabilistic failure model was used to make ARAMIS more applicable to hydrogen infrastructure. Additionally, the accident consequences, i.e., jet fires and explosions, were simulated using Computational Fluid Dynamics (CFD) methods replacing the traditional empirical model. The results showed that the risk levels at the station house and the road near the refueling area were 5.80 × 10−5 and 3.37 × 10−4, respectively, and both were within the acceptable range. Furthermore, the hydrogen dispenser leaked and caused a jet fire, and the flame ignited the exposed gasoline causing a secondary accident, considered the most hazardous accident scenario. A case study was conducted to demonstrate the practicability of the methodology. This method is believed to provide trustworthy decisions for establishing safe distances from dispensers and optimizing the arrangement of the refueling area. [ABSTRACT FROM AUTHOR]

In recent years, hazardous materials transportation accidents have received increasing attention. Previous studies have focused on accidents involving a single vehicle. When vehicles loaded with materials gather on a stretch of road, a potential domino accident might cause terrible incidents. This paper prompts a quantitative risk assessment (QRA) model to estimate the risk of multi-vehicle incidents. The model calculates the possibility of leakage and explosion of hazardous chemicals using a dynamic Bayesian network (DBN). For different types of hazardous chemicals, the model uses event trees to list different scenarios and analyzes the probability of domino accidents caused by each scenario. The FN-curve and potential loss of life (PLL) are used as an index to evaluate social risk. A case involving multiple vehicles in the JinShan District, Shanghai, is analyzed. The result of the case shows that the state of the driver, the type of road, weather factors and the distance between vehicles have vital impacts on the societal risk resulting from hazardous materials transportation accidents. [ABSTRACT FROM AUTHOR]

Proliferative diabetic retinopathy (PDR) the sequel of diabetic retinopathy (DR), a frequent complication of diabetes mellitus (DM), is the leading cause of blindness in the working-age population. The current screening process for the DR risk is not sufficiently effective such that often the disease is undetected until irreversible damage occurs. Diabetes-associated small vessel disease and neuroretinal changes create a vicious cycle resulting in the conversion of DR into PDR with characteristic ocular attributes including excessive mitochondrial and retinal cell damage, chronic inflammation, neovascularisation, and reduced visual field. PDR is considered an independent predictor of other severe diabetic complications such as ischemic stroke. A "domino effect" is highly characteristic for the cascading DM complications in which DR is an early indicator of impaired molecular and visual signaling. Mitochondrial health control is clinically relevant in DR management, and multi-omic tear fluid analysis can be instrumental for DR prognosis and PDR prediction. Altered metabolic pathways and bioenergetics, microvascular deficits and small vessel disease, chronic inflammation, and excessive tissue remodelling are in focus of this article as evidence-based targets for a predictive approach to develop diagnosis and treatment algorithms tailored to the individual for a cost-effective early prevention by implementing the paradigm shift from reactive medicine to predictive, preventive, and personalized medicine (PPPM) in primary and secondary DR care management. [ABSTRACT FROM AUTHOR]

Several large‐scale components of the climate system may undergo a rapid transition as critical conditions are exceeded. These tipping elements are also dynamically coupled, allowing for a global domino effect under global warming. Here we focus on such cascading events involving the Greenland Ice Sheet (GIS), the West Antarctica Ice Sheet (WAIS) and the Atlantic Meridional Overturning Circulation (AMOC). Using a conceptual model, we study the combined tipping behavior due to three dominant feedbacks: the marine ice sheet instability for the WAIS, the height‐surface mass balance feedback for the GIS and the salt‐advection feedback for the AMOC. We show that, in a realistic parameter range of the model, a tipping of the WAIS can inhibit cascading events by preserving the AMOC stability. Plain Language Summary: In the climate system, the interaction of specific components known as tipping elements are thought to be able to induce a global domino effect, or cascading tipping. In this study, we present a conceptual model containing the most strongly interacting components, namely the Atlantic Meridional Overturning Circulation (AMOC), the Greenland Ice Sheet and the West Antarctica Ice Sheet. We find that the stability of this system as a whole is strongly modified when interactions are included. Especially, while a Greenland Ice Sheet collapse destabilizes the AMOC, the model shows that a collapse of the West Antarctica Ice Sheet might prevent a global cascading event by stabilizing the AMOC. Key Points: A conceptual model of interacting Atlantic Meridional Overturning Circulation (AMOC), Greenland Ice Sheet and West Antarctica Ice Sheet (WAIS) is presentedInteractions between these tipping elements strongly modifies the stability of the whole systemA collapse of the WAIS can prevent tipping of the AMOC [ABSTRACT FROM AUTHOR]

