Autonomous vehicles operate without direct human intervention,which introduces safety risks that differ from those of conventional vehicles.Although many studies have examined safety issues related to autonomous drivi...Autonomous vehicles operate without direct human intervention,which introduces safety risks that differ from those of conventional vehicles.Although many studies have examined safety issues related to autonomous driving,high-risk situations have often been defined using single indicators,making it difficult to capture the complex and evolving nature of accident risk.To address this limitation,this study proposes a structured framework for defining and analyzing high-risk situations throughout the traffic accident process.High-risk situations are described using three complementary indicators:accident likelihood,accident severity,and accident duration.These indicators explain how risk emerges,increases,and persists over time.Based on this concept,a framework for traffic accident visualization analysis is developed to support phase-specific risk assessment and visualization.The framework combines accident-phase information with factor-level risk contributions,allowing systematic identification of key factors and their interactions across different accident stages.Using combinations of the three indicators,high-risk situations are classified into twenty-seven distinct types,providing a clear typology for complex accident scenarios involving autonomous vehicles.The applicability of the proposed framework is demonstrated through two representative accident scenarioswith different risk characteristics.The results showthat the framework effectively captures interactions among multiple risk factors,explains how risk levels change from pre-crash to post-crash phases,and identifies contributing factors that are difficult to detect using conventional traffic accident investigation methods.Overall,the proposed framework offers a practical basis for autonomous vehicle accident analysis,safety evaluation,and policy-related decision-making.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
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
DAYU3D is a modern three-dimensional(3D)computer code for thermal-hydraulic design and accident analysis in hightemperature gas-cooled reactors(HTGRs),developed by the Institute of Nuclear and New Energy Technology(IN...DAYU3D is a modern three-dimensional(3D)computer code for thermal-hydraulic design and accident analysis in hightemperature gas-cooled reactors(HTGRs),developed by the Institute of Nuclear and New Energy Technology(INET)at Tsinghua University.Compared to the traditional codes like TINTE,the DAYU3D code has advantages due to its refined framework,improved models,and more efficient algorithms.It is able to simulate the continuous movement of control rods and is more rigorous in treating radiation heat transfer and the break mass flow.Advanced computational methods significantly improve the computational efficiency of DAYU3D,achieving a time reduction of over 60%compared to TINTE.Extensive verification and validation with more than 100 cases demonstrate that DAYU3D is promising for HTGR 3D thermal-hydraulic design and accident analyses.展开更多
Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/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 https://doi.org/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
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
Dear Editor,As an important energy storage device,lithium-ion battery plays a vital role in electric aircrafts,which are new and promising equipment of transportation in the future with low carbon emissions.Accurate p...Dear Editor,As an important energy storage device,lithium-ion battery plays a vital role in electric aircrafts,which are new and promising equipment of transportation in the future with low carbon emissions.Accurate prediction of the state of charge(SOC)of lithium-ion batteries is of great importance in reducing the probability of abnormal accidents and ensuring flight safety.展开更多
In the scenario of a steam generator tube rupture accident in a lead-cooled fast reactor,secondary circuit subcooled water under high pressure is injected into an ordinary-pressure primary vessel,where a molten lead-b...In the scenario of a steam generator tube rupture accident in a lead-cooled fast reactor,secondary circuit subcooled water under high pressure is injected into an ordinary-pressure primary vessel,where a molten lead-based alloy(typically pure lead or lead-bismuth eutectic(LBE))is used as the coolant.To clarify the pressure build-up characteristics under water-jet injection,this study conducted several experiments by injecting pressurized water into a molten LBE pool at Sun Yat-sen University.To obtain a further understanding,several new experimental parameters were adopted,including the melt temperature,water subcooling,injection pressure,injection duration,and nozzle diameter.Through detailed analyses,it was found that the pressure and temperature during the water-melt interaction exhibited a consistent variation trend with our previous water-droplet injection mode LBE experiment.Similarly,the existence