Accident Process Research Articles

A method for the core accident chain based on fuzzy-DEMATEL-ISM: An application to aluminium production explosion

The occurrence of accidents is often influenced by many factors, which result in the complexity of the causes of accidents. Therefore, clarifying the accident chain of the explosion accident is of great significance for the daily management of safety. In this study, a novel method of the core accident chain based on the traditional fuzzy-DEMATEL-ISM method was proposed. This method can clarify the importance of each accident chain and rank them accordingly by calculating their weighted centralities. Then, the explosion accident caused by the contact of molten aluminium and water, which has caused heavy casualties and property losses, is analyzed systematically. In order to clarify the impact relationships and hierarchical structure of the various factors in the complex explosion accident systems, and establish the accident system models, twenty-two factors were summarized, and the evolution process of explosion accident were obtained by the fuzzy-DEMATEL-ISM approach. The results reveal that equipment damage or failure has the most direct impact to the explosion accidents. The core accident chain that national policy (aluminium market demand)→incomplete safety management system→disordered on-site management→insufficient lighting→physical discomfort→improper operation→equipment damage or failure is obtained, which has the most significant influence on the occurrence of explosion accidents. The result analysis is employed to give some advice. This research is helpful for safety practitioners to develop accident prevention strategies and make aluminum production safer.

The design of intelligent highway transportation system in smart city based on the internet of things.

The design of intelligent expressway transportation system based on the Internet of Things is studied to improve the safety, travel experience, and operation management of expressway. The characteristics of the Internet of Things and cloud computing technology and its application on the expressway are analyzed, and the system design requirements of expressway intelligent transportation are understood. Besides, the overall architecture of the system is studied and designed. The IaaS layer, PaaS layer, and SaaS layer of the cloud platform are designed and deployed. The intelligent information system can make expressway highly informative. The simulation experiments reveal that the system only needs 120 milliseconds in accident processing time, which is far lower than the intelligent transportation system that only uses edge computing technology (201 milliseconds) and the intelligent transportation system that only uses cloud computing technology (443 milliseconds). Meanwhile, the accident response time is only 12s, which is also superior to other models. In terms of cost-effectiveness, the monthly cost of the system is 7004 yuan, with a CPU utilization rate of 53%, demonstrating good cost-effectiveness and resource utilization efficiency. In addition, compared with the existing system, the average traffic congestion time has been reduced by 25%, the traffic accident rate has been reduced by 18%, and the accident rate has been reduced by 27%. The intelligent traffic system design of expressway, expressway safety, travel service, and operation management is effectively improved by researching the intelligent traffic system design of expressway.

Optimization study of tail-lateral occupant injury and restraint system for an off-road vehicle ramp rollover

The process of rollover accidents involving specialized vehicles is characterized by intense motion and long duration. Although these accidents are infrequent, they often lead to a high fatality rate. In this study, we utilized LS-Dyna software to simulate the rollover of a vehicle on a side ramp. This simulation aimed to verify the reliability of our model establishment by comparing the vehicle’s motion attitude and center-of-mass acceleration with experimental results. Additionally, we sought to investigate the lateral occupant injuries that occur in the tail section of a certain type of specialized vehicle during a rollover. Initially, we obtained the vehicle’s motion trajectory and the dummy’s motion state through simulation. Subsequently, we extracted the injury response of each part of the dummy. We then simplified the entire vehicle model and made improvements to the occupant restraint system, ultimately designing an enhanced system. Finally, we approximated and replaced the entire vehicle model by establishing an approximation model. We combined this with an optimization algorithm to optimize the occupant restraint system. The simulation results demonstrate that the improved occupant restraint system significantly reduces the axial force on the neck of the occupant and the comprehensive evaluation index of injury. Furthermore, the simulation results for each component fall below the injury limit value specified in the FMVSS208 crash occupant protection standard. Therefore, the improved occupant restraint system proposed in this study effectively mitigates lateral occupant injury during rollover accidents.

