This paper proposes a Bayesian Network-based framework for risk assessment and probability estimation of vessel-platform allision accidents,using a novel technique that derives probabilities from incidental data.A dat...This paper proposes a Bayesian Network-based framework for risk assessment and probability estimation of vessel-platform allision accidents,using a novel technique that derives probabilities from incidental data.A dataset of 557 allision incidents collected from multiple open source agencies is analysed to identify causation patterns.Basic causes could only be determined for 375 incidents,with supply vessels involved in 61%of cases.Statistical analysis revealed that vessel type and the month of occurrences are significantly associated,and most incidents arose during cargo transfer operations.Fixed installation accounted for the majority of allisions with moving vessels,and human error emerged as the leading contributor(30%).Building on these insights,a Bayesian Network model is developed incorporating 42 identified causes,three causal factors and four consequence levels.Using a recent probabilistic approach,probabilities of basic causes are derived from annual allision occurrence rates.The BN model is then applied to predict annual allision probabilities and to conduct sensitivity analyses.Results show that weather-related causes and misalignment errors exert the strongest influences on accident probabilities.The methodology is transparent and holistic in providing better discernment of the causation probability of allision accidents.展开更多
Correction to:Nuclear Science and Techniques(2025)36:111 http://gffzzd3cc09b8251d45dfsqnob6nwnfcf56kqp.ffgz.tsg.suse.edu.cn/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have ...Correction to:Nuclear Science and Techniques(2025)36:111 http://gffzzd3cc09b8251d45dfsqnob6nwnfcf56kqp.ffgz.tsg.suse.edu.cn/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have read‘SCRs’.In Table 7 of this article,the column header ρ_fuel was incorrect and should have read CPv_fuel.For completeness and transparency,the old incorrect version and the corrected version of Table 7 are displayed below.展开更多
A substantial amount hazardous chemical accident(HCA)data have been accumulated in the form of unstructured textual data,making systematic analysis and utilization challenging.More importantly,manually identifying and...A substantial amount hazardous chemical accident(HCA)data have been accumulated in the form of unstructured textual data,making systematic analysis and utilization challenging.More importantly,manually identifying and analyzing key information from a considerable quantity of accident data is inefficient and highly susceptible to subjective bias.To efficiently unlock the value of HCA investigation reports and uncover underlying accident patterns,a semi-automated method for knowledge graph(KG)construction has been developed to model the HCA data.First,an ontology that accurately expresses key factors of HCAs is established.Second,an automated method is developed for the identification,standardization,and enhancement of accident factors,which combines deep learning(DL)and natural language processing(NLP)techniques.Specifically,the deep neural network model,named interaction region and type information(IRTI)is proposed to extract accident factors and their relationships from lengthy HCA data with complex overlapping issues.Non-standard accident factors are standardized using ChatGPT-4 in combination with the proposed text clustering model,named contrastive learningbased short text clustering(CLSTC).The processed accident factors are used to construct the hazardous chemical accident knowledge graph(HCAKG).Finally,the risk factors in the HCAKG are statistically analyzed,and their internal topological relationships are explored to facilitate quantitative analysis.Data from HCA investigation reports are used to demonstrate the effectiveness of this method.The result shows that it improves the accuracy and efficiency of accident data analysis,promoting better risk assessment and management strategies.展开更多
To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains i...To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.展开更多
With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the ch...With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.展开更多
This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal...This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal factors and their performance changes in hazardous chemical operational accidents, along with determining the functional failure link relationships. Subsequently, FERM was employed to elucidate both qualitative and quantitative operational accident information within a unified framework, which could be regarded as the input of information fusion to obtain the fuzzy belief distribution of each cause factor. Finally, the derived risk values of the causal factors were ranked while constructing multi-level accident causation chains to unveil the weak links in system functionality and the primary roots of operational accidents. Using the specific case of the “1·15” major explosion and fire accident at Liaoning Panjin Haoye Chemical Co., Ltd., seven causal factors and their corresponding performance changes were identified. Additionally, five accident causation chains were uncovered based on the fuzzy joint distribution of the functional assessment level(FAL) and reliability distribution(RD),revealing an overall increase in risk along the accident evolution path. The research findings demonstrated that FERM enabled the effective characterization, rational quantification and accurate analysis of the inherent uncertainties in hazardous chemical operational accident risks from a systemic perspective.展开更多
