Risk Of Domino Effects Research Articles

Agent-based risk modeling of domino effects in urban LNG stations

As the transfer hub between natural gas and users, urban LNG stations (ULSs) are the important link of the whole LNG industry chain. Due to special geographical location and various process equipment, potential risks in ULSs, especially domino effect accidents, usually lead to catastrophic consequences and social impacts. In this study, a dynamic risk assessment model for analyzing domino effects in urban LNG stations (DRADL) based on agent modelling and simulation is proposed. Tanks and tank cars as well as vaporizers and boilers in ULSs are modeled. A set of physical process and effect models are employed as the simulation process in this paper. Considering the lightweight nature and narrow flammability limit of LNG vapor cloud, a cyclic process is applied to judge the consequences of vapor cloud dispersion, which could avoid overestimating the results. A real urban LNG station is taken as a case study for modeling its potential domino effect risk. The results demonstrate the effectiveness and the advantages of the proposed ABMS approach for LNG dynamic risk assessment. The proposed DRADL model takes into account the combined effects of explosion and fire and LNG characteristics, which can provide guidance for risk management and rescue operation of domino effect accidents in urban LNG stations.

Optimizing safety barrier allocation to prevent domino effects in large-scale chemical clusters using graph theory and optimization algorithms

Domino effects are high-impact low-probability events that can have catastrophic consequences. To prevent and to reduce risks related to such events, safety barriers (SBs) are crucial. However, the initiation, propagation, and stopping processes of domino effects are characterized with complexity and uncertainties and hence they are unpredictable. This makes it challenging to allocate SBs based on predicted probabilities. In this study, a multi-objective optimization model which integrates graph theory with Non-dominated Sorting Genetic Algorithm II (NSGA-II) was proposed to allocate add-on SBs effectively. Graph metrics were used to quantify the escalation risks related to storage tanks and to optimize the allocation of add-on SBs, thereby minimizing the consequences of a domino effect under a budget constraint. The results of the case study demonstrate great efficiency in finding globally optimal strategies with a largest reduction of 94.3% in the out-closeness score due to the implementation of add-on SBs, allowing decision-makers to choose the most preferable investment strategy in face of domino effect risk. Our study therefore provides a novel approach to achieve an optimal allocation of add-on SBs globally and can be useful in preventing domino effects in large-scale chemical clusters equipped with a large number of storage tanks.

Buckling failure analysis of storage tanks under the synergistic effects of fire and wind loads

Fire-induced domino effect is one of the main threats to hazardous material storage tanks, and many attempts have been conducted to assess the vulnerability of storage tanks exposed to fire to evaluate domino effect risk. However, past research ignored the influence of wind load on the thermal buckling behavior of storage tanks exposed to fire, which may underestimate the risk of exposed tanks. This paper thus conducts a numerical simulation of the thermal buckling behavior of steel vertical dome storage tanks under the synergistic effect of static wind loads and thermal effects. The effects of wind parameters and heat radiation parameters on the thermal post-buckling behavior and the time to failure (ttf) of storage tanks are investigated to analyze the synergistic effects of fire and wind loads. By comparing the circumferential and meridional stresses before and after the thermal post-buckling stage, it is found that under the disturbing effect of the positive wind pressure load, the thermal post-buckling of the tanks on downwind occurs earlier and more severe. Besides, the effects of wind angle, fire location height, and diameter on buckling damage were investigated. The comparative analysis of different scenarios shows that the tanks in the windy scenario are more prone to thermal post-buckling, and the deformation is intensified, with an increased likelihood of failure.

Optimization of firefighting strategies in process plants with emphasis on domino effects and safe evacuation

AbstractEffective 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.

Modeling and analysis of domino effect in petrochemical storage tank farms under the synergistic effect of explosion and fire

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.

Numerical Simulation of Chemical Storage Tank Area Leakage and Explosion Accident Based on FLACS

The large amount of oil storage tank possesses significant risks of leakage, and once leakage occurs, the combustible gas is prone to fire and explosion accidents. When the combustible gas cloud is exposed to the ignition source, there are possibilities of triggering the domino effect with more serious consequences. As one important kind of protective layers, the combustible gas detectors continuously monitor the leakage of combustible gas, guaranteeing the safety performance of the site. Using the computational fluid dynamics software FLACS as a tool, the impact of the consequences of the raw material leakage with a vapor cloud explosion accident in a large chemical fiber manufacturer's storage tank area is studied, and the risk of domino effect in the tank area during the course of the accident is predicted. The study shows that FLACS can be applied to the simulation study of gas diffusion explosion phenomenon in complex operation and storage areas, with the great capability of the explosion risk quantitative assessment and the reliable prediction to the risk of domino effects.