A seafarers’ cognitive error mining model based on IDA and TRACEr and mitigation measures for ship collision accidents

Human factor is the main cause of maritime accidents. However, the in-depth study on the mechanism of cognitive errors in seafarers’ human error needs to be supplemented. This study empirically analyzes 116 collision cargo ships along the Yangtze River trunk line. To explore the relationship between seafarers’ task errors and the cognitive process of accidents, a seafarers’ cognitive error mining model is proposed, which integrates the Information, Decision, and Action (IDA) cognitive model into the Technique for the Retrospective and Predictive Analysis of Cognitive Errors (TRACEr). According to the approach of mining from the outside to the inside, firstly, the error mode in the cognitive stage of seafarer tasks are identified. Then the fine-grained main manifestation of the task errors is mined by K-means, and Apriori algorithm is employed to mine the hidden features between the external and internal error modes. The results show that there are four main problems of Yangtze River ship accidents, and seafarers have four to seven corresponding causal chains from psychological error mechanism to performance shaping factors for each major issue in the cognitive stage. On the basis of the results, this study summarizes the guiding principles of accident prevention and seafarer management measures to provide decision support for water traffic safety.

The preliminary design of emergency core cooling scheme and loss-of-coolant accident analysis for Tsinghua high flux reactor

This paper proposes the preliminary emergency core cooling scheme for Tsinghua High Flux Reactor. According to the thermohydraulic characteristics of high flux reactors, forced circulation needs to be maintained by emergency pumps in the early stage. When the decay power is low enough, natural circulation between core and the reactor pool is initiated to remove the residual core heat. The sources of safety injection are accumulators and reactor pool. Accumulator injection can ensure core safety in the early stage and reactor pool injection can maintain long time stable forced circulation. To avoid emptying the reactor pool, the waterproof zone needs to be built. The waterproof zone consists of reactor pool and several finite volume dry pools. All pipelines and equipment in the reactor coolant system are placed in the dry pools. Once break accident occurs, the dry pool where the break is located can collect the leaked coolant. With the increase of break back pressure, the break flow is restricted. The current scheme is modeled by Relap5 and different size breaks at four locations (namely core inlet, core outlet, primary heat exchanger inlet and main pump inlet) are assumed. According to the response characteristics of the scheme, the accident process can be divided into five stages: non-shutdown stage, high-injection stage, low-injection stage, stable forced circulation stage and natural circulation stage. Critical heat flux predicted by Sudo CHF correlations is adopted as the primary safety criterion. Through analysis, a success path is found to maintain core safety for a wide range of loss-of-coolant accident scenarios.

Experimental study on effect of pressure on ADS-4 liquid entrainment characteristics in T-junction

Liquid entrainment phenomenon can occur in the T-junction formed by the vertical ADS-4 pipeline and the hot pipe section during SBLOCA process in AP1000 reactor. At present, most of the studies on the liquid entrainment phenomenon in T-junction with large branch pipe concentrate on the atmospheric pressure condition, which is difficult to accurately reflect the real state of the accident process. The liquid entrainment experiments were carried out at 0.1–0.4 MPa on ADETEL facility. The results show that there will be obvious reverse flow phenomenon in the branch at 0.1 MPa and the phenomenon disappears gradually with the increase of pressure. Furthermore, the occurrence of intermittent two-phase slug flow in the horizontal tube was observed at lower pressures. As pressure increases, the entrainment process will become more continuous and stable, with a concomitant reduction in intermittency. The steady-state entrainment liquid level and the onset of entrainment liquid level both decrease with increasing pressure, indicating that increasing pressure can facilitate the liquid entrainment amount. The existing correlations cannot accurately estimate the entrainment amount during SBLOCA in nuclear reactor with a deviation of more than +100% between the predictions and experimental data.

Simulation of a Hazardous Chemical Cascading Accident Using the Graph Neural Network

In the storage of hazardous chemicals, due to space limitations, various hazardous chemicals are usually mixed stored when their chemical properties do not conflict. In a fire or other accidents during storage, the emergency response includes two key steps: first, using fire extinguishers like dry powder and carbon dioxide to extinguish the burning hazardous chemicals. In addition, hazardous chemicals around the accident site are often watered to cool down to prevent the spread of the fire. But both the water and extinguishers may react chemically with hazardous chemicals at the accident site, potentially triggering secondary accidents. However, the existing research about hazardous chemical domino accidents only focuses on the pre-rescue stage and ignores the simulation of rescue-induced accidents that occur after rescue. Aiming at the problem, a quantitative representation algorithm for the spatial correlation of hazardous chemicals is first proposed to enhance the understanding of their spatial relationships. Subsequently, a graph neural network is introduced to simulate the evolution process of hazardous chemical cascade accidents. By aggregating the physical and chemical characteristics, the initial accident information of nodes, and bi-temporal node status information, deep learning models have gained the ability to accurately predict node states, thereby improving the intelligent simulation of hazardous chemical accidents. The experimental results validated the effectiveness of the method.