A domino accident is a type of major industrial accident that occurs when the primary scenario grows and spreads to many facilities.The maximum distance at which escalation effects can be considered reliable is define...A domino accident is a type of major industrial accident that occurs when the primary scenario grows and spreads to many facilities.The maximum distance at which escalation effects can be considered reliable is defined as the safety distance,and this is the threshold distance to prevent the occurrence of secondary scenarios with more serious impacts than the primary scenarios.In this study,the aim was to determine the safety distances for the domino effects of process accidents in chemical organizations.A new methodology was proposed based on the analysis of past domino accidents,creation of domino scenarios,determination of threshold values for domino effects,and determination of threshold value-based physical effects.A case study of the proposed methodology was also performed.From the analysis of domino accidents,the primary scenario,escalation vector,and secondary scenario,which are domino effect elements,were identified.Domino scenarios based on these elements were created for chemical organizations.New safety distance-based threshold values were proposed.Correlational calculations to be associated with safety distances covering all primary scenarios for domino accidents were put forward.With the case study,the organization's domino accident risk was determined quantitatively,and the effectiveness of the proposed methodology was demonstrated.展开更多
Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research ...Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research in Sri Lanka.In this context,the present study investigates the spatial and temporal patterns of RTAs in theMatara urban area in 2023,with the goal of supporting evidence-based policy interventions.A suite of GIS-based spatial analysis techniques including hotspot analysis,kernel density estimation,GiZ score mapping,and spatial autocorrelation(Moran’s I=0.36,p<0.01)was applied to examine the distribution and contributing factors of RTAs.The results identified several high-risk zones,particularly along the Colombo-Wellawaya main road,as well as near the southern expressway exit,and around Rahula Junction,which collectively accounted for over 40% of all recorded accidents.These areas are characterized by high traffic volumes,complex road geometries,and significant pedestrian activity.Driverrelated behaviors were dominant causes,with negligence accounting for 57% of accidents,aggressive driving for 14%,and alcohol influence for 8%.Temporally,the highest incidence of RTAs(38%)was recorded during the afternoon peak hours(11:00 a.m.to 4:59 p.m.).Based on these findings,targeted policy measures such as enhanced traffic enforcement,infrastructure redesign,and public awareness campaigns are recommended to reduce accident frequency and improve road safety in high-risk areas.This study provides a localized,data-driven framework that can guide urban traffic planning and safety interventions in Matara and similar urban settings.展开更多
Domestic accidents (DA) are common in children and responsible for high morbidity and mortality in developed countries. Objective: This work aimed to describe the epidemiological profile of AD in children aged 0 to 15...Domestic accidents (DA) are common in children and responsible for high morbidity and mortality in developed countries. Objective: This work aimed to describe the epidemiological profile of AD in children aged 0 to 15 years in Libreville. Materials and Methods: All children aged 0 to 15 years who were victims of unintentional trauma occurring at home or in its immediate surroundings were included. We studied the mother’s age, family situation, socioeconomic level, type of housing, age and sex of the child, characteristics of AD and their management. Results: The majority of mothers lived in an intermediate dwelling (80.6%). They were married (37.1%), middle managers (58.2%) and of average socioeconomic level (60.5%). The average age of the mothers was 39.9 ± 11.4 years. Families with more than three children were most exposed (39.2%) to the occurrence of AD. The average age of the children was 6.5 ± 3.3 years with a male predominance. The sex ratio was 1.8. The most common ADs were falls (34.7%), followed by cuts (22.3%) and burns (17.7%). Wounds (54.4%), followed by burns (33%) and fractures (5.1%) were the main types of injuries. The upper limbs were the most affected body part (33.9%) followed by the lower limbs (30.1%) and the head (27.3%). The yard was the preferred location for ADs to occur (51.1%), and particularly during the holiday period (48.4%). The risk factors related to the occurrence of AD were age, socioeconomic level, number of children and type of housing. Care was provided at home in 51.9% of cases. Conclusion: The occurrence of AD in children is not negligible;hence the need to implement preventive measures to minimize their frequency.展开更多
We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a fram...We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a framework for identifying accident factors related to human abilities and characteristics,hardware,software,and the environment.Beyond assessing the accident factors in each element,we also examined the interrelationship between humans and each element.This study highlights the importance of(1)training to enhance situational awareness,(2)improving decision-making skills,and(3)establishing structured decision-making procedures to prevent maritime collision accidents.Additionally,we considered safety measures through(4)hardware enhancements and(5)environmental measures.Furthermore,to prevent accidents,implementing measures grounded in(6)predictions is deemed effective.This study identified accident factors through prediction alongside the SHELL model analysis and proposed countermeasures based on the findings.By applying these predictions,more countermeasures can be derived,which,when combined strategically,can significantly aid in preventing maritime collision accidents.展开更多