Multiobjective optimization of process equipment distribution: Effect of pumping cost

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.

Vulnerability assessment method for domino effects analysis in chemical clusters

Chemical clusters are attributed with large inventories of hazardous materials whose release could result in catastrophic events, as observed in the Tianjin Port accident. Such events are typically high-impact low-probability (HILP) accidents since multiple robust safety barriers can significantly ensure the integrity of installations. However, the consequences are extremely serious if the safety barriers broke down due to disaster factors. The current risk assessment methods cannot capture the complex multi-hazard scenarios and the interaction of escalation factors causing domino effects. To overcome such gaps, the present study proposes a quantitative vulnerability assessment method for multi-hazard scenarios triggered by natural events. The vulnerability assessment method considers the exposure of hazards, the sensitivity of causes, and the resilience of asset in modelling the primary event and the possible domino accidents. The proposed method assists in analyzing the risk of domino effects triggered by natural disasters and optimizing the deployment of safety barriers in chemical clusters. The application of the method is demonstrated through a detailed case study.

Analysis and Prevention and Control System of Domino Accident Risk Data in Chemical Parks Based on Topological Neural Network.

A topologically based neural network algorithm is used to conduct an in-depth study and analysis of domino accident risk data in chemical parks, and this is used to construct a prevention and control system applied to the safety prediction of chemical parks. Firstly, the operating model of the flue gas turbine is expanded and analyzed according to the basic theory of topology, and the object element model is constructed to determine the feature vector and potential risk level. Then, the idea of differential evolution is introduced into the topological neural network to solve the problem that the learning rate and weighting coefficients are difficult to determine, and then the complete DE-ENN algorithm is proposed and tested with the UCI standard data set to verify the effectiveness of the algorithm. Finally, the algorithm is applied to the potential risk identification of the smoke machine operation model, and the experimental results show that the method not only has a simple structure, short running time, and high prediction accuracy but also has excellent generalization ability. For the inherent risk and domino effect risk of chemical equipment in chemical fiber enterprises, the accident risk assessment method based on the protection layer analysis method is proposed; combined with the probability of domino accident and personnel vulnerability model based on the comprehensive analysis of the research results of the allowable risk standard, the allowable risk standard applicable to chemical fiber production enterprises in China is proposed. Given the potential accident risk characteristics of chemical fiber production enterprises, the calculation method of firefighting demand and firefighting capacity of firefighting system is given; the index system of firefighting system emergency response capacity assessment is constructed from three aspects of firefighting system integrity, reliability, and effectiveness, and the assessment model and grade classification standard of firefighting emergency response capacity of chemical fiber production enterprises are determined.

A cost-effective optimization model of safety investment allocation for risk reduction of domino effects

In general, the allocation strategy of safety measures in the domino effect is based on technical standards or simplistic rules of thumb, often leading to a subjective and uncertain decision-making process. In this work, a cost-effective risk reduction optimization model is proposed to objectively allocate the safety investment concerning domino effects in view of the risk and economic cost. Different from previous safety barrier performance assessments, we directly relate risk to economic cost through mathematical functions to trade off the economic effectiveness and domino effect risk under lower uncertainty. Not only mitigating measures, but also preventive measures are considered for domino risk reduction in the decision-making process of safety investment allocation in practical applications. The results from the case study demonstrate that the proposed model can help decision makers to identify the optimal safety investment among different investments and find the optimal investment allocation strategy given a specific economic investment in the worst-case domino scenario.

Application of data mining to minimize fire-induced domino effect risks.

