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
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
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
Background:Falls are a significant public health concern among older adults,often leading to severe injuries and decreased quality of life.Fall prevention self-management behaviors are critical in reducing fall risk.H...Background:Falls are a significant public health concern among older adults,often leading to severe injuries and decreased quality of life.Fall prevention self-management behaviors are critical in reducing fall risk.However,the status and influencing factors of these behaviors among community-dwelling older adults in China remain poorly understood.This study aimed to investigate fall prevention self-management behaviors and their influencing factors among community-dwelling older adults in Fuzhou,China.Methods:From June to December 2022,we used multi-stage cluster random sampling and invited 675 community-dwelling older adults from Fujian as participants.We conducted a questionnaire survey using the general information questionnaire,Fall Prevention Self-management Behavior among Older Adults Questionnaire,Questionnaire on Knowledge,Belief,and Practice of Falls Prevention among Older Adults in Community,Modified Falls Efficacy Scale,Social Support Rating Scale,and Chinese Version of the Self-Assessment Fall Risk Scale for Older Adults.Multivariate linear regression was used to identify the factors influencing fall prevention self-management behavior among older adults.Results:The overall score of fall prevention self-management behaviors was 146.81±34.22,indicating a moderate level.Key influencing factors included education level,pre-retirement occupation,income,medication type,self-assessed physical condition,fear of falling,knowledge and practices in fall prevention,social support,and fall risk.These factors collectively explained 34.3%of the variance in self-management behaviors.Conclusion:The findings highlight the need for targeted interventions to enhance fall prevention self-management among community-dwelling older adults.Interventions should focus on improving knowledge,strengthening social support,and addressing psychological barriers such as fear of falling.This study provides valuable insights for developing community-based strategies to reduce fall risks and promote healthy aging.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
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
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
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
Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the c...Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.展开更多
The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving ...The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving reliability, an approach for assessing the effect of driving erroneous actions on the dynamic performance of the driver vehicle system is presented. The analysis of driving erroneous actions in the driver vehicle system has been performed to show that the reliability during perception with variety widely could result in the incidents and/or accidents in traffic system.展开更多
More than 100 t of nitrobenzene (NB) and related compounds were discharged into the Songhua River,the fourth longest river in China,because of the world-shaking explosion of an aniline production factory located in Ji...More than 100 t of nitrobenzene (NB) and related compounds were discharged into the Songhua River,the fourth longest river in China,because of the world-shaking explosion of an aniline production factory located in Jilin City on November 13,2005.As one of the efforts to predict the fate of residual NB in the river,NB biodegradation abilities by microbes in the water and sediments from different river sections were evaluated systematically.The results indicated that microbial communities from any section of ...展开更多
Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The exi...Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inad- equate human-aircraft-environment interactions and organizational deficiencies effectively, and highly depend on analysts＇ skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphi^taxonomic-associative approach. A new graphic model named accident tree （AceiTree）, with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system （HFACS） to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to fac- tors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.展开更多
Lower limb injures are frequently observed in passenger car traffic accidents.Previous studies of the injuries focus on long bone fractures by using either cadaver component tests or simulations of the long bone kinem...Lower limb injures are frequently observed in passenger car traffic accidents.Previous studies of the injuries focus on long bone fractures by using either cadaver component tests or simulations of the long bone kinematics,which lack in-depth study on the fractures in stress analysis.This paper aims to investigate lower limb impact biomechanics in real-world car to pedestrian accidents and to predict fractures of long bones in term of stress parameter for femur,tibia,and fibula.For the above purposes,a 3D finite element(FE) model of human body lower limb(HBM-LL) is developed based on human anatomy.The model consists of the pelvis,femur,tibia,fibula,patella,foot bones,primary tendons,knee joint capsule,meniscus,and ligaments.The FE model is validated by comparing the results from a lateral impact between simulations and tests with cadaver lower limb specimens.Two real-world accidents are selected from an in-depth accident database with detailed information about the accident scene,car impact speed,damage to the car,and pedestrian injuries.Multi-body system(MBS) models are used to reconstruct the kinematics of the pedestrians in the two accidents and the impact conditions are calculated for initial impact velocity and orientations of the car and pedestrian during the collision.The FE model is used to perform injury reconstructions and predict the fractures by using physical parameters,such as von Mises stress of long bones.The calculated failure level of the long bones is correlated with the injury outcomes observed from the two accident cases.The reconstruction result shows that the HBM-LL FE model has acceptable biofidelity and can be applied to predict the risk of long bone fractures.This study provides an efficient methodology to investigate the long bone fracture suffered from vehicle traffic collisions.展开更多
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.
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 community of older adults who participated in this study.Ministry of Education Science and Technology Industry-University Co-operation Collaborative Education Project(230806630292310).