Risk identification model of aviation system based on text mining and risk propagation

Due to the aviation accident is rarely predictable and often irreversible, how to ensure aviation safety is of uttermost importance. Textual aviation accident reports contain the cause and process of the accident which could help people understand incidents. However, the cause of the accident always is summarized by the expert and the accident report would be incomplete, the identification of aviation safety accident risk is not timely and accurate. In this paper, a safety risk identification model is proposed, aiming to identify the correlation between aviation safety accident risk factors by machine learning from textual aviation accident reports. In detail, the feature of aviation accidents is extracted and classified by text mining technology, on this basis, the correlation coefficient matrix between different features is established. Finally, the correlation network of aviation safety risk is proposed, and the risk propagation process of accidents is developed based on the network to identify aviation safety accident risk.

Study on the effects of accident-tolerant fuels on the safety of CPR1000 nuclear power plants

Abstract In this paper, CPR1000 Nuclear power plant was taken as the reference unit. According to CPR1000 Probabilistic Safety Analysis (PSA), the Large Break loss of coolant accident (LOCA), Medium Break LOCA, Small Break LOCA, Station Blackout (SBO), Total Loss of Feed water (TLOFW) and Anticipated transient without trip (ATWT) with Loss of Main Feed water (LOMF) were selected as the representative accident scenarios. The house holding deterministic programs LOCUST were used to analyze each of the above selected scenarios for five different accident tolerant fuels (ATF). The effects on accident process, reactor core damage time, system success criteria and personnel response time were analyzed under the above scenarios. The above results for the five ATF materials were compared to those for standard UO2-Zr in the same scenarios, then some useful conclusions were obtained which can be used to support ATF material selection. In the end, based on the deterministic calculations, the effects of different ATF materials on CPR1000 PSA results such as core damage frequency (CDF) were evaluated in detail with traditional PSA software Risk Spectrum. According to the results, ATFs have some advantages on core damage time, success criteria or operators’ action time window. But the CDF was changed little compared to standard UO2-Zr system. Through the studies, it is found the most important thing is that due to the much longer time windows some new plant modifications can be provided to mitigate the accidents which can contribute to the plant safety and decrease risk more.

Investigation and CFD simulation of coal dust explosion accident in confined space: A case study of Gaohe Coal Mine Ventilation Air Methane oxidation power plant

The study investigates a coal dust explosion accident within a confined space in Shanxi. The accident was caused by coal dust coming into contact with a high-temperature heat source under the influence of the stack effect. Based on the investigation of the coal dust explosion accident, the study uses computational fluid dynamics (CFD) simulation to reconstruct the accident scenario. The simulation results provide a detailed depiction of coal dust movement within subsurface semi-enclosed confined spaces during the ventilation diffusion stage, influenced by the stack effect, and confirm the formation of a coal dust layer at the heat source due to coal dust deposition. The simulation results of the two explosion processes indicate that excessively high coal dust concentrations within confined spaces have a negative correlation with the development of explosion flames and the peak overpressure. It resulted in a secondary explosion with a relatively low concentration of coal dust, where the peak overpressure was five times that of the primary explosion. Comparative analysis between simulation results and actual investigations the accuracy of the CFD simulation in capturing the accident process and its characteristics, providing valuable insights for preventing and controlling coal dust explosion accidents.