Data mining (DM) has been applied in many advanced science and technology fields, but it has still not been used for domino effect risk management to explore minimum risk scenarios. This work investigates the feasibility of DM in minimizing the risk of fire-induced domino effects in chemical processing facilities. Based on DM, an evidential failure mode and effects analysis (E-FMEA), which could bridge chemical facilities' operational reliability and domino effect risk, is combined with fault tree analysis (FTA) for the occurrence risk modeling of loss of containment (LOC) event of chemical facilities, which is often the triggering point of fire-induced domino effects. Industry specific data such as reliability data, inspection records, and maintenance records are of great value to model the potential occurrence criticality of LOC. The data are used to characterize the LOC risk priority number (RPN) of chemical facilities through FTA and E-FMEA, search and statistics rules are proposed to mine inspection records to assess LOC risk factors. According to the RPN scores of facilities, inherent safety strategies to minimize risk via inventory control are proposed, and their effectiveness is tested using a well-known probit model. In this way, the approach proposes a unit-specific evidence-based risk minimization strategy for fire-induced domino effects. A case study demonstrates the capability of DM in the risk minimization of fire-induced domino effects.

A dynamic domino effect risk analysis model for rail transport of hazardous material

Rail transport of hazardous material (RTHM) plays a vital role in the supply chain of raw materials and products. However, RTHM can pose severe risks due to the large quantities of flammable and explosive chemicals transported over rail tracks crossing residential and industrial areas and possible human and technical failures. Among the potential safety issues, the domino effect is one of the most feared events, which can have devastating consequences despite its relatively low probability. As the first study, the present investigation develops a dynamic risk analysis model for analyzing domino effects in RTHM based on Dynamic Bayesian Network. Accident scenarios such as pool fire, flash fire, fire ball, vapor cloud explosion, and BLEVE are considered to analyze domino effects. The model performance is tested on a real RTHM (i.e., gasoline transportation), demonstrating the effectiveness of the proposed model in simulating the domino-driven effects in terms of both consequences and probability escalation and in dealing with the parameter and model uncertainties.

Fire resistance of a vertical oil tank exposed to pool-fire heat radiation after high-velocity projectile impact

Due to the complex effects of combined loadings on complete steel structures, the combined effects of high-velocity projectile impact and heat radiation due to a pool-fire on a vertical Q345 steel tank have not been generally considered. In this study, a consecutive coupling approach is established. The combined effects of projectile perforation and heat radiation on the failure modes and fire resistance of a vertical steel tank are investigated. Additionally, the effects of the projectile size, projectile shape, and separation distance are analyzed. The results indicate that compared with a fixed-roof tank without impact, the perforation results in stress concentrations in the plastic deformation zone. The stress level of the perforated tank is higher, and the fire resistance of the perforated tank is lower. Additionally, as the perforation size increases, the stress level triggering the thermal buckling of the perforated tank decreases outside of the plastic deformation zone. Additionally, the fire resistance decreases. Moreover, as the separation distance decreases, the stress level of the cylindrical shell increases. The fire resistance of the perforated tank decreases dramatically. By understanding the failure mode, this study is able to suggest fire and explosion protection measures in petrochemical industries to decrease or eliminate the domino effect risk and incident damage. Additionally, the fire resistance data can help improve guidelines and understanding for fire and rescue services, which would undoubtedly play a vital part in emergency response and rescue, and enhance the process safety level overall.

Interacting tipping elements increase risk of climate domino effects under global warming

Abstract. With progressing global warming, there is an increased risk that one or several tipping elements in the climate system might cross a critical threshold, resulting in severe consequences for the global climate, ecosystems and human societies. While the underlying processes are fairly well-understood, it is unclear how their interactions might impact the overall stability of the Earth's climate system. As of yet, this cannot be fully analysed with state-of-the-art Earth system models due to computational constraints as well as some missing and uncertain process representations of certain tipping elements. Here, we explicitly study the effects of known physical interactions among the Greenland and West Antarctic ice sheets, the Atlantic Meridional Overturning Circulation (AMOC) and the Amazon rainforest using a conceptual network approach. We analyse the risk of domino effects being triggered by each of the individual tipping elements under global warming in equilibrium experiments. In these experiments, we propagate the uncertainties in critical temperature thresholds, interaction strengths and interaction structure via large ensembles of simulations in a Monte Carlo approach. Overall, we find that the interactions tend to destabilise the network of tipping elements. Furthermore, our analysis reveals the qualitative role of each of the four tipping elements within the network, showing that the polar ice sheets on Greenland and West Antarctica are oftentimes the initiators of tipping cascades, while the AMOC acts as a mediator transmitting cascades. This indicates that the ice sheets, which are already at risk of transgressing their temperature thresholds within the Paris range of 1.5 to 2 ∘C, are of particular importance for the stability of the climate system as a whole.