Due to the various dynamic conditions of construction sites, quality failures have become part and parcel of the industry. Many studies have identified the causal factors of construction site quality failures and their cost impacts. However, limited studies have been made evaluating the domino effects of these on one another and the correlation between the cost impact and frequency of each attribute. In this study, made in the context of ongoing research into related artificial intelligence (AI)–based predictive models, a total of 2,527 nonconformance reports (NCRs) collected from 59 construction projects within the scope of a previous study were analyzed using the Delphi method and logistic regression analysis. According to the Delphi results, 25 critical cost impact factors were refined and categorized into five main groups: Materials, Design, Installation, Operation, and Process. Then, five main hypotheses were developed to test each attribute's cost impact and interaction by logistic regression. The results showed that although some attributes (from the Materials and Operation groups) have a significant impact on the cost of quality if observed in a failure report individually, others may become a critical cost-impact factor when interacting with other attributes. No significant correlation was observed between the frequency and cost impact of the attributes. Finally, a holistically based quality control system that considers the domino effects of causal factors from planning to operation was proposed for construction practitioners to reduce quality failures causing cost and time overruns. [ABSTRACT FROM AUTHOR]

Based on the typical physical effects of different accidents and considering the interaction of time and space, a dynamic evolution model of the domino effect was proposed in this study. The Monte Carlo method was used to deal with the uncertainty of the evolution path and capture the characteristics of the time evolution. The model considered mixed accident types and the synergistic effect of accidents and extended the application of the probit model. Risk assessment parameters such as evolution path, evolution time, tank accident probability, and domino evolution probability were obtained to evaluate the vulnerability of storage tanks exposed to such hazards. The proposed model was verified through a comparative case analysis, and the results showed that the model can not only capture the space–time dimension but also overcome the limitations of conventional analysis of high-level domino propagation. Different accident types, synergistic effects, and burning capacity of storage tanks have a significant impact on the domino propagation process. [ABSTRACT FROM AUTHOR]

In this study, a fuzzy Bayesian network (FBN) approach was proposed to analyze the domino effects of pool fire. Failure probabilities were calculated using triangular fuzzy numbers, the combined center of area (CoA)/sum-product method and the BN approach. Consequence modeling, probit equations and leaky–noisy-OR (L-NOR) gates were used to analyze the domino effects, and modify conditional probability tables (CPTs). Methanol storage tanks were selected to confirm the practical feasibility of the suggested method. The domino probability using bow-tie analysis (BTA) and FBN in the first and second levels was compared, and the ratio of variation was used for sensitivity analysis. Probability of the domino effect in the first and second levels (FBN) was 0.0071472631 and 0.0090630640, respectively. The results confirm this method is a suitable tool for analyzing the domino effects and that using FBN and L-NOR gate is a good way to assess the reliability of tanks. [ABSTRACT FROM AUTHOR]

The present study aims to find out the origin of authors and the main sources in which citing documents of Wakefield's 1998 retracted article are published in order to understand whether they act as promoters of a negative domino effect, there is, keeping alive a retracted article due to fraudulent data and analysis on the relationship between MMR (measles, mumps, and rubella) vaccine and autism. The metadata of the 1577 citing documents of Wakefield's article were downloaded from Scopus in three files according to the year of publication: 1998–2004 (partial retraction), 2005–2010 (in between partial and full retraction) and 2011–2020 (post full retraction). The number of citing documents in each period is 329, 411 and 837, respectively. A comparison between first and last periods indicates an impressive growth of language, authors, countries as well as journals from broader field coverage. Also, recent citing articles are highly cited and, even in a negative context, they contribute to the diffusion of a fraudulent article in the science context. The findings reinforce the urgency to create internal strategies in the scientific communication process, mainly inside the editorial flow, in order to reduce the dissemination of a retracted article that, in this case, is still harmful to society. At the end, the creation of an automatic mechanism to detect retracted articles included in the reference list of accepted articles is suggested. [ABSTRACT FROM AUTHOR]