文摘Background:Falls are a significant public health concern among older adults,often leading to severe injuries and decreased quality of life.Fall prevention self-management behaviors are critical in reducing fall risk.However,the status and influencing factors of these behaviors among community-dwelling older adults in China remain poorly understood.This study aimed to investigate fall prevention self-management behaviors and their influencing factors among community-dwelling older adults in Fuzhou,China.Methods:From June to December 2022,we used multi-stage cluster random sampling and invited 675 community-dwelling older adults from Fujian as participants.We conducted a questionnaire survey using the general information questionnaire,Fall Prevention Self-management Behavior among Older Adults Questionnaire,Questionnaire on Knowledge,Belief,and Practice of Falls Prevention among Older Adults in Community,Modified Falls Efficacy Scale,Social Support Rating Scale,and Chinese Version of the Self-Assessment Fall Risk Scale for Older Adults.Multivariate linear regression was used to identify the factors influencing fall prevention self-management behavior among older adults.Results:The overall score of fall prevention self-management behaviors was 146.81±34.22,indicating a moderate level.Key influencing factors included education level,pre-retirement occupation,income,medication type,self-assessed physical condition,fear of falling,knowledge and practices in fall prevention,social support,and fall risk.These factors collectively explained 34.3%of the variance in self-management behaviors.Conclusion:The findings highlight the need for targeted interventions to enhance fall prevention self-management among community-dwelling older adults.Interventions should focus on improving knowledge,strengthening social support,and addressing psychological barriers such as fear of falling.This study provides valuable insights for developing community-based strategies to reduce fall risks and promote healthy aging.
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.
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.
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 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.
基金support provided by the Qingdao Science and Technology Benefits People Demonstration and Guidance Project(21-1-4-sf-4-nsh).
文摘Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.
文摘The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving reliability, an approach for assessing the effect of driving erroneous actions on the dynamic performance of the driver vehicle system is presented. The analysis of driving erroneous actions in the driver vehicle system has been performed to show that the reliability during perception with variety widely could result in the incidents and/or accidents in traffic system.
文摘More than 100 t of nitrobenzene (NB) and related compounds were discharged into the Songhua River,the fourth longest river in China,because of the world-shaking explosion of an aniline production factory located in Jilin City on November 13,2005.As one of the efforts to predict the fate of residual NB in the river,NB biodegradation abilities by microbes in the water and sediments from different river sections were evaluated systematically.The results indicated that microbial communities from any section of ...
基金co-supported by the Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China (IRT0905)the Step Program of Beijing Key Laboratory (No. Z121104002812053)
文摘Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inad- equate human-aircraft-environment interactions and organizational deficiencies effectively, and highly depend on analysts＇ skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphi^taxonomic-associative approach. A new graphic model named accident tree （AceiTree）, with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system （HFACS） to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to fac- tors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.
基金supported by National Hi-tech Research and Development Program of China (863 Program,Grant No. 2006AA110101)"111 Program" of Ministry of Education and State Administration of Foreign Experts Affairs of China (Grant No. 111-2-11)+1 种基金General Motors Research and Development Center (Grant No. RD-209)Project of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body,Hunan University,China (Grant No. 60870004)
文摘Lower limb injures are frequently observed in passenger car traffic accidents.Previous studies of the injuries focus on long bone fractures by using either cadaver component tests or simulations of the long bone kinematics,which lack in-depth study on the fractures in stress analysis.This paper aims to investigate lower limb impact biomechanics in real-world car to pedestrian accidents and to predict fractures of long bones in term of stress parameter for femur,tibia,and fibula.For the above purposes,a 3D finite element(FE) model of human body lower limb(HBM-LL) is developed based on human anatomy.The model consists of the pelvis,femur,tibia,fibula,patella,foot bones,primary tendons,knee joint capsule,meniscus,and ligaments.The FE model is validated by comparing the results from a lateral impact between simulations and tests with cadaver lower limb specimens.Two real-world accidents are selected from an in-depth accident database with detailed information about the accident scene,car impact speed,damage to the car,and pedestrian injuries.Multi-body system(MBS) models are used to reconstruct the kinematics of the pedestrians in the two accidents and the impact conditions are calculated for initial impact velocity and orientations of the car and pedestrian during the collision.The FE model is used to perform injury reconstructions and predict the fractures by using physical parameters,such as von Mises stress of long bones.The calculated failure level of the long bones is correlated with the injury outcomes observed from the two accident cases.The reconstruction result shows that the HBM-LL FE model has acceptable biofidelity and can be applied to predict the risk of long bone fractures.This study provides an efficient methodology to investigate the long bone fracture suffered from vehicle traffic collisions.