of a steam explosion was confirmed,which typically results in a much stronger pressure build-up.For the non-explosion cases,increasing the injection pressure,melt-pool temperature,nozzle diameter,and water subcooling promoted pressure build-up in the melt pool.However,a limited enhancement effect was observed when increasing the injection duration,which may be owing to the continually rising pressure in the interaction vessel or the isolation effect of the generated steam cavity.Regardless of whether a steam explosion occurred,the calculated mechanical and kinetic energy conversion efficiencies of the melt were relatively small(not exceeding 4.1%and 0.7%,respectively).Moreover,the range of the conversion efficiency was similar to that of previous water-droplet experiments,although the upper limit of the jet mode was slightly lower.展开更多
Estimate of the Deterministic Neutron RBE for Radiation-induced Pseudo-Pelger Huët Cell Formation R.E.Goans1,2,C.J.Iddins1,R.E.Goans,Jr.3(1.Radiation Emergency Assistance Center/Training Site,Oak Ridge,TN;2.MJW C...Estimate of the Deterministic Neutron RBE for Radiation-induced Pseudo-Pelger Huët Cell Formation R.E.Goans1,2,C.J.Iddins1,R.E.Goans,Jr.3(1.Radiation Emergency Assistance Center/Training Site,Oak Ridge,TN;2.MJW Corporation,Amherst,NY;3.LMU Debusk School of Medicine,Harrogate,TN)Abstract:Using archival peripheral blood slides from radiation accident patients,we have recently described the pseudo-Pelger Huët anomaly(PPHA)in neutrophils as a new radiation-induced biomarker,useful for dosimetry not only immediately after a radiation incident but also potentially helpful as a tool in retrospective dosimetry.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
Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence sem...Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence semantic dependencies.A robust entity extraction method tailored for accident texts is proposed.Design/methodology/approach–This method is implemented through a dual-branch multi-task mutual learning model named R-MLP,which jointly performs entity recognition and accident phase classification.The model leverages a shared BERT encoder to extract contextual features and incorporates a sentence span indexing module to align feature granularity.A cross-task mutual learning mechanism is also introduced to strengthen semantic representation.Findings–R-MLP effectively mitigates the impact of semantic complexity and data sparsity in domain entities and enhances the model’s ability to capture inter-sentence semantic dependencies.Experimental results show that R-MLP achieves a maximum F1-score of 0.736 in extracting six types of key railway accident entities,significantly outperforming baseline models such as RoBERTa and MacBERT.Originality/value–This demonstrates the proposed method’s superior generalization and accuracy in domainspecific entity extraction tasks,confirming its effectiveness and practical value.展开更多
A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These...A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.展开更多
1 Martin Hibbert was a survivor of a serious accident.During the incident,Martin's spine(脊柱)was seriously hurt but he was fortunate to be alive.Despite this spinal cord injury(SCI),Martin was determined to turn ...1 Martin Hibbert was a survivor of a serious accident.During the incident,Martin's spine(脊柱)was seriously hurt but he was fortunate to be alive.Despite this spinal cord injury(SCI),Martin was determined to turn tragedy into something good.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
City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a trag...City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a tragic accident.Blair was called to the scene of a deer struck by a car.Upon arrival,he found the mother deer had suffered four broken legs and sadly had to be put down to prevent further suffering.展开更多
Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents.The main challenge lies in achieving real-time,reliable and highly a...Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents.The main challenge lies in achieving real-time,reliable and highly accurate detection across diverse Internet-of-vehicles(IoV)environments.To overcome this challenge,this paper leverages deep learning to automatically learn patterns from visual data to detect accidents with high accuracy.A visual classification model based on the ResNet-50 architecture is presented for distinguishing between accident and non-accident images.The model is trained and tested on a labeled dataset and achieves an overall accuracy of 91.84%,with a precision of 94%,recall of 90.38%,and an F1-score of 92.14%.Training behavior is observed over 100 epochs,where the model has shown rapid accuracy gains and loss reduction within the first 30 epochs,followed by gradual stabilization.Accuracy plateaues between 90−93%,and loss values remain consistent between 0.1 and 0.2 in later stages.To understand the effect of training strategy,the model is optimized using three different algorithms,namely,SGD,Adam,and Adadelta with all showing effective performance,though with varied convergence patterns.Further,to test its effectiveness,the proposed model is compared with existing models.In the end,the problems encountered in implementing the model in practical automotive settings and offered solutions are discussed.The results support the reliability of the approach and its suitability for real-time traffic safety applications.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