Aggregation of vehicles transporting hazardous chemicals is part of a complex system of hazardous chemical transportation with frequent accidents that threaten public safety. In order to avoid catastrophic consequences in the vehicle aggregation areas, dynamic risk assessment models have been studied in this paper. The macro quantitative risk assessment (M-QRA) model determines the accident probability through the probability of leakage and the probability of induced secondary accidents and takes into account the domino effect to determine the risk in conjunction with the consequence of pool fire, but some data are not readily available. Therefore, in order to accurately assess the risk in case of incomplete data, a rapid quantitative risk assessment (R-QRA) model considering the number of vehicles and the critical mass of hazardous chemicals was developed. In this paper, the M-QRA and R-QRA model were used to calculate the real-time risk of aggregation of vehicles transporting hazardous chemicals respectively, and the two models were compared in terms of calculation accuracy and assessment efficiency. The results show that the risks obtained from the two models are basically consistent, but the R-QRA model is faster in calculation, which is of great practical significance for actual engineering applications and helps safety management. [ABSTRACT FROM AUTHOR]

• A comprehensive probability prediction method for domino effects is developed. • Escalation probability models under different synergistic effects are established. • Different scenarios after unit failure are modeled to obtain domino probability. • Risk reduction measures are proposed based on the posterior probability analysis. 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. [ABSTRACT FROM AUTHOR]

With the enlargement and intensification of oil storages, the technologies and equipment used in the tank farm are quite complicated. Hence, once any fire accident occurs, the domino effect may be triggered with catastrophic consequences. In order to reduce the impact of oil storage accidents on the surrounding personnel and environment, the model of safety barrier was established with the event tree and Bayesian network method by considering the performance of three types of safety barrier, including the active, passive, emergency and response measures, and the probability of the domino effect was evaluated quantitatively. The results show that: the multi-layer safety barriers can reduce the probability of domino effect by 3 to 7 orders of magnitude and the probability of the multi-level domino effect to a greater extent. Besides, the passive protection barrier is the most effective, followed by the emergency and response measures, and the active barrier is the least effective. Generally, the research results can provide some guidance for reducing the damage and impact of regional accidents in the areas where multiple devices are concentrated.

Abstract Several large‐scale components of the climate system may undergo a rapid transition as critical conditions are exceeded. These tipping elements are also dynamically coupled, allowing for a global domino effect under global warming. Here we focus on such cascading events involving the Greenland Ice Sheet (GIS), the West Antarctica Ice Sheet (WAIS) and the Atlantic Meridional Overturning Circulation (AMOC). Using a conceptual model, we study the combined tipping behavior due to three dominant feedbacks: the marine ice sheet instability for the WAIS, the height‐surface mass balance feedback for the GIS and the salt‐advection feedback for the AMOC. We show that, in a realistic parameter range of the model, a tipping of the WAIS can inhibit cascading events by preserving the AMOC stability.

The location of process equipment is an important issue for the industry. Poor distribution directly affects the safety and economy of the process. In this work, a multi-objective optimization is proposed to optimize the distribution of the layout, minimizing the annual cost and the risk of a domino effect. The optimization model minimizes the domino effect risk by evaluating the consequences and frequency of accidents due to explosions. The cost function considers equipment, pipes, land, active and passive safeguards, and the cost of explosion and pumping. The resulting model corresponds to an MINLP. For multi-objective optimization the ε-constraint method is used. The model is solved using GAMS®. The case study is the biodiesel production process using ethanol at supercritical conditions. The HPSI index is used to identify dangerous equipment. The fault tree methodology is used to estimate the frequency of accidents. The influence of pump cost on the safety and location of the equipment is determined. Under the consideration of the case study, pumping costs could represent more than 40% of the total annual cost. Safe distributions can be generated without considering the cost of pumping within the optimization, but according to the results of this work operating costs could be up to 80% higher when such cost is included. Multi-objective optimization allowed to find the best solution for this problem. [Display omitted] • Process layout multi-objective optimization. • Effect of pumping cost on equipment distribution and safety. • Safety criteria consideration on biodisel layout optimization. • The optimization model minimizes the domino effect risk on biodiesel production. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic evolutionary model to quantify the domino effect of ship engine room fires. Based on the spatial and temporal characteristics of fire accidents, the dynamic probability of the domino effect of multiple accident units is calculated using matrix calculation and Monte Carlo simulation. The uncertainties of shipboard personnel, automatic detection systems, sprinkler systems, and the synergistic effects of multiple escalation vectors from different units are addressed. The dynamic probability of the domino effect of multiple accident units is calculated, and a risk assessment of complex fire scenarios in ship engine rooms is implemented. This study also presents the model feasibility in terms of fire risk assessment in cabins with numerous pieces of equipment. The results indicate that 2 min and 4 min are vital time nodes for the development and spread of fires. The extinguishing work on key equipment in the path of the fire's spread can effectively restrain its further expansion. The results can provide critical references for ship fire prevention, fire suppression, and fire protection design. [ABSTRACT FROM AUTHOR]