Ship accident re-enactment based on AIS data and virtual reality: a case study of “Xiang Xiang Yin Huo 0410” ship accident

Abstract The recurrence of ship accidents was an effective method of maritime investigation. To analyze the cause of the sinking of “Xiang Xiang Yin Huo 0410”, a vessel accident recurrence simulation system was constructed by integrating an automatic identification system and virtual reality technology to replicate the navigation and accident process of the accident vessel. The voyaging process of the accident vessel was reduplicated in the simulation system according to the AIS information, such as speed, course, and turning speed. The mathematical model of accident vessel maneuvering was established by using MMG to reproduce the ship maneuvering scheme based on the maneuvering data before the accident obtained through on-the-spot investigation. The navigation and sinking process of the accident vessel were reproduced visually, and the cause of the accident was judged and analyzed intuitively by constructing a three-dimensional model of the accident vessel and a mathematical model of ocean waves. The actual application indicates that the ship’s navigation and accident process under external force, combined with the ship’s maneuvering data, automatic identification data, and hydrometeorological data, was consistent with the actual accident process of the accident. The method proposed in this paper provided a new idea for the investigation and analysis of maritime accidents.

Quantitative assessment of human error of emergency behavior for hazardous chemical spills in chemical parks

In-depth research on human error is of great significance to improve the human reliability in the emergency rescue as well as to avoid the occurrence of secondary accidents. Therefore, the standardized process and key emergency behaviors in the emergency rescue process of hazardous chemical leakage accidents are first analyzed. Based on the Cognitive Reliability and Error Analysis Method, the human error mode was sorted out, and the human error probability estimation model was established. Combining the improved Analytic Hierarchy Process and entropy weight method, a model for estimating the severity of human error was established, realizing the quantitative analysis of the human reliability of the emergency behavior. The study showed that the 21 emergency behaviors were clustered into 3 categories, with clustering 1 including 2 emergency behaviors, which have the highest level of severity, clustering 2 including 11 emergency behaviors, and clustering 3 including 8 emergency behaviors. Finally, countermeasures were proposed in four areas, including increasing the level of Common Performance Conditions and the ability to transmit information on accidents, etc. It indicates that the method can widely guide the improvement of emergency response capability in chemical parks.

Research on the influence of emergency rescue information importance on emergency decisions

AbstractEmergency rescue information is a significant factor affecting emergency decisions in the accident process, and determining the content and importance of this information can greatly assist emergency decisions and improve their effectiveness. For this reason, this paper combines decision‐making trial and evaluation laboratory (DEMATEL) with a backpropagation (BP) neural network and uses the Levenberg‒Marquardt (LM) algorithm to optimize it, builds the LM‐BP‐DEMATEL model, and investigates the contents and importance of emergency rescue information with hazardous chemical spills as an illustrative case. First, the meaning of emergency rescue information was defined using national laws and regulations and academic research. Second, using hazardous chemical spills as an example, 62 hazardous chemical spills were collected, and 7 categories with a total of 32 emergency rescue information were extracted. Third, the constructed LM‐BP‐DEMATEL model was utilized to analyse the importance of 14 types of common emergency rescue information in 62 cases. Last, the centrality and causality of 14 types of emergency rescue information were obtained and then classified into four categories according to centrality and causality. The research results show that deaths (U8) and leakage information (U6) are the most critical emergency rescue information, that more attention should be given to emergency decision‐making and that targeted strategies should be formulated to improve the effect of emergency decisions.

Car Damage Detection with VGG-16

In today's traffic accidents, assessing the damage and keeping damage records quickly is necessary. It is crucial to accelerate damage assessment studies to prevent traffic congestion caused by accidents and open the road to traffic quickly. Deep learning technologies provide various advantages in calculating the magnitude of the damage, displaying the damage situation, and making inferences about the material extent of the damage. In this study, a decision support system is aimed not only for insurance companies or official institutions to see the results but also for the end user and to reveal the damage class of the accidents. The software offered aims to provide an objective perspective not only in accident processes but also in quickly determining the financial value of the vehicle when buying and selling the vehicle. In this study, the training phase of our VGG16-based model, a CNN sub-model, was developed on the data set we obtained from the Kaggle platform (5757 images). With VGG16, our vehicle object detection rate is 98%, the accuracy rate of whether the vehicle is damaged is 90%, the results obtained in the training in which we detect the damaged area is 70%, and finally, the accuracy rate in determining the level of damage (low, medium and high) is 66% has been obtained.

