The aerodynamic drag on a train running in an evacuated tube varies with tube air pressure, train speed and shape, as well as blockage ratio. This paper uses numerical simulations to study the effects of different fac...The aerodynamic drag on a train running in an evacuated tube varies with tube air pressure, train speed and shape, as well as blockage ratio. This paper uses numerical simulations to study the effects of different factors on the aerodynamic drag of a train running at subsonic speed in an evacuated tube. Firstly, we present the assumption of a steady state, two dimensional, incompressible viscous flow with lubricity wall conditions. Subsequently, based on the Navier-Stokes equation and the k-c turbulent models, we calculate the aerodynamic drag imposed on the column train with a 3-meter diameter running under different pressure and blockage ratio conditions in an evacuated tube transporta- tion （ETT） system. The simulation is performed with FLUENT 6.3 software package. An analyses of the simulation re- sults suggest that the blockage ratio for ETT should be in the range of 0.25-0.7, and the tube internal diameter in the range of 2-4 m, with the feasible vacuum pressure in the range of 1-10 000 Pa for the future subsonic ETT trains.展开更多
Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges.In the past 10 years,the pavement infrastructure strongly supports the rapid development of the global so...Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges.In the past 10 years,the pavement infrastructure strongly supports the rapid development of the global social economy.New theories,new methods,new technologies and new materials related to pavement engineering are emerging.Deterioration of pavement infrastructure is a typical multi-physics problem.Because of actual coupled behaviors of traffic and environmental conditions,predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material analysis.In order to summarize the current and determine the future research of pavement engineering,Journal of Traffic and Transportation Engineering(English Edition)has launched a review paper on the topic of"New innovations in pavement materials and engineering:A review on pavement engineering research 2021".Based on the joint-effort of 43 scholars from 24 well-known universities in highway engineering,this review paper systematically analyzes the research status and future development direction of 5 major fields of pavement engineering in the world.The content includes asphalt binder performance and modeling,mixture performance and modeling of pavement materials,multi-scale mechanics,green and sustainable pavement,and intelligent pavement.Overall,this review paper is able to provide references and insights for researchers and engineers in the field of pavement engineering.展开更多
The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to opti...The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to optimizing urban logistics spatial patterns and ensuring reasonable resource allocation. Based on Tencent Online Maps Platform from December 2014, 4396 logistics points of interest （POI） were collected in Beijing, China. By the methods of industrial concentration evaluation and kernel density analysis, the spatial distribution pattern of logistics in Beijing are explored, the interaction mechanism among the type differ- ence, supply-demand side factors and location choice behavior are clarified, and the internal mechanism of spatial differentiation under the combined influence of transportation, land rent and assets are revealed. The following conclusions are drawn in the paper. （1） Logistics en- terprises and logistics nodes exhibit the characteristic of both co-agglomeration and spatial separation in location, and logistics activities display the spatial pattern of ＂marginal area of downtown area, suburbs and exurban area＂, which have a weak coupling degree with logis- tics employment space. （2） The public logistics space, namely, logistics parks and logistics centers, is produced under the guidance of the government, and the terminal logistics space consisting of logistics distribution centers serving for the specific industries and terminal users is dominated by enterprises. The Iocational differentiation between the two modes of logistics space is significant. （3） In the formation of the logistics spatial location, the government can change the traffic condition by re-planning the transport routes and freight station locations, and control the land rent and availability of different areas by increasing or decreasing the land use of logistics, to impact the enterprise behavior and form different types of logistics space and function differentiation. In comparison, logistics enterp展开更多
This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous revie...This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous reviews.This study proposes a classification framework for SOM research based on product flow,from its design to its final disposal.Although SOM has been studied for many years,most related research remains conceptual.Our criterion for choosing papers is that they must be relevant to practical problems.This review aims to provide readers a guide that will facilitate their search for papers in their field of interest.More importantly,we hope that this review can provide insightful managerial implications for SOM.展开更多
The ChatGPT,a lite and conversational variant of Generative Pretrained Transformer 4(GPT-4)developed by OpenAI,is one of the milestone Large Language Models(LLMs)with billions of parameters.LLMs have stirred up much i...The ChatGPT,a lite and conversational variant of Generative Pretrained Transformer 4(GPT-4)developed by OpenAI,is one of the milestone Large Language Models(LLMs)with billions of parameters.LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks,which profoundly impact various fields.This paper mainly discusses the future applications of LLMs in dentistry.We introduce two primary LLM deployment methods in dentistry,including automated dental diagnosis and cross-modal dental diagnosis,and examine their potential applications.Especially,equipped with a cross-modal encoder,a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations.We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application.While LLMs offer significant potential benefits,the challenges,such as data privacy,data quality,and model bias,need further study.Overall,LLMs have the potential to revolutionize dental diagnosis and treatment,which indicates a promising avenue for clinical application and research in dentistry.展开更多