In the process of green and smart mine construction under the context of carbon neutrality,China's coal safety situation has been continuously improved in recent years.In order to recognize the development of coal...In the process of green and smart mine construction under the context of carbon neutrality,China's coal safety situation has been continuously improved in recent years.In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents,this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years(2017-2021),from four dimensions(accident level,type,region,and time),and then proposed the preventive measures based on accident statistical laws.The results show that the storage of coal resources has obvious geographic characteristics,mainly concentrated in the Midwest,with coal resources in Shanxi and Shaanxi accounting for about 49.4%.The proportion of coal consumption has dropped from 70.2%to 56%between 2011 and 2021,but still accounts for more than half of the all.Meanwhile,the accident-prone areas are positively correlated with the amount of coal production.Among different levels of coal mine accidents,general accidents had the highest number of accidents and deaths,with 692 accidents and 783 deaths,accounting for 87.6%and 54.64%respectively.The frequency of roof,gas,and transportation accidents is relatively high,and the number of single fatalities caused by gas accidents is the largest,about 4.18.In terms of geographical distribution of accidents,the safety situation in Shanxi Province is the most severe.From the time distribution of coal mine accidents,the accidents mainly occurred in July and August,and rarely occurred in February and December.Finally,the"4+4"safety management model is proposed,combining the statistical results with coal production in China.Based on the existing health and safety management systems,the manage-ments are divided into four sub-categories,and more specific measures are suggested.展开更多
Abrupt air pollution accidents can endanger people’s health and destroy the local ecological environment.The appropriate emergency response can minimize the harmful effects of accidents and protect people’s lives an...Abrupt air pollution accidents can endanger people’s health and destroy the local ecological environment.The appropriate emergency response can minimize the harmful effects of accidents and protect people’s lives and property.This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years.With decades of effort,China has made significant progress in emergency monitoring technologies and equipment,source estimation technologies,pollutant dispersion simulation technologies and others.Many effective domestic emergency monitoring instruments(e.g.,portable DOAS/FT-IR systems,portable FID/PID systems,portable GC-MS systems,scanning imaging remote sensing systems,and emergency monitoring vehicles)had been developed which can meet the demands for routine emergency response activities.A monitoring layout technique combining air dispersion simulation,fuzzy comprehensive evaluation,and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources.Multiple source estimation technologies,including the forward method and the inversion method,have been established and evaluated under various scenarios.Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed.A comprehensive emergency response platform integrating database support,source estimation,monitoring schemes,fast monitoring of pollutants,pollution predictions and risk assessment was developed based on the technical idea of"source identification-model simulation-environmental monitoring"dynamic interactive feedback.It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China.展开更多
In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and impl...In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.展开更多
AIM:To investigate the actual injury situation of seniors in traffic accidents and to evaluate the different injury patterns.METHODS:Injury data,environmental circumstances and crash circumstances of accidents were co...AIM:To investigate the actual injury situation of seniors in traffic accidents and to evaluate the different injury patterns.METHODS:Injury data,environmental circumstances and crash circumstances of accidents were collected shortly after the accident event at the scene.With these data,a technical and medical analysis was performed,including Injury Severity Score,Abbreviated Injury Scale and Maximum Abbreviated Injury Scale.The method of data collection is named the German InDepth Accident Study and can be seen as representative.RESULTS:A total of 4430 injured seniors in traffic accidents were evaluated.The incidence of sustaining severe injuries to extremities,head and maxillofacial region was significantly higher in the group of elderly people compared to a younger age(P<0.05).The number of accident-related injuries was higher in the group of seniors compared to other groups.CONCLUSION:Seniors are more likely to be involved in traffic injuries and to sustain serious to severe injuries compared to other groups.展开更多
BACKGROUND: This study was undertaken to analyze the characteristics and risk factors relating to fatalities and injuries caused by paragliding.METHODS: The judicial examination reports and hospital documents of 82 pa...BACKGROUND: This study was undertaken to analyze the characteristics and risk factors relating to fatalities and injuries caused by paragliding.METHODS: The judicial examination reports and hospital documents of 82 patients traumatized in 64 accidents during 242 355 paragliding jumps between August 2004 and September 2011 were analyzed.RESULTS: In these accidents, 18 of the 82 patients lost their lives. In the patients with a confirmed cause of accident, most of them were involved with multiple fractures and internal organ injuries(n=8, 44.4%).CONCLUSION: We investigated the incidence of paragliding injuries, the types of the injuries, and the severity of affected anatomical regions. The findings are significant for the prevention of paragliding injuries and future research.展开更多