As lithium-ion batteries(LIBs)continue to evolve toward lower costs and higher energy densities,their potential safety risks have become increasingly apparent.Incidents such as explosions at energy storage facilities,...As lithium-ion batteries(LIBs)continue to evolve toward lower costs and higher energy densities,their potential safety risks have become increasingly apparent.Incidents such as explosions at energy storage facilities,fires in electric vehicles,and building fires ignited by charging two-wheeled vehicles have been occurring with alarming frequency,often resulting in significant casualties and injuries.Conducting indepth investigations into thermal runaway(TR)incidents in LIBs can significantly reduce the risk of future occurrences.However,current investigations into LIB fire and explosion incidents face challenges due to the difficulty of conducting in-depth analyses and the lack of a robust theoretical framework to guide these investigations.To enhance the effectiveness of in-depth investigations into battery fire and explosion incidents and to address the lack of theoretical guidance,this paper is the first to systematically examine the conservation and flow patterns of elements during the TR process of LIBs.The analysis reveals that during TR,the gas products generated include approximately 1.5 g of H_(2),23.6 g of CO,88.4 g of CO_(2),8.9 g of C_(2)H_(4),7.3 g of CH_(4),3.7 g of C_(2)H_(6),and 82 g of electrolyte vapor.After TR,the solid compounds formed consist of approximately 2.5 g of LiF,29–92.2 g of elemental Ni/Co/Mn,11.4 g of Li_(2)CO_(3),200.6 g of graphite,1.4 g of NiO,29.6 g of MnO,30.1 g of CoO,67 g of elemental Cu,0.03 g of LiNiO_(2),and 4.3 g of LiAlO_(2).Importantly,the energy released from reactions forming solid compounds during TR surpasses that from gas-forming reactions.This investigation represents the first application of Hess’s law to verify the conservation of elements during the TR process of lithium-ion batteries.The proposed methodology is also applicable to other types of energy storage batteries,effectively advancing techniques for comprehensively investigating lithium battery fire and explosion incidents.展开更多
To address various challenges,including delayed traffic accident detection response,poor localization accuracy,and inadequate rescue efficiency,this study presents a YOLOv10-based intelligent detection and classificat...To address various challenges,including delayed traffic accident detection response,poor localization accuracy,and inadequate rescue efficiency,this study presents a YOLOv10-based intelligent detection and classification system.Featuring a three-tier“perception-decision-action”framework,the system uses an enhanced YOLOv10 model for precise accident detection and implements multiscale feature fusion to improve the recognition of diverse accident scenarios.The classification module employs dynamic weighting to assess accidents as mild,moderate,or severe,coupled with a tri-level response protocol.For route optimization,the path planning component uses a refined A*algorithm with a four-dimensional cost function.Tests show that the system delivers 98.2%detection accuracy with subsecond response times,maintains 93.5%reliability in harsh weather,and enhances rescue operations by 23.7%in efficiency.This solution offers a robust technical approach for smart traffic management systems.展开更多
The passive containment heat removal system(PCS)is one of the key passive safety systems of China’s third-generation advanced pressurized water reactor-Hua-long Pressurized Reactor(HPR1000),used to prevent overpressu...The passive containment heat removal system(PCS)is one of the key passive safety systems of China’s third-generation advanced pressurized water reactor-Hua-long Pressurized Reactor(HPR1000),used to prevent overpressure of large concrete containment under severe accident scenarios.This paper provides an overview of the development of the HPR1000 passive containment heat removal system,including its operating principles and configuration,internal heat exchanger design,feasibility tests,engineering-scale PCS verification tests,comprehensive tests on PCS-containment coupling characteristics,among other key supporting studies.These extensive studies demonstrated that the PCS of HPR1000,which is designed based on flashing-driven open natural circulation and efficient condensation heat transfer theory,can work effectively and ensure the integrity of the containment under various accident scenarios.The system has been applied to Fuqing No.5 and No.6 nuclear power units and Zhangzhou No.1 and No.2 units of China’s first million-kilowatt third-generation nuclear power HPR1000.It is also applied to K-2/K-3 units of Karachi Nuclear Power Plant in Pakistan.展开更多
基金supported by the Korea Institute of Police Technology(No.:RS-2024-00405603).