With the development of green tribology in the shipping industry,the application of water lubrication gradually replaces oil lubrication in stern bearings and thrust bearings.In terms of large-scale and high-speed shi...With the development of green tribology in the shipping industry,the application of water lubrication gradually replaces oil lubrication in stern bearings and thrust bearings.In terms of large-scale and high-speed ships,water-lubricated bearings with high performance are more strictly required.However,due to the lubricating medium,water-lubricated bearings have many problems such as friction,wear,vibration,noise,etc.This review focuses on the performance of marine water-lubricated bearings and their failure prevention mechanism.Furthermore,the research of marine water-lubricated bearings is reviewed by discussing its lubrication principle,test technology,friction and wear mechanism,and friction noise generation mechanism.The performance enhancement methods have been overviewed from structure optimization and material modification.Finally,the potential problems and the perspective of water-lubricated bearings are given in detail.展开更多
In order to analyze the influence rule of experimental parameters on the energy-absorption characteristics and effectively forecast energy-absorption characteristic of thin-walled structure, the forecast model of GA-B...In order to analyze the influence rule of experimental parameters on the energy-absorption characteristics and effectively forecast energy-absorption characteristic of thin-walled structure, the forecast model of GA-BP hybrid algorithm was presented by uniting respective applicability of back-propagation artificial neural network （BP-ANN） and genetic algorithm （GA）. The detailed process was as follows. Firstly, the GA trained the best weights and thresholds as the initial values of BP-ANN to initialize the neural network. Then, the BP-ANN after initialization was trained until the errors converged to the required precision. Finally, the network model, which met the requirements after being examined by the test samples, was applied to energy-absorption forecast of thin-walled cylindrical structure impacting. After example analysis, the GA-BP network model was trained until getting the desired network error only by 46 steps, while the single BP-ANN model achieved the same network error by 992 steps, which obviously shows that the GA-BP hybrid algorithm has faster convergence rate. The average relative forecast error （ARE） of the SEA predictive results obtained by GA-BP hybrid algorithm is 1.543%, while the ARE of the SEA predictive results obtained by BP-ANN is 2.950%, which clearly indicates that the forecast precision of the GA-BP hybrid algorithm is higher than that of the BP-ANN.展开更多
Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging alo...Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.展开更多
The temperature and moisture of the pavement structure can be greatly influenced by the wind speed above pavement surface.The wind speed above pavement surface not only is dominated by the wind speed of atmosphere,but...The temperature and moisture of the pavement structure can be greatly influenced by the wind speed above pavement surface.The wind speed above pavement surface not only is dominated by the wind speed of atmosphere,but also it is highly related to the landform and buildings around road.However,currently there are no studies about the wind field above pavement surface in consideration of the effect of the landform and buildings.A simulation method,which is combined with geographic information system(GIS),wind data from meteorological observatory and computational fluid dynamics(CFD)software,is employed to study the effect of the landform and the wind speed of atmosphere on the wind field above pavement surface.Three cases are studied,including an urban road,a coastal road and a mountainous road.Furthermore,the wind field distribution above road surface in different wind directions was studied in our work.Results indicate that the wind field above pavement surface can be greatly affected by the landforms,buildings and wind direction.This simulation method can provide reliable results for the wind field above pavement surface.The maximum relative errors between simulated and measured wind speed can be less than 20%in the analysis of the three cases.It is recommended that the CFD simulation method is a good tool to accurately know the wind field above pavement surface.展开更多
Purpose-The design goal for the tracking interval of high-speed railway trains in China is 3 min,but it is difficult to achieve,and it is widely believed that it is mainly limited by the tracking interval of train arr...Purpose-The design goal for the tracking interval of high-speed railway trains in China is 3 min,but it is difficult to achieve,and it is widely believed that it is mainly limited by the tracking interval of train arrivals.If the train arrival tracking interval can be compressed,it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval.The goal of this article is to study how to compress the train arrival tracking interval.Design/methodologylapproach-By simulating the process of dense train groups arriving at the station and stopping,the headway between train arrivals at the station was calculated,and the pattern of train arrival headway was obtained,changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.Findings-When the running speed of trains is high,the headway between trains is short,the length of the station approach throat area is considerable and frequent train arrivals at the station,the arrival headway for the first group or several groups of trains will exceed the headway,but the subsequent sets of trains will havea headway equal to the arrival headway.This convergence characteristic is obtained by appropriately increasing the running time.Originality/value-According to this pattern,there is no need to overly emphasize the impact of train arrival headway on the headway.This plays an important role in compressing train headway and improving high-speedrailwaycapacity.展开更多