Fatal traffic accidents in urban areas can adversely affect the urban road traffic system and pose many challenges for urban traffic management.Therefore,it is necessary to first classify emergency responses to such a...Fatal traffic accidents in urban areas can adversely affect the urban road traffic system and pose many challenges for urban traffic management.Therefore,it is necessary to first classify emergency responses to such accidents and then handle them quickly and correctly.The aim of this paper is to develop an evaluation index system and to use appropriate methods to investigate emergency-response classifications to fatal traffic accidents in Chinese urban areas.This study used a multilevel hierarchical structural model to determine emergency-response classification.In the model,accident attributes,urban road network vulnerability,and institutional resilience were used as classification criteria.Each evaluation indicator was selected according to importance ranking and independence screening and was given an interpretation and a quantitative criterion.The Fuzzy Delphi Method was used to rank the importance of the evaluation indices and the combined weight of each index was calculated using the G1 method.Finally,the case of a fatal traffic accident was used to validate the model.The results showed that the multilevel hierarchical structural model,Fuzzy Delphi Method,and G1 method can effectively address the problem of emergency-response classification.Because of its simplicity and adaptability,the approach presented here could be useful for decisionmakers and practitioners for determining emergency-response classifications.展开更多
It is an important issue to identify important influencing factors in railway accident analysis.In this paper,employing the good measure of dependence for two-variable relationships,the maximal information coefficient...It is an important issue to identify important influencing factors in railway accident analysis.In this paper,employing the good measure of dependence for two-variable relationships,the maximal information coefficient(MIC),which can capture a wide range of associations,a complex network model for railway accident analysis is designed in which nodes denote factors of railway accidents and edges are generated between two factors of which MIC values are larger than or equal to the dependent criterion.The variety of network structure is studied.As the increasing of the dependent criterion,the network becomes to an approximate scale-free network.Moreover,employing the proposed network,important influencing factors are identified.And we find that the annual track density-gross tonnage factor is an important factor which is a cut vertex when the dependent criterion is equal to 0.3.From the network,it is found that the railway development is unbalanced for different states which is consistent with the fact.展开更多
In order to improve the forecasting precision of road accidents, by introducing Markov chains forecasting method, a grey-Markov model for forecasting road accidents is established based on grey forecasting method. The...In order to improve the forecasting precision of road accidents, by introducing Markov chains forecasting method, a grey-Markov model for forecasting road accidents is established based on grey forecasting method. The model combines the advantages of both grey forecasting method and Markov chains forecasting method, overcomes the influence of random fluctuation data on forecasting precision and widens the application scope of the grey forecasting. An application example is conducted to evaluate the grey-Markov model, which shows that the precision of the grey-Markov model is better than that of grey model in forecasting road accidents.展开更多
In recent years,China has experienced frequent chemical production accidents.This study collates 1900 briefings of such accidents from 2012 to 2023,sourced from a variety of repositories.By employing association rule ...In recent years,China has experienced frequent chemical production accidents.This study collates 1900 briefings of such accidents from 2012 to 2023,sourced from a variety of repositories.By employing association rule mining,we analyzed the connections between causative factors and patterns of these accidents.The analysis revealed significant association rules characterized by high lift values,severe consequences,and patterns not previously recognized.A network model was constructed utilizing Gephi■software to represent the causative factors of these accidents.Through a centrality analysis of the network nodes,key factors contributing to these incidents were identified.Moreover,a SARIMAX model was developed and validated using time series data to predict future accident trends in chemical production.The forecasts generated by this model provide valuable insights for chemical production sectors,highlighting periods with an increased likelihood of accidents.Conclusively,this integration of data mining and predictive modeling could provide a critical method for improving safety protocols and enhancing risk management in chemical industry.展开更多
基金Supported by the Portuguese Foundation for Science and Technology(Fundação para a Ciência e Tecnologia—FCT),under contract UIDB/UIDP/00134/2020。
摘要This paper proposes a Bayesian Network-based framework for risk assessment and probability estimation of vessel-platform allision accidents,using a novel technique that derives probabilities from incidental data.A dataset of 557 allision incidents collected from multiple open source agencies is analysed to identify causation patterns.Basic causes could only be determined for 375 incidents,with supply vessels involved in 61%of cases.Statistical analysis revealed that vessel type and the month of occurrences are significantly associated,and most incidents arose during cargo transfer operations.Fixed installation accounted for the majority of allisions with moving vessels,and human error emerged as the leading contributor(30%).Building on these insights,a Bayesian Network model is developed incorporating 42 identified causes,three causal factors and four consequence levels.Using a recent probabilistic approach,probabilities of basic causes are derived from annual allision occurrence rates.The BN model is then applied to predict annual allision probabilities and to conduct sensitivity analyses.Results show that weather-related causes and misalignment errors exert the strongest influences on accident probabilities.The methodology is transparent and holistic in providing better discernment of the causation probability of allision accidents.