One of the areas most affected by the occurrence of fires and explosions is the economy. These accidents lead to direct economic damages, which results in the withdrawal of capital for the reconstruction of damaged areas. In addition, there are other indirect economic losses, such as business interruption and reputational losses. The DOW Fire and Explosion Index (F&EI-DOW) is currently the most complete methodology for quantifying economic losses. Notwithstanding, the F&EI-DOW focuses on quantifying the hazardous potential of process units, and, does not provide an overall criterion for the hazardous potential of the entire industrial site with regard to: the inclusion of the so-called domino effect, the probabilistic risk assessment, the updating of existing risk analysis tools with new emerging Artificial Intelligence Techniques, and the quantification of reputation losses. For this purpose, the development of a new Fire and Explosion Economic Losses-Index (FEEL-Index) is proposed, which integrates the F&EI-DOW with new factors, such as the Damaged Area Factor , the Accident Probability Factor and the Reputation Loss Factor. With regard to the application to a case study, the total losses quantified by the overall FEEL-Index predict a value higher than the one predicted by the F&EI-DOW. The results obtained on an hydrocarbon storage case study show that the application of the FEEL-Index is relevant for increasing the risk perception, as well as providing guidance for prevention, mitigation, and risk management of accidents in process industries. [Display omitted] [ABSTRACT FROM AUTHOR]

1970'lerde dünyanın ilgisini çeken Batı ülkelerindeki büyük kazalar, kimya ve petrokimya sektörlerinde ve kümelerinde iç ve dış domino etkilerine yönelik araştırmalar için başlangıç noktasıdır. Başlangıçta, bu araştırmalar devlet kurumları ve hükümetle ilgili araştırma merkezleri tarafından yayınlandı. 1970'lerde ve 1980'lerde artan nicel risk analizleri ve Hollanda'da basılan “renkli kitaplar”, domino etkilerinin nicelleştirilmesinde önemli bir rol oynamaktadır. İkinci Avrupa Seveso Direktifi, 1990'ların ortalarından sonra konuyla ilgili akademik yayınların ve domino etkileri üzerine bilimsel araştırmaları önemli ölçüde artmasını teşvik etmektedir. Batı ülkelerindeki araştırmalara risk değerlendirmelerinde olasılıklar hakimdir ve karmaşık domino etkileri ve sonuçları için başarısızlık mekanizmaları hesaplanır. Önceki çalışmalar siyasi, resmi ve özel karar alma ile yakından ilgilidir. Risk yönetimine geçiş henüz emekleme aşamasındadır. Domino etkilerinin başlangıç noktalarındaki ilk senaryoları anlamak için gelecekte olabilecek süreçlere bir geçiş gereklidir. Hindistan'da 1990'ların ortalarında domino etkileri için bir farkındalık çağrısı yapıldı. Uluslararası bilimsel literatürde domino etkileri üzerine Çin yayınları, 2000'lerin ortalarından itibaren ortaya çıkmaktadır. Çin’deki hızlı sanayileşme nedeniyle, sektördeki birçok büyük kazayla kıyaslandığında diğer kimya şirketlerine göre çok fazladır. Bu derleme çalışmasında, 1966-2018 döneminde domino etkileri üzerine yapılan araştırmaların sonuçları, bu kaza süreçlerinin ana belirleyicileri ve bu alanda gelecekteki olası geçiş tartışılmıştır.