Knowledge graph technology is widely applied in the domain of general knowledge reasoning with an excellent performance.For fine-grained professional fields,professional knowledge graphs can provide more accurate info...Knowledge graph technology is widely applied in the domain of general knowledge reasoning with an excellent performance.For fine-grained professional fields,professional knowledge graphs can provide more accurate information in practical industrial scenarios.Based on an aviation assembly domain-specific knowledge graph,the article constructs a joint knowledge reasoning model,which combines a named entity recognition model and a subgraph embedding learning model.When performing knowledge reasoning tasks,the two models vectorize entities,relationships and entity attributes in the same space,so as to share parameters and optimize learning efficiency.The knowledge reasoning model,which provides intelligent question answering services,is able to reduce the assembly error rate and improve the assembly efficiency.The system can accurately solve general knowledge reasoning problems in the assembly process in actual industrial scenarios of general assembly and component assembly under interference-free conditions.Finally,this paper compares the proposed knowledge reasoning model based on knowledge representation learning and the question-answering system based on large-scale pre-trained models.In the application scenario of system functional testing in general assembly,the joint model attains an accuracy rate of 95%,outperforming GPT with 78%accuracy and enhanced representation through knowledge integration with 71%accuracy.展开更多
Cross-line trains, as a link between high-speed and conventional rail networks, will increase the complexity of transport organization and lead to significant challenges in dispatch coordination between the two system...Cross-line trains, as a link between high-speed and conventional rail networks, will increase the complexity of transport organization and lead to significant challenges in dispatch coordination between the two systems. Based on the characteristics of high-speed transport organization, this paper deals with the necessity of dispatch coordination between high-speed and conventional lines from the following two perspectives： the operation of cross-line trains and work coordination in connection stations. An adjustment model for the operation of high-speed trains, taking cross-line trains into account, is established. Finally, the dispatch system is described in terms of construction and process. Methods for organizing dispatch are proposed, and the processes of coordination adjustment under normal and unexpected situations are analyzed. The discussion in this paper may serve as a theoretical basis for the development of high-speed rail dispatch systems.展开更多
A resolved CFD-DEM method is proposed to simulate the fluid-particle interaction for large complex granules.The airflow in a vertical sinter fixed bed is numerically studied using this method.The multi-sphere clumped ...A resolved CFD-DEM method is proposed to simulate the fluid-particle interaction for large complex granules.The airflow in a vertical sinter fixed bed is numerically studied using this method.The multi-sphere clumped method is used to create irregular sinter particles in DEM.The immersed boundary method and dynamic cell refinement are applied to describe the fluid flow around particles with higher resolution,by which the fluid-particle interaction can be simulated more accurately.The simulation results presented the packing voidage distributions and the airflow fields in the sinter beds of different single and mixed particle size ranges.The bed pressure drops were simulated and the results were compared with the corresponding experimental ones.The good agreement indicated that the proposed resolved CFD-DEM method is an effective tool to model the fluid-particle interaction for irregular large granules in the gas-solid multi-phase systems.展开更多
Directed energy deposition-arc(DED-Arc)technology has the advantages of simple equipment,low manufacturing cost and high deposition rate,while the use of DED-Arc has problems of microstructure inhomogeneity,position d...Directed energy deposition-arc(DED-Arc)technology has the advantages of simple equipment,low manufacturing cost and high deposition rate,while the use of DED-Arc has problems of microstructure inhomogeneity,position dependence of macroscopic mechanical properties and anisotropy.Therefore,it is necessary to carry out a subsequent heat treatment to improve its microstructure uniformity,mechanical properties and superelasticity.In this investigation,the DED-Arc 15-layer NiTi alloy thin-walled parts with the solution treatment at different process parameters were studied to analyze the effects of solution heat treatment on microstructure,phase composition,phase transformation,microhardness,tensile and superelasticity.The temperature range of solution treatment is 800-1050℃,and the treatment time range is 1-5.5 h.The results show that after solution treatment at 800℃/1 h,the content of precipitated phase decreases,the grain is refined,the microhardness increases,and the mechanical properties in the 0°direction are improved.The strain recovery rate after 10 tensile cycles has increased from 37.13%(as-built)to 49.25%(solid solution treatment).This research provides an effective post treatment method for high-performance DED-Arc NiTi shape memory alloys.展开更多