Analysis of the explosion risk of low-concentration oxygen-bearing coal bed methane in the low-temperature environment

In the process of deep cooling and liquefaction of low-concentration (concentration <30 %) oxygen-bearing coal bed methan, there is a risk of explosion because the methane concentration in the ultra-low temperature environment is within the explosion limit. It is of great guiding significance to study the occurrence mechanism and accident-causing process of such accidents. Firstly, the experimental system of low-temperature methane explosion characteristics is constructed, and it is found that when ignition energy exceeds a certain range, the process of deep cooling and liquefaction of low-concentration oxygen-bearing coal bed methane will cause explosion. Then, the occurrence of the gas explosion accident in low-temperature environment is briefly described, and the causes of the accident are analyzed preliminarily, and the dynamic characteristics of methane explosion propagation under ultra-low temperature conditions are studied by Fluent numerical simulation, and it is obtained that ultra-low temperature conditions have a promotion effect on the explosion pressure. Finally, based on the analysis of catastrophe theory, the traditional accident causation cusp catastrophe model is improved, and the “experimental safety state" and the “internal causes of explosion-external cause of explosion" are taken as the state variables and control variables respectively, and the explosion risk analysis model for deep cooling and liquefaction of low-concentration oxygen-bearing coal bed methane based on the cusp catastrophe theory is constructed. Based on the accident case, the process of accidents caused by risk factors is described, and the evolution mechanism of such disasters and accidents is clarified. Finally, the hazard state evaluation method for liquefaction explosion of low-concentration oxygen-bearing coal bed methane is proposed based on the catastrophe theory, and this evaluation model is applied to evaluate and analyze the hazard state of accident case. The evaluation results are consistent with the actual hazard state, confirming the rationality and feasibility of this evaluation method. In this paper, the key hazards of such accidents are found out in detail and provides support for safety decision-making in the deep cooling and liquefaction process of low-concentration oxygen-bearing coal bed methane.

Reflood oxidation performances of Cr-coated Zr-Sn-Nb alloy cladding tubes at 1000 °C∼1200 °C

Reflood plays an important role in preventing the serious accident process. In this paper, the reflood oxidation performances of Cr-coated Zr-Sn-Nb alloy cladding tubes at 1000 °C, 1100 °C and 1200 °C were studied by high-temperature steam oxidation followed by in-situ water quenching. The oxidation kinetics, macroscopic morphology, phase transformation and microstructural evolution were investigated. Cr coating can provide excellent anti-reflood oxidation protection for Zr-Sn-Nb alloy, resulting in an oxidation rate constant of only 1/4–1/7 of that of uncoated Zr-Sn-Nb alloys. However, the cladding tube degraded into fragments due to excessive thermal stress during the in-situ water quenching after reflood oxidation at 1200 °C for 4000 s. After reflood oxidation at 1000 °C and 1100 °C, the most prominent feature of the surface is a porous flocculation structure main due to the formation of volatile products, while after 1200 °C, it is a fine mackerel scale-like structure accompanied by protruding whiskers main owing to Cr3+ rapidly migrates outward to the outer surface via short circuit paths. After oxidation, the cross-section of Cr-coated Zr-Sn-Nb alloys exhibits a multi-layer structure. The thickness of each layer changes approximately linearly with oxidation time. However, due to the redox reaction, compared to that after oxidation for 2000s, the Cr2O3 layer becomes thinner and the residual Cr coating becomes thicker after oxidation at 1200 °C for 4000 s.

Simulated safety analysis of a total loss of feedwater accident in the steam generator of CPR1000 nuclear power plant

As M310 series units, CPR1000 Nuclear Power Plant in China is also the first batch of demonstration nuclear power plants in China to try out SOP(the state-oriented procedure) accident procedures. The establishment of SOP accident regulations is an important work to mitigate the consequences of radioactive accidents in the design of nuclear power plants, and it is also the embodiment of the defense-in-depth requirements in the implementation of nuclear safety regulations. It can handle superimposed accidents, human errors in program implementation and events not considered in the primary cause sequence. In order to study the efficiency of its upgraded SOP procedure and its ability to deal with severe accidents, the typical primary cause event of severe accidents in nuclear power plants–such as the total loss of feedwater accident of steam generators has been adopted for research. The initial state of the simulation is the full power operation of the nuclear power plant, the simulation process is from the loss of all the water supply accidents to the whole accident processing. A total of 30 simulation experiments were carried out. The temperature and pressure of the key parameters obtained are the average values of 30 simulation experiments. The stability and efficiency of the updated SOP are evaluated by the treatment time of the water supply loss accident and the changes of reactor temperature and pressure after the accident. The results show that the upgraded SOP procedure is more stable and efficient. The upgraded SOP procedure, when dealing with other types of accidents, has improved the treatment of residual heat conduction in the core, increased the efficiency of accident treatment, and enhanced the safety of the reactor. At the same time, based on the weaknesses of the upgraded SOP procedure, constructive suggestions on changing the setting value of the steam generator bypass valve have also been put forward accordingly. Furthermore, it can be concluded from many simulated accidents that this change will win about 5% more of the disposal time for nuclear power plants under accidents, which provides references for the subsequent upgrading of M310 series power plant procedures.