A novel approach to reduce fire-induced domino effect risk by leveraging loading/unloading demands in chemical industrial parks

Due to complexities and uncertainties, risk management of domino effects in chemical plants in operation is challenging. A global optimal risk management scheme can hardly be obtained, therefore, finding a targeted local optimal risk management scheme can be prudent. In the present study, a novel risk management approach is proposed to reduce fire-induced domino effect risk by leveraging loading/unloading demands based on risk aggregation and inventory management. The proposed approach uses the aggregation of three risk indicators as part of the risk management strategy. The first risk indicator is the loss of containment (LOC) risk of chemical installations, which indicates how likely a storage tank may cause a primary fire accident. The second risk indicator is the secondary fire accident inducing ability of chemical installations, which indicates how likely a primary tank may cause secondary fire accidents only. The third risk indicator is the inter-unit closeness degree of chemical installations, which indicates how severe the overall consequence a primary tank may cause. Combining the aggregate risk with the inventory availability of storage tanks, candidate risk management schemes are proposed based on inventory management on chemical loading/unloading demands. The optimal risk management scheme is determined based on the potential losses of fire-induced domino effects. A case study demonstrates the effectiveness of the proposed methodology and risk management strategy for fire-induced domino effects.

A novel approach for domino effects modeling and risk analysis based on synergistic effect and accident evidence

Modeling the spatial-temporal evolution of domino effects and analyzing its risk could guide risk prevention and control. In the present work, a novel approach is proposed to model the spatial-temporal evolution and perform a risk analysis of fire-induced domino effects based on synergistic effect and accident evidence. The approach takes fire accident evidence into account to model the synergistic effect of burning units. The receivable thermal dose is adopted as the failure criterion of endangered units to consider heat energy accumulation. The time to failure and escalation probability are used to assess domino effect risk. The proposed approach is effective to model the dynamic evolution of accident propagation, and the results provide a visible image of domino effect evolution and associated risk, and also the results are helpful to identify the most vulnerable unit and the most dangerous units. A case study is illustrated to demonstrate the credibility and applicability of the proposed approach.

Influence mechanism of congestion degree of layout on domino effect in petrochemical plants

The study focused on the establishment of the congestion degree in describing the layout of process plants, and discovering the influence mechanism of congestion degree on the risk of domino effect, in view of the fact that the congestion degree has not been used to represent the characteristics of petrochemical plant layout. A characterization model was built for the congestion degree of process plant layouts applying the theory of fuzzy model that it took safety distance, the amount of materials involved and the hazard of these substances into consideration, and came out with a membership function through logical calculus, which made congestion degree a comparable data. Secondly, a systematic domino effect risk analysis method was generalized on account of domino effect quantitative risk analysis method which include the equipment damage probability, the domino effect occurrence probability, risk analysis based on the consequences, individual risk index and social risk index, the process plant natural risk index and real risk index, and then these indices were compared to select the most suitable ones to illustrate the risk of domino effect and to research about part of the storage tank field of a petrochemical plant. Finally, the influence mechanism of layout congestion degree on domino effect of regional accident was obtained through this quantitative analysis. Simultaneously, a range of the congestion degree was acquired according to the individual risk index which can be used as a reference in the design stage of the process plant. The result proved that high congestion degree in process plant greatly increased the risk of domino effect in most of the quantitative risk analysis index, such as the probability of resulting in secondary accidents, the harm on both human and the equipments caused by the initial accident, and the individual risk and social risk, etc. The characterization models for the congestion degree and the domino risk analysis method established and summarized in the study have been applied in the design stage of process plant layout to optimize the layout, and thus reduce the risk of domino effect caused by accidents.