摘要Correction to:Nuclear Science and Techniques(2025)36:111 http://gffzzd3cc09b8251d45dfsqnob6nwnfcf56kqp.ffgz.tsg.suse.edu.cn/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have read‘SCRs’.In Table 7 of this article,the column header ρ_fuel was incorrect and should have read CPv_fuel.For completeness and transparency,the old incorrect version and the corrected version of Table 7 are displayed below.
基金supported by the Key Research and Development Program of Xinjiang Uygur Autonomous Region(2022B03004-3)the National Natural Science Foundation of China(62366052)+1 种基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01C427,2022D01C429)the Research Project of Huairou Laboratory(YZD2024025A)。
摘要A substantial amount hazardous chemical accident(HCA)data have been accumulated in the form of unstructured textual data,making systematic analysis and utilization challenging.More importantly,manually identifying and analyzing key information from a considerable quantity of accident data is inefficient and highly susceptible to subjective bias.To efficiently unlock the value of HCA investigation reports and uncover underlying accident patterns,a semi-automated method for knowledge graph(KG)construction has been developed to model the HCA data.First,an ontology that accurately expresses key factors of HCAs is established.Second,an automated method is developed for the identification,standardization,and enhancement of accident factors,which combines deep learning(DL)and natural language processing(NLP)techniques.Specifically,the deep neural network model,named interaction region and type information(IRTI)is proposed to extract accident factors and their relationships from lengthy HCA data with complex overlapping issues.Non-standard accident factors are standardized using ChatGPT-4 in combination with the proposed text clustering model,named contrastive learningbased short text clustering(CLSTC).The processed accident factors are used to construct the hazardous chemical accident knowledge graph(HCAKG).Finally,the risk factors in the HCAKG are statistically analyzed,and their internal topological relationships are explored to facilitate quantitative analysis.Data from HCA investigation reports are used to demonstrate the effectiveness of this method.The result shows that it improves the accuracy and efficiency of accident data analysis,promoting better risk assessment and management strategies.
摘要To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.
基金The National Social Science Foundation Youth Project of China:Research on the collaborative govemance path of administrative law and criminal law against dangerous driving behaviors in the digital-intelligent society(25CFX108)。
摘要With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.
基金supported by the National Key Research&Development Program of China(2021YFB3301100)the National Natural Science Foundation of China(52004014)the Fundamental Research Funds for the Central Universities(ZY2406).
摘要This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal factors and their performance changes in hazardous chemical operational accidents, along with determining the functional failure link relationships. Subsequently, FERM was employed to elucidate both qualitative and quantitative operational accident information within a unified framework, which could be regarded as the input of information fusion to obtain the fuzzy belief distribution of each cause factor. Finally, the derived risk values of the causal factors were ranked while constructing multi-level accident causation chains to unveil the weak links in system functionality and the primary roots of operational accidents. Using the specific case of the “1·15” major explosion and fire accident at Liaoning Panjin Haoye Chemical Co., Ltd., seven causal factors and their corresponding performance changes were identified. Additionally, five accident causation chains were uncovered based on the fuzzy joint distribution of the functional assessment level(FAL) and reliability distribution(RD),revealing an overall increase in risk along the accident evolution path. The research findings demonstrated that FERM enabled the effective characterization, rational quantification and accurate analysis of the inherent uncertainties in hazardous chemical operational accident risks from a systemic perspective.