Disturbance observer-based control method has achieved good results in the carfollowing scenario of intelligent and connected vehicle(ICV).However,the gain of conventional extended disturbance observer(EDO)-based cont...Disturbance observer-based control method has achieved good results in the carfollowing scenario of intelligent and connected vehicle(ICV).However,the gain of conventional extended disturbance observer(EDO)-based control method is usually set manually rather than adjusted adaptively according to real time traffic conditions,thus declining the car-following performance.To solve this problem,a car-following strategy of ICV using EDO adjusted by reinforcement learning is proposed.Different from the conventional method,the gain of proposed strategy can be adjusted by reinforcement learning to improve its estimation accuracy.Since the“equivalent disturbance”can be compensated by EDO to a great extent,the disturbance rejection ability of the carfollowing method will be improved significantly.Both Lyapunov approach and numerical simulations are carried out to verify the effectiveness of the proposed method.展开更多
Because of its large capacity,high efficiency and energy savings,the subway has gradually become the primary mode of transportation for citizens.A high density of passengers exists within a large-passenger-flow subway...Because of its large capacity,high efficiency and energy savings,the subway has gradually become the primary mode of transportation for citizens.A high density of passengers exists within a large-passenger-flow subway station,and the number of casualties and injuries during a fire emergency is substantial.In this paper,Pathfinder software and on-site measured data of Pingzhou station in Shenzhen(China)were utilized to simulate a fire emergency evacuation in a large-passenger-flow subway station.The Required Safe Egress Time(RSET),number of passengers and flow rates of stairs and escalators were analysed for three fire evacuation scenarios:train fire,platform fire and hall fire.The evacuation time of the train fire,which was 1173 s,was the longest,and 3621 occupants needed to evacuate when the train was fully loaded.Occupants could not complete the evacuation within 6 mins in all three fire evacuation scenarios,which does not meet the current standard requirements and codes.By changing the number of passengers and the number of stairs for evacuation,the flow rate capacity and evacuation time were explored,which have reference values for safety management and emergency evacuation plan optimization during peak hours of subway operation.展开更多
This study presents a hybrid data-mining framework based on feature selection algorithms and clustering methods to perform the pattern discovery of high-speed railway train rescheduling strategies(RSs).The proposed mo...This study presents a hybrid data-mining framework based on feature selection algorithms and clustering methods to perform the pattern discovery of high-speed railway train rescheduling strategies(RSs).The proposed model is composed of two states.In the first state,decision tree,random forest,gradient boosting decision tree(GBDT)and extreme gradient boosting(XGBoost)models are used to investigate the importance of features.The features that have a high influence on RSs are first selected.In the second state,a K-means clustering method is used to uncover the interdependences between RSs and the influencing features,based on the results in the first state.The proposed method can determine the quantitative relationships between RSs and influencing factors.The results clearly show the influences of the factors on RSs,the possibilities of different train operation RSs under different situations,as well as some key time periods and key trains that the controllers should pay more attention to.The research in this paper can help train traffic controllers better understand the train operation patterns and provides direction for optimizing rail traffic RSs.展开更多
Previous studies have found that drivers’physiological conditions can deteriorate under noise conditions,which poses a potential hazard when driving.As a result,it is crucial to identify the status of drivers when ex...Previous studies have found that drivers’physiological conditions can deteriorate under noise conditions,which poses a potential hazard when driving.As a result,it is crucial to identify the status of drivers when exposed to different noises.However,such explo-rations are rarely discussed with short-term physiological indicators,especially for rail transit drivers.In this study,an experiment involving 42 railway transit drivers was conducted with a driving simulator to assess the impact of noise on drivers’physiological responses.Considering the individuals’heterogeneity,this study introduced drivers’noise annoyance to measure their self-noise-adaption.The variances of drivers’heart rate variability(HRV)along with different noise adaptions are explored when exposed to different noise conditions.Several machine learning approaches(support vector machine,K-nearest neighbour and random forest)were then used to classify their physiological status under different noise conditions according to the HRV and drivers’self-noise adaptions.Results indicate that the volume of traffic noise negatively affects drivers’performance in their routines.Drivers with different noise adaptions but exposed to a fixed noise were found with discrepant HRV,demonstrating that noise adaption is highly associated with drivers’physiological status under noises.It is also found that noise adaption inclusion could raise the accuracy of classifications.Overall,the random forests classifier performed the best in identifying the physiological status when exposed to noise conditions for drivers with different noise adaptions.展开更多