Investigation on the Screening Model of Chemical Hazards Based on the Risk of Domino Effect and Terrorist Attack

The heavy losses are often caused in modern chemical plants at the time of the accident. In order to prevent accidents, the screening and identification of hazards is needed. In this paper, the screening model of hazards in chemical plants was studied under the domino effect and the risk of terrorist attack. According to the threshold and strength of the domino effect of the unit under the main accident scenarios, the index of domino effect was developed. The risk index of terrorist attacks was determined in line with the distance between the unit and the boundary under the assumption of terrorist attacks. The hazards screening model Z was designed based on two aspects of the study. The model was applied in screening the hazards. The results showed that closer units near the border were more dangerous under the risk of terrorist attack, and the devices surrounded by units with greater influence of accidents were more dangerous under the risk of domino effect. The indices of the tanks were ordered: Z105>Z101>Z103>Z106>Z104>Z102>Z201>Z202>Z203>Z204>Z205>Z206>Z303>Z304>Z301>Z302>Z306>Z305. The domino effect and the risk of terrorist attacks were combined into the present model for perfection and correction of the existing hazards screening model, as the new basis for major hazards identification.

Investigation of the influence of the projected proportion of a burst vessel on the hazard caused by fragments

The effects of the projected proportion of a blast tank on the ground distribution of fragments, the probability of impact with a target, the rupture probability of the impacted target, and the risk of domino effect were investigated using Monte Carlo simulation. The results showed that the number of fragments between the actual projected ranges derived without considering the projected proportion was much larger than that obtained considering the projected proportion. The fragments were projected to large distance up to 1200 m based on the historical explosive vessels. The probability of fragment impact derived considering the projected proportion was lower than the corresponding one obtained without considering the projected proportion at each value of distance. The rupture probability of the target depended very little on the projected proportion of the blast vessel, but the risk of domino effect was influenced by the projected proportion. Hence, the effect of the projected proportion of the burst vessel on the risk of domino effect was found to be significant.

PARADIGMS OF EUROPEAN INTEGRATION PROCESSES IN THE EU, VISEGRÁD GROUP, AND UKRAINE

The scientific interest of the development of the theory and practice of cooperation of Central European countries of the Visegrád Group in the context of modern European integration processes is important for developing and implementing the strategy of foreign and domestic policy in European countries and Ukraine at the modern stage. At the beginning of the XXI century, under the changes in the geopolitical situation on the European continent, the countries of Central Europe (full members of the European Union) build a new operating system of international relations and accordingly continue to delegate some of their powers to suprastate institutions of the EU. The purpose of this scientific study is to determine paradigmatic aspects of European integration processes, modern threats arising in the EU, prospects for the interaction of EU countries, and to form a new format of cooperation of Ukraine and countries of the Visegrád Group. The aim of the creation of the alliance of the Visegrád Group (1991) was the desire to contribute to the construction of European security architecture and economic cooperation through the effective cooperation within European institutions. The whole activity of the Visegrád Group is aimed at strengthening stability in the Central European region. Risks in the economic sphere and strengthening of Euroscepticism are considered traditional for the EU functioning. In view of signing the Rome Declaration in 2017, the EU threats and challenges for the short-term (2018–2020) include: hybrid consequences of the aggression of the Russian Federation in Ukraine, European migrant crisis, a series of terrorist acts in European cities, unpredictable policy of the newly elected US president D. Trump in relation to the European security system, strengthening the position of far-left and far-right political forces in European states, Brexit and its consequences, in particular, risk of domino effect in other member countries of the Union. Therefore, we consider it appropriate to carry out system analysis of key relevant challenges and threats to the EU for 2018–2020 and to consider interconditionality and interdependence of problems that may affect the EU future. Given the defined trends, development and economic stability of each state are strategically important, however, special attention in this context should be paid to the analysis of the development of large countries of the European Union, such as Poland, Czech Republic, Slovakia, and Hungary. V4 countries are characterized by sustainable economic growth. If to analyse the Visegrád Four as a single national state, then the Visegrád Group is the fifth largest economy in Europe and the 12th in the world. The authors consider it too simplistic to define the essence of the Visegrád alliance only as a consolidation of the efforts of Central European countries for the sake of “returning to Europe” through Euro-Atlantic integration. In the modern dimension of events, the interaction format V4 + Ukraine is much more complex and more promising than it appears. Since joining NATO and the European Union in 1999 and 2004 by the Visegrád Group (i.e. Central European countries) geopolitically changes the status of the Central European Region, transforms bilateral and multilateral relations of Central European countries – full members of the EU with Ukraine. Moreover, this changes the system of relations within the Visegrád Four, as well as with other member states of the European Union.