文摘Autonomous vehicles operate without direct human intervention,which introduces safety risks that differ from those of conventional vehicles.Although many studies have examined safety issues related to autonomous driving,high-risk situations have often been defined using single indicators,making it difficult to capture the complex and evolving nature of accident risk.To address this limitation,this study proposes a structured framework for defining and analyzing high-risk situations throughout the traffic accident process.High-risk situations are described using three complementary indicators:accident likelihood,accident severity,and accident duration.These indicators explain how risk emerges,increases,and persists over time.Based on this concept,a framework for traffic accident visualization analysis is developed to support phase-specific risk assessment and visualization.The framework combines accident-phase information with factor-level risk contributions,allowing systematic identification of key factors and their interactions across different accident stages.Using combinations of the three indicators,high-risk situations are classified into twenty-seven distinct types,providing a clear typology for complex accident scenarios involving autonomous vehicles.The applicability of the proposed framework is demonstrated through two representative accident scenarioswith different risk characteristics.The results showthat the framework effectively captures interactions among multiple risk factors,explains how risk levels change from pre-crash to post-crash phases,and identifies contributing factors that are difficult to detect using conventional traffic accident investigation methods.Overall,the proposed framework offers a practical basis for autonomous vehicle accident analysis,safety evaluation,and policy-related decision-making.
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)。
文摘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.
文摘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.
文摘DAYU3D is a modern three-dimensional(3D)computer code for thermal-hydraulic design and accident analysis in hightemperature gas-cooled reactors(HTGRs),developed by the Institute of Nuclear and New Energy Technology(INET)at Tsinghua University.Compared to the traditional codes like TINTE,the DAYU3D code has advantages due to its refined framework,improved models,and more efficient algorithms.It is able to simulate the continuous movement of control rods and is more rigorous in treating radiation heat transfer and the break mass flow.Advanced computational methods significantly improve the computational efficiency of DAYU3D,achieving a time reduction of over 60%compared to TINTE.Extensive verification and validation with more than 100 cases demonstrate that DAYU3D is promising for HTGR 3D thermal-hydraulic design and accident analyses.
文摘Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/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 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).
文摘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.
基金supported in part by the Chunhui Project of the Ministry of Education of China(HZKY20220429)the Department of Science&Technology of Liaoning Province(2022-MS-300)the Educational Department of Liaoning Province(LJKMZ20220561)
文摘Dear Editor,As an important energy storage device,lithium-ion battery plays a vital role in electric aircrafts,which are new and promising equipment of transportation in the future with low carbon emissions.Accurate prediction of the state of charge(SOC)of lithium-ion batteries is of great importance in reducing the probability of abnormal accidents and ensuring flight safety.
基金supported by Basic and Applied Basic research foundation of Guangdong province(Nos.2021A1515010343 and 2022A1515011582)the Science and Technology Program of Guangdong Province(Nos.2021A0505030026 and 2022A0505050029).
文摘In the scenario of a steam generator tube rupture accident in a lead-cooled fast reactor,secondary circuit subcooled water under high pressure is injected into an ordinary-pressure primary vessel,where a molten lead-based alloy(typically pure lead or lead-bismuth eutectic(LBE))is used as the coolant.To clarify the pressure build-up characteristics under water-jet injection,this study conducted several experiments by injecting pressurized water into a molten LBE pool at Sun Yat-sen University.To obtain a further understanding,several new experimental parameters were adopted,including the melt temperature,water subcooling,injection pressure,injection duration,and nozzle diameter.Through detailed analyses,it was found that the pressure and temperature during the water-melt interaction exhibited a consistent variation trend with our previous water-droplet injection mode LBE experiment.Similarly,the existence of a steam explosion was confirmed,which typically results in a much stronger pressure build-up.For the non-explosion cases,increasing the injection pressure,melt-pool temperature,nozzle diameter,and water subcooling promoted pressure build-up in the melt pool.However,a limited enhancement effect was observed when increasing the injection duration,which may be owing to the continually rising pressure in the interaction vessel or the isolation effect of the generated steam cavity.Regardless of whether a steam explosion occurred,the calculated mechanical and kinetic energy conversion efficiencies of the melt were relatively small(not exceeding 4.1%and 0.7%,respectively).Moreover,the range of the conversion efficiency was similar to that of previous water-droplet experiments,although the upper limit of the jet mode was slightly lower.