The current research on individual risks mainly focuses on the individual risk considering a single fire or the spatial distribution of multiple fires. It is more realistic to study spatial and temporal variations of individual risks. Based on the probit model, an improved approach is presented to assess the spatial and temporal variations of individual risks considering synergistic effects of multiple fires occurred sequentially. Firstly, the evolution sequence of multiple fires is estimated based on the probit model and the dynamic heat radiation distribution is calculated based on the Mudan model. Then, the critical heat radiation dose thresholds of different casualty levels are acquired based on literature data and the probit model which is applied to evaluate the relationship between heat radiation and the casualty level. Finally, the critical casualty time is proposed to reflect the temporal and spatial variations of individual risks. The dynamic individual risks of different escape strategies are assessed to assist in choosing the optimum escape plan. Furthermore, the critical safety escape distance is presented as a warning to provide a reference for the closest distance from firefighters to the center of the fire source. In the case study of multiple fires occurred sequentially in a storage tank farm, the critical casualty times of different casualty levels, the dynamic individual risk during the escape of a person, and the critical safe escape distance are estimated. Due to the low computational load, this approach can also assist in emergency decision-making at the fire accident site. [ABSTRACT FROM AUTHOR]

• A new method to predict the evolution sequence of domino accidents. • The method focuses on the uncertainty in the spatial-temporal evolution process of the domino effect. • The method is more comprehensive compared to existing models. • Prediction results can provide decision support for emergency response. 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. [ABSTRACT FROM AUTHOR]

• Method for uncertainty propagation in domino effect risk assessment modeling. • Improve evidence theory based on the stress-strength interference model. • Cumulative distribution function of failure time and escalation probability. • Sensitivity of parameters to uncertainty of risk assessment results. • Effect of fire temperature control on domino accident risk. The severity and complexity of fire-induced domino effects have received widespread attention. The spatial and temporal evolution process modeling of domino accidents is still stuck in single crisp value, in which the uncertainty will affect the reliability of the results. In this paper, we propose a computational method for uncertainty propagation of the evolution process modeling of the domino effect called Uncertainty Propagation of Domino Evolution Model (UPDEM), aiming to increase the reliability of risk assessment results. The method is capable of obtaining ranges and corresponding probability envelopes for tiame to failure and escalation probabilities, and quantifying uncertainty for all computational models that require input parameters. The uncertainty is quantified based on the evidence theory and a parameter cropping method based on the stress-strength interference model is proposed to optimize the evidence theory. The proposed method is applied to a case study and compared with previous studies. The comparison confirms that the results are more reliable after considering uncertainty and can produce the worst possible scenario consequence. Conducting the sensitivity analysis to prioritize the treatment of parameters and identify effective measures in risk control. The methodology can provide an important reference for decision-makers to prevent and control domino effects. [ABSTRACT FROM AUTHOR]

High complexity and growing interdependencies of chemical and process facilities have made them increasingly vulnerable to domino effects. Domino effects, particularly fire dominoes, are spatial-temporal phenomena where not only the location of involved units, but also their temporal entailment in the accident chain matter. Spatial-temporal dependencies and uncertainties prevailing during domino effects, arising mainly from possible synergistic effects and randomness of potential events, restrict the use of conventional risk assessment techniques such as fault tree and event tree. Bayesian networks—a type of probabilistic network for reasoning under uncertainty—have proven to be a reliable and robust technique for the modeling and risk assessment of domino effects. In the present study, applications of Bayesian networks to modeling and safety assessment of domino effects in petroleum tank terminals has been demonstrated via some examples. The tutorial starts by illustrating the inefficacy of event tree analysis in domino effect modeling and then discusses the capabilities of Bayesian network and its derivatives such as dynamic Bayesian network and influence diagram. It is also discussed how noisy OR can be used to significantly reduce the complexity and number of conditional probabilities required for model establishment.

In order to select the location of fire stations more scientifically and improve the efficiency of emergency management in chemical industry parks (CIPs), an improved risk calculation model for hazardous chemicals has been proposed by taking the domino effect and the identification of major hazardous installations for hazardous chemicals into account. In the analysis of the domino effect, the Monte Carlo simulation was used. Then, a location model of the fire stations was established with the optimization objectives of minimizing total cost and maximizing total risk coverage. The solving procedure of the location model is based on the augmented ε-constraint method combined with the TOPSIS method. Finally, a green chemical industry park was used as a case study for the validation and analysis of the location model. The results showed that the improved model could protect the high-risk areas, which is beneficial for the location decisions of fire stations.