Analysis of Factors Affecting Road Transport Accidents of Hazardous Materials Based on PG-BN

To analyze the factors affecting road accidents involving hazardous materials, the Bayesian network (BN) model was used to fit the accident data. However, considering the possible overfitting phenomenon of the BN model, the model was optimised by combining Pearson’s chi-squared test and Granger causality test (PG) methods. First, the data of hazardous materials accidents were preprocessed, and the index system of factors affecting hazardous materials road transport was constructed from five dimensions of “people, vehicles, hazmat, roads, and environment”; second, Pearson’s chi-squared test and the Granger causality test were used to screen the factors affecting hazardous materials road transport accidents and to determine the causal relationship between the factors; finally, the BN model was constructed with accident severity and accident processing time as target nodes, and the results were analyzed and validated. The results show that the overall relative error rate of the model is less than 10% and can be used to explore the risk factors of hazardous materials transport accidents; weather, visibility, lighting, intersection type, road condition, road type, driver condition, vehicle type, etc. are all important factors affecting the severity of hazardous materials transport accidents. The study can serve as a reference for the safety supervision and management of hazardous materials transport enterprises and industrial management departments.

Cause analysis of secondary explosion accident in Hushan Gold Mine, Shandong Province, China based on HFACS-CM model

Explosion accidents often occur during mining, especially sudden secondary explosions, which pose a serious threat to the life and property safety of employees. Based on the development process and consequences of typical secondary explosion accidents in Hushan Gold Mine, Qixia City, Shandong Province, China, this paper uses accident analysis model and cone measurement calculation method to determine the direct cause of secondary explosion accidents. The main conclusions are as follows: The HFACS-CM model is used to analyze the causes of secondary explosion from five aspects: external environment, organizational influence, unsafe leadership, the prerequisite conditions of unsafe behavior and unsafe behavior. It is found that the CO ignition explosion in the mining process is the direct cause of secondary explosion. Then, combined with the experimental data of the cone measuring instrument, the field CO amount was calculated, and the MCO ≥ 101.4 m3 was obtained, indicating that the CO production did reach the condition of explosion range, and the analysis results of the model were verified. Through HFACS-CM model analysis and calculation verification, the key causes of secondary explosion accidents in such mines are found and lessons are learned, which provides an effective reference for the effective prevention of deflagration accidents in the field of mine safety.

Modeling and performance analysis of emergency response process for hydrogen leakage and explosion accidents

To address concerns associated with the initial response process following hydrogen refueling station leakage and explosion accidents, this research introduces the utilization of stochastic colored Petri nets for dynamic modeling of the emergency response procedure. Through the construction of a process model for responding to hydrogen leakage and explosion accidents at refueling stations, the model's effectiveness is assessed using an Isomorphic Markov chain (MC) analysis approach, followed by simulation and analysis of the emergency response procedure. Furthermore, the performance of the emergency process in managing hydrogen leakage and explosion accidents at refueling stations is evaluated, considering place occupancy probabilities and transition utilization probabilities. By optimizing the timing of transitions, critical stages in the process for handling hydrogen leakage and explosion accidents at hydrogen refueling stations are identified, and recommendations for process enhancement are proposed. The findings reveal that continuous hydrogen leakage conditions and the phase involving the summoning of rescue personnel are prone to information congestion. The timely arrival of the on-site manager and the prompt reporting of incident details emerge as pivotal actions within the emergency response process for hydrogen refueling station leakage and combustion incidents. These actions wield substantial influence over the efficacy of emergency response and mitigation, underscoring their significance as primary areas for improvement.