文摘Estimate of the Deterministic Neutron RBE for Radiation-induced Pseudo-Pelger Huët Cell Formation R.E.Goans1,2,C.J.Iddins1,R.E.Goans,Jr.3(1.Radiation Emergency Assistance Center/Training Site,Oak Ridge,TN;2.MJW Corporation,Amherst,NY;3.LMU Debusk School of Medicine,Harrogate,TN)Abstract:Using archival peripheral blood slides from radiation accident patients,we have recently described the pseudo-Pelger Huët anomaly(PPHA)in neutrophils as a new radiation-induced biomarker,useful for dosimetry not only immediately after a radiation incident but also potentially helpful as a tool in retrospective dosimetry.
文摘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.
基金funded by the Technology Research and Development Plan Program of China State Railway Group Co.,Ltd.(No.Q2024T001)the Foundation of China Academy of Railway Sciences Co.,Ltd.(No:2024YJ259).
文摘Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence semantic dependencies.A robust entity extraction method tailored for accident texts is proposed.Design/methodology/approach–This method is implemented through a dual-branch multi-task mutual learning model named R-MLP,which jointly performs entity recognition and accident phase classification.The model leverages a shared BERT encoder to extract contextual features and incorporates a sentence span indexing module to align feature granularity.A cross-task mutual learning mechanism is also introduced to strengthen semantic representation.Findings–R-MLP effectively mitigates the impact of semantic complexity and data sparsity in domain entities and enhances the model’s ability to capture inter-sentence semantic dependencies.Experimental results show that R-MLP achieves a maximum F1-score of 0.736 in extracting six types of key railway accident entities,significantly outperforming baseline models such as RoBERTa and MacBERT.Originality/value–This demonstrates the proposed method’s superior generalization and accuracy in domainspecific entity extraction tasks,confirming its effectiveness and practical value.
文摘A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.
文摘1 Martin Hibbert was a survivor of a serious accident.During the incident,Martin's spine(脊柱)was seriously hurt but he was fortunate to be alive.Despite this spinal cord injury(SCI),Martin was determined to turn tragedy into something good.
文摘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.
文摘City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a tragic accident.Blair was called to the scene of a deer struck by a car.Upon arrival,he found the mother deer had suffered four broken legs and sadly had to be put down to prevent further suffering.
基金the Deanship of Graduate Studies and Scientific Research at Najran University for funding this work under the Growth Funding Program grant code(NU/GP/SERC/13/358-6)。
文摘Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents.The main challenge lies in achieving real-time,reliable and highly accurate detection across diverse Internet-of-vehicles(IoV)environments.To overcome this challenge,this paper leverages deep learning to automatically learn patterns from visual data to detect accidents with high accuracy.A visual classification model based on the ResNet-50 architecture is presented for distinguishing between accident and non-accident images.The model is trained and tested on a labeled dataset and achieves an overall accuracy of 91.84%,with a precision of 94%,recall of 90.38%,and an F1-score of 92.14%.Training behavior is observed over 100 epochs,where the model has shown rapid accuracy gains and loss reduction within the first 30 epochs,followed by gradual stabilization.Accuracy plateaues between 90−93%,and loss values remain consistent between 0.1 and 0.2 in later stages.To understand the effect of training strategy,the model is optimized using three different algorithms,namely,SGD,Adam,and Adadelta with all showing effective performance,though with varied convergence patterns.Further,to test its effectiveness,the proposed model is compared with existing models.In the end,the problems encountered in implementing the model in practical automotive settings and offered solutions are discussed.The results support the reliability of the approach and its suitability for real-time traffic safety applications.