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With Russian troops gathering at the Ukrainian border at the time of writing, Europe and the West are facing a real possibility of a full-scale continental war unprecedented for our generation. The purpose of this paper is to bring forth arguments that the security in the Black Sea area is of vital importance for both the present and future developments in the entire continent. Most recent studies on this topic focus on Russia's intentions in Ukraine and the weak responses coming from the West. Scholars are divided when it comes to Mr. Putin's ultimate goals. While some view the recent developments as a bluff, others are concerned that the troop movements might pave the way for a full invasion of Ukraine which will lead to a domino effect. This paper will focus on qualitative analysis. Mr. Putin's and Russia's intentions in the Black Sea will be analyzed from primary sources (such as Presidential speeches), while scholarly articles, research papers and policy documents will be used to build a bridge between history, politics and current affairs. The focus will be to establish the extent to which the recent developments in the area are a prelude to an 'old' Russian dream of access to the Mediterranean. A compare and contrast approach to appeasement will be used in order to make predictions on the possible outcomes. Our results will show that Mr. Putin is using the Black Sea security as a bargaining chip in his confrontation with the West with the ultimate goal of gaining dominance in the Mediterranean space. This paper will contribute to the recent literature on Eastern European security and how the West continues to misinterpret the dynamics and history of the region. [ABSTRACT FROM AUTHOR]

Synergistic effects of pool fires in fire-induced domino accidents can result in greater damage than single pool fire. Existing research mainly adopts a superposition method based on simplified assumptions to analyze the contribution of synergistic effect of pool fires for domino effects. Therefore, the synergistic effect of pool fires has not been well understood. In this study, a new CFD-based method is developed to model the synergistic effect of pool fires. Case studies were carried out taking double pool fires as an example. The influence of key factors, including wind speed, vertical fire location, fuel type, and separation distance has been investigated quantitatively. The results demonstrated that the proposed CFD based approach can model the consequences of pool fires more comprehensively and assess the domino effects under synergistic effect more precisely than the traditional superposition method. Compared with the single pool fire, the synergistic effect of double pool fires can increase the probability of domino accidents for the adjacent tanks at the downwind by six orders of magnitude. In addition, it is observed that the received maximum radiation heat flux and escalation probability of the target tank in the downwind direction rise with increased wind speed. While the maximum radiation heat flux received by target tanks and escalation probability reduced with increased separation distance and vertical fire location. Moreover, according to the minimum safety distance recommended by present design standards, the synergistic effect of double pool fires in diesel storage tank farms will lead to a higher escalation probability of near equipment than gasoline storage tank farms. This study can be used to predict accident consequences and assess the domino effect under the synergistic effect of pool fires, and guide the layout optimization of the chemical storage tank area. [ABSTRACT FROM AUTHOR]

Fire‐induced domino accidents are less probable but highly consequent. Although past studies conducted risk assessment of such events, classical models were used for impact estimation. Moreover the influence of varying weather on evolution of fire domino effect was not investigated, where past research necessitates the use of computational fluid dynamics to perform such analysis. This paper adopts a consolidated risk analysis approach to perform consequence modeling using fire dynamics simulator. Various atmospheric conditions were incorporated in the model. The outcomes were used in probabilistic analysis to estimate the escalation probabilities. Risk of domino events was presented as domino levels. It was found that 37% reduction in humidity ratio resulted in 10% decrease in tanks failure time. At 3 and 6 m/s winds, the failure time of tank in flame direction reduced by 56% and 80%, whereas the escalation probability increased by 3 and 4 orders respectively. The tank farm failed in 11.3 and 12.85 min at 3 and 6 m/s respectively, which is less than the suggested mitigation time. [ABSTRACT FROM AUTHOR]

The interaction between dysfunctional customers and other customers can cause the domino effect (i.e., the dissemination of a dysfunctional client’s behavior to other nearby clients). However, it is not understood if this effect will manifest under certain levels of damage to the company. This study thus aims to verify if the amount of damage from the dysfunctional behavior can affect the probability of the domino effect. Through five experimental studies, we prove that the amount of damage influences the likelihood of dysfunctional behavior replication. Moreover, we found that this effect is explained by the acceptability of the dysfunctional behavior. We also identify that a consumer’s ethics level, perception of risk in replicating the behavior, and social distance acts as boundary conditions of the amount of damage effect on the probability of replicating the dysfunctional behavior.