摘要A domino accident is a type of major industrial accident that occurs when the primary scenario grows and spreads to many facilities.The maximum distance at which escalation effects can be considered reliable is defined as the safety distance,and this is the threshold distance to prevent the occurrence of secondary scenarios with more serious impacts than the primary scenarios.In this study,the aim was to determine the safety distances for the domino effects of process accidents in chemical organizations.A new methodology was proposed based on the analysis of past domino accidents,creation of domino scenarios,determination of threshold values for domino effects,and determination of threshold value-based physical effects.A case study of the proposed methodology was also performed.From the analysis of domino accidents,the primary scenario,escalation vector,and secondary scenario,which are domino effect elements,were identified.Domino scenarios based on these elements were created for chemical organizations.New safety distance-based threshold values were proposed.Correlational calculations to be associated with safety distances covering all primary scenarios for domino accidents were put forward.With the case study,the organization's domino accident risk was determined quantitatively,and the effectiveness of the proposed methodology was demonstrated.
摘要Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research in Sri Lanka.In this context,the present study investigates the spatial and temporal patterns of RTAs in theMatara urban area in 2023,with the goal of supporting evidence-based policy interventions.A suite of GIS-based spatial analysis techniques including hotspot analysis,kernel density estimation,GiZ score mapping,and spatial autocorrelation(Moran’s I=0.36,p<0.01)was applied to examine the distribution and contributing factors of RTAs.The results identified several high-risk zones,particularly along the Colombo-Wellawaya main road,as well as near the southern expressway exit,and around Rahula Junction,which collectively accounted for over 40% of all recorded accidents.These areas are characterized by high traffic volumes,complex road geometries,and significant pedestrian activity.Driverrelated behaviors were dominant causes,with negligence accounting for 57% of accidents,aggressive driving for 14%,and alcohol influence for 8%.Temporally,the highest incidence of RTAs(38%)was recorded during the afternoon peak hours(11:00 a.m.to 4:59 p.m.).Based on these findings,targeted policy measures such as enhanced traffic enforcement,infrastructure redesign,and public awareness campaigns are recommended to reduce accident frequency and improve road safety in high-risk areas.This study provides a localized,data-driven framework that can guide urban traffic planning and safety interventions in Matara and similar urban settings.
摘要Domestic accidents (DA) are common in children and responsible for high morbidity and mortality in developed countries. Objective: This work aimed to describe the epidemiological profile of AD in children aged 0 to 15 years in Libreville. Materials and Methods: All children aged 0 to 15 years who were victims of unintentional trauma occurring at home or in its immediate surroundings were included. We studied the mother’s age, family situation, socioeconomic level, type of housing, age and sex of the child, characteristics of AD and their management. Results: The majority of mothers lived in an intermediate dwelling (80.6%). They were married (37.1%), middle managers (58.2%) and of average socioeconomic level (60.5%). The average age of the mothers was 39.9 ± 11.4 years. Families with more than three children were most exposed (39.2%) to the occurrence of AD. The average age of the children was 6.5 ± 3.3 years with a male predominance. The sex ratio was 1.8. The most common ADs were falls (34.7%), followed by cuts (22.3%) and burns (17.7%). Wounds (54.4%), followed by burns (33%) and fractures (5.1%) were the main types of injuries. The upper limbs were the most affected body part (33.9%) followed by the lower limbs (30.1%) and the head (27.3%). The yard was the preferred location for ADs to occur (51.1%), and particularly during the holiday period (48.4%). The risk factors related to the occurrence of AD were age, socioeconomic level, number of children and type of housing. Care was provided at home in 51.9% of cases. Conclusion: The occurrence of AD in children is not negligible;hence the need to implement preventive measures to minimize their frequency.
摘要We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a framework for identifying accident factors related to human abilities and characteristics,hardware,software,and the environment.Beyond assessing the accident factors in each element,we also examined the interrelationship between humans and each element.This study highlights the importance of(1)training to enhance situational awareness,(2)improving decision-making skills,and(3)establishing structured decision-making procedures to prevent maritime collision accidents.Additionally,we considered safety measures through(4)hardware enhancements and(5)environmental measures.Furthermore,to prevent accidents,implementing measures grounded in(6)predictions is deemed effective.This study identified accident factors through prediction alongside the SHELL model analysis and proposed countermeasures based on the findings.By applying these predictions,more countermeasures can be derived,which,when combined strategically,can significantly aid in preventing maritime collision accidents.