文摘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 Natural Science Foundation of China(52106284,52422609)the Natural Science Foundation of Hebei Province(B2021507001)Key Research Special Project of CPPU(ZDZX202501)。
文摘As lithium-ion batteries(LIBs)continue to evolve toward lower costs and higher energy densities,their potential safety risks have become increasingly apparent.Incidents such as explosions at energy storage facilities,fires in electric vehicles,and building fires ignited by charging two-wheeled vehicles have been occurring with alarming frequency,often resulting in significant casualties and injuries.Conducting indepth investigations into thermal runaway(TR)incidents in LIBs can significantly reduce the risk of future occurrences.However,current investigations into LIB fire and explosion incidents face challenges due to the difficulty of conducting in-depth analyses and the lack of a robust theoretical framework to guide these investigations.To enhance the effectiveness of in-depth investigations into battery fire and explosion incidents and to address the lack of theoretical guidance,this paper is the first to systematically examine the conservation and flow patterns of elements during the TR process of LIBs.The analysis reveals that during TR,the gas products generated include approximately 1.5 g of H_(2),23.6 g of CO,88.4 g of CO_(2),8.9 g of C_(2)H_(4),7.3 g of CH_(4),3.7 g of C_(2)H_(6),and 82 g of electrolyte vapor.After TR,the solid compounds formed consist of approximately 2.5 g of LiF,29–92.2 g of elemental Ni/Co/Mn,11.4 g of Li_(2)CO_(3),200.6 g of graphite,1.4 g of NiO,29.6 g of MnO,30.1 g of CoO,67 g of elemental Cu,0.03 g of LiNiO_(2),and 4.3 g of LiAlO_(2).Importantly,the energy released from reactions forming solid compounds during TR surpasses that from gas-forming reactions.This investigation represents the first application of Hess’s law to verify the conservation of elements during the TR process of lithium-ion batteries.The proposed methodology is also applicable to other types of energy storage batteries,effectively advancing techniques for comprehensively investigating lithium battery fire and explosion incidents.
文摘To address various challenges,including delayed traffic accident detection response,poor localization accuracy,and inadequate rescue efficiency,this study presents a YOLOv10-based intelligent detection and classification system.Featuring a three-tier“perception-decision-action”framework,the system uses an enhanced YOLOv10 model for precise accident detection and implements multiscale feature fusion to improve the recognition of diverse accident scenarios.The classification module employs dynamic weighting to assess accidents as mild,moderate,or severe,coupled with a tri-level response protocol.For route optimization,the path planning component uses a refined A*algorithm with a four-dimensional cost function.Tests show that the system delivers 98.2%detection accuracy with subsecond response times,maintains 93.5%reliability in harsh weather,and enhances rescue operations by 23.7%in efficiency.This solution offers a robust technical approach for smart traffic management systems.
基金supported by China Nuclear Power Engineering Co.,Ltd.and Harbin Engineering University,and granted financial resources by China’s National Energy Administration and China National Nuclear Corporation.
文摘The passive containment heat removal system(PCS)is one of the key passive safety systems of China’s third-generation advanced pressurized water reactor-Hua-long Pressurized Reactor(HPR1000),used to prevent overpressure of large concrete containment under severe accident scenarios.This paper provides an overview of the development of the HPR1000 passive containment heat removal system,including its operating principles and configuration,internal heat exchanger design,feasibility tests,engineering-scale PCS verification tests,comprehensive tests on PCS-containment coupling characteristics,among other key supporting studies.These extensive studies demonstrated that the PCS of HPR1000,which is designed based on flashing-driven open natural circulation and efficient condensation heat transfer theory,can work effectively and ensure the integrity of the containment under various accident scenarios.The system has been applied to Fuqing No.5 and No.6 nuclear power units and Zhangzhou No.1 and No.2 units of China’s first million-kilowatt third-generation nuclear power HPR1000.It is also applied to K-2/K-3 units of Karachi Nuclear Power Plant in Pakistan.