基金supported by the National Key R&D Program of China (2022YFC3004701)the National Natural Science Foundation of China (52274242,51904293)+1 种基金the Natural Science Foundation of Jiangsu Province (BK20190627)the China Postdoctoral Science Foundation (2019M661998).
摘要In the process of green and smart mine construction under the context of carbon neutrality,China's coal safety situation has been continuously improved in recent years.In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents,this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years(2017-2021),from four dimensions(accident level,type,region,and time),and then proposed the preventive measures based on accident statistical laws.The results show that the storage of coal resources has obvious geographic characteristics,mainly concentrated in the Midwest,with coal resources in Shanxi and Shaanxi accounting for about 49.4%.The proportion of coal consumption has dropped from 70.2%to 56%between 2011 and 2021,but still accounts for more than half of the all.Meanwhile,the accident-prone areas are positively correlated with the amount of coal production.Among different levels of coal mine accidents,general accidents had the highest number of accidents and deaths,with 692 accidents and 783 deaths,accounting for 87.6%and 54.64%respectively.The frequency of roof,gas,and transportation accidents is relatively high,and the number of single fatalities caused by gas accidents is the largest,about 4.18.In terms of geographical distribution of accidents,the safety situation in Shanxi Province is the most severe.From the time distribution of coal mine accidents,the accidents mainly occurred in July and August,and rarely occurred in February and December.Finally,the"4+4"safety management model is proposed,combining the statistical results with coal production in China.Based on the existing health and safety management systems,the manage-ments are divided into four sub-categories,and more specific measures are suggested.
基金supported by the National Key Research and Development Program of China(No.2017YFC0209900)Beijing Nova Program from Beijing Municipal Science&Technology Commission(No.Z201100006820098)the Youth Science and Technology Talents Support Program(2020)by Anhui Association for Science and Technology(No.RCTJ202002)。
摘要Abrupt air pollution accidents can endanger people’s health and destroy the local ecological environment.The appropriate emergency response can minimize the harmful effects of accidents and protect people’s lives and property.This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years.With decades of effort,China has made significant progress in emergency monitoring technologies and equipment,source estimation technologies,pollutant dispersion simulation technologies and others.Many effective domestic emergency monitoring instruments(e.g.,portable DOAS/FT-IR systems,portable FID/PID systems,portable GC-MS systems,scanning imaging remote sensing systems,and emergency monitoring vehicles)had been developed which can meet the demands for routine emergency response activities.A monitoring layout technique combining air dispersion simulation,fuzzy comprehensive evaluation,and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources.Multiple source estimation technologies,including the forward method and the inversion method,have been established and evaluated under various scenarios.Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed.A comprehensive emergency response platform integrating database support,source estimation,monitoring schemes,fast monitoring of pollutants,pollution predictions and risk assessment was developed based on the technical idea of"source identification-model simulation-environmental monitoring"dynamic interactive feedback.It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China.
基金the National Natural Science Foundation of China(No.51208065)the Science and Technology Planning Project of Hunan Province(No.2015JC3056)+1 种基金the Science and Technology Planning Project of Guangdong Province(No.2015B010110005)the Project of Hunan Province key Laboratory of Safety Design and Reliability Technology for Engineering Vehicle(No.KF1506)
摘要In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.
基金Supported by Federal Highway Research Institute(BASt)the German Research Association of the Automotive Technology,a department of the VDA(German Association of the Automotive Industry)
摘要AIM:To investigate the actual injury situation of seniors in traffic accidents and to evaluate the different injury patterns.METHODS:Injury data,environmental circumstances and crash circumstances of accidents were collected shortly after the accident event at the scene.With these data,a technical and medical analysis was performed,including Injury Severity Score,Abbreviated Injury Scale and Maximum Abbreviated Injury Scale.The method of data collection is named the German InDepth Accident Study and can be seen as representative.RESULTS:A total of 4430 injured seniors in traffic accidents were evaluated.The incidence of sustaining severe injuries to extremities,head and maxillofacial region was significantly higher in the group of elderly people compared to a younger age(P<0.05).The number of accident-related injuries was higher in the group of seniors compared to other groups.CONCLUSION:Seniors are more likely to be involved in traffic injuries and to sustain serious to severe injuries compared to other groups.
摘要BACKGROUND: This study was undertaken to analyze the characteristics and risk factors relating to fatalities and injuries caused by paragliding.METHODS: The judicial examination reports and hospital documents of 82 patients traumatized in 64 accidents during 242 355 paragliding jumps between August 2004 and September 2011 were analyzed.RESULTS: In these accidents, 18 of the 82 patients lost their lives. In the patients with a confirmed cause of accident, most of them were involved with multiple fractures and internal organ injuries(n=8, 44.4%).CONCLUSION: We investigated the incidence of paragliding injuries, the types of the injuries, and the severity of affected anatomical regions. The findings are significant for the prevention of paragliding injuries and future research.
基金supported by the Fifth 333 High-Level Talents Project of Jiangsu Province under Grant BRA2017443the Key Research Base of Jiangsu University Philosophy and Social Science under Grant 2018ZDJD-B007.
摘要Fatal traffic accidents in urban areas can adversely affect the urban road traffic system and pose many challenges for urban traffic management.Therefore,it is necessary to first classify emergency responses to such accidents and then handle them quickly and correctly.The aim of this paper is to develop an evaluation index system and to use appropriate methods to investigate emergency-response classifications to fatal traffic accidents in Chinese urban areas.This study used a multilevel hierarchical structural model to determine emergency-response classification.In the model,accident attributes,urban road network vulnerability,and institutional resilience were used as classification criteria.Each evaluation indicator was selected according to importance ranking and independence screening and was given an interpretation and a quantitative criterion.The Fuzzy Delphi Method was used to rank the importance of the evaluation indices and the combined weight of each index was calculated using the G1 method.Finally,the case of a fatal traffic accident was used to validate the model.The results showed that the multilevel hierarchical structural model,Fuzzy Delphi Method,and G1 method can effectively address the problem of emergency-response classification.Because of its simplicity and adaptability,the approach presented here could be useful for decisionmakers and practitioners for determining emergency-response classifications.
基金Supported by the Fundamental Research Funds for the Central Universities under Grant No.2016YJS087the National Natural Science Foundation of China under Grant No.U1434209the Research Foundation of State Key Laboratory of Railway Traffic Control and Safety,Beijing Jiaotong University under Grant No.RCS2016ZJ001
摘要It is an important issue to identify important influencing factors in railway accident analysis.In this paper,employing the good measure of dependence for two-variable relationships,the maximal information coefficient(MIC),which can capture a wide range of associations,a complex network model for railway accident analysis is designed in which nodes denote factors of railway accidents and edges are generated between two factors of which MIC values are larger than or equal to the dependent criterion.The variety of network structure is studied.As the increasing of the dependent criterion,the network becomes to an approximate scale-free network.Moreover,employing the proposed network,important influencing factors are identified.And we find that the annual track density-gross tonnage factor is an important factor which is a cut vertex when the dependent criterion is equal to 0.3.From the network,it is found that the railway development is unbalanced for different states which is consistent with the fact.
摘要In order to improve the forecasting precision of road accidents, by introducing Markov chains forecasting method, a grey-Markov model for forecasting road accidents is established based on grey forecasting method. The model combines the advantages of both grey forecasting method and Markov chains forecasting method, overcomes the influence of random fluctuation data on forecasting precision and widens the application scope of the grey forecasting. An application example is conducted to evaluate the grey-Markov model, which shows that the precision of the grey-Markov model is better than that of grey model in forecasting road accidents.
基金support given by the Young Scientists Fund of National Natural Science Foundation of China(No.52004134)the Key Program of National Natural Science Foundation of China(No.51834007).
摘要In recent years,China has experienced frequent chemical production accidents.This study collates 1900 briefings of such accidents from 2012 to 2023,sourced from a variety of repositories.By employing association rule mining,we analyzed the connections between causative factors and patterns of these accidents.The analysis revealed significant association rules characterized by high lift values,severe consequences,and patterns not previously recognized.A network model was constructed utilizing Gephi■software to represent the causative factors of these accidents.Through a centrality analysis of the network nodes,key factors contributing to these incidents were identified.Moreover,a SARIMAX model was developed and validated using time series data to predict future accident trends in chemical production.The forecasts generated by this model provide valuable insights for chemical production sectors,highlighting periods with an increased likelihood of accidents.Conclusively,this integration of data mining and predictive modeling could provide a critical method for improving safety protocols and enhancing risk management in chemical industry.