Purpose – Straightness measurement of rail weld joint is of essential importance to railway maintenance. Dueto the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint ...Purpose – Straightness measurement of rail weld joint is of essential importance to railway maintenance. Dueto the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a5-m wavelength range, leaving a significant knowledge gap in this field.Design/methodology/approach – In this study, the authors used the well-established inertial referencemethod (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methodshave been applied in different types of rail straightness measurement trollies, respectively. These instrumentswere tested in a high-speed rail section within a certain region of China. The test results were ultimatelyvalidated through using traditional straightedge and feeler gauge methods as reference data to evaluate the railweld joint straightness within the 5-m wavelength range.Findings – The research reveals that IR-method and MCR-method produce reasonably similar measurementresults for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy forwavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed,carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.Originality/value – The research compare two methods’ measurement effects in a longer wavelength rangeand demonstrate the superiority of MCR-method.展开更多
A series of accidents caused by crowds within the last decades evoked a lot of scientific interest in modeling the movement of pedestrian crowds. Based on the discrete element method, a granular dynamic model, in whic...A series of accidents caused by crowds within the last decades evoked a lot of scientific interest in modeling the movement of pedestrian crowds. Based on the discrete element method, a granular dynamic model, in which the human body is simplified as a self-driven sphere, is proposed to simulate the characteristics of crowd flow through an exit. In this model, the repulsive force among people is considered to have an anisotropic feature, and the physical contact force due to body deformation is quantified by the Hertz contact model. The movement of the human body is simulated by applying the second Newton＇s law. The crowd flow through an exit at different desired velocities is studied and simulation results indicated that crowd flow exhibits three distinct states, i.e., smooth state, transition state and phase separation state. In the simulation, the clogging phenomenon occurs more easily when the desired velocity is high and the exit may as a result be totally blocked at a desired velocity of 1.6 m/s or above, leading to faster-to-frozen effect.展开更多
基金supported by the National Natural Science Foundation of China (No. 50678152)the Scientific Plan Fund of Shaanxi Province(No. 2009K09-24)
文摘The aerodynamic drag on a train running in an evacuated tube varies with tube air pressure, train speed and shape, as well as blockage ratio. This paper uses numerical simulations to study the effects of different factors on the aerodynamic drag of a train running at subsonic speed in an evacuated tube. Firstly, we present the assumption of a steady state, two dimensional, incompressible viscous flow with lubricity wall conditions. Subsequently, based on the Navier-Stokes equation and the k-c turbulent models, we calculate the aerodynamic drag imposed on the column train with a 3-meter diameter running under different pressure and blockage ratio conditions in an evacuated tube transporta- tion （ETT） system. The simulation is performed with FLUENT 6.3 software package. An analyses of the simulation re- sults suggest that the blockage ratio for ETT should be in the range of 0.25-0.7, and the tube internal diameter in the range of 2-4 m, with the feasible vacuum pressure in the range of 1-10 000 Pa for the future subsonic ETT trains.
基金National Key R&D Program of China(No.2018YFB1600200,2021YFB1600200)National Natural Science Foundation of China(No.51608457,51778038,51808016,51808403,51908057,51908072,51908165,51908331,52008029,52008069,52078018,52078025,52078049,52078209,52108403,52122809,52178417)+9 种基金Marie Sk?odowska-Curie Individual Fellowships of the European Commission’s Horizon 2020 programme(No.101024139)Natural Science Foundation of Heilongjiang Province(No.JJ2020ZD0015)China Postdoctoral Science Foundation funded project(No.BX20180088)Research Capability Enhancement Program for Young Professors of Beijing University of Civil Engineering and Architecture(No.02080921021)Young Scholars of Beijing Talent Program(No.02082721009)Beijing Municipal Natural Science Foundation and Beijing Municipal Education Commission(No.KZ201910016017)German Research Foundation(No.OE 514/15-1(459436571))Fundamental Research Funds for the Central Universities(No.2020kfyXJJS127)Marie Sk?odowska-Curie Individual Fellowships of the European Commission’s Horizon 2020 Programme(No.101030767)Research Fund for High Level Talent Program(No.22120210108)。
文摘Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges.In the past 10 years,the pavement infrastructure strongly supports the rapid development of the global social economy.New theories,new methods,new technologies and new materials related to pavement engineering are emerging.Deterioration of pavement infrastructure is a typical multi-physics problem.Because of actual coupled behaviors of traffic and environmental conditions,predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material analysis.In order to summarize the current and determine the future research of pavement engineering,Journal of Traffic and Transportation Engineering(English Edition)has launched a review paper on the topic of"New innovations in pavement materials and engineering:A review on pavement engineering research 2021".Based on the joint-effort of 43 scholars from 24 well-known universities in highway engineering,this review paper systematically analyzes the research status and future development direction of 5 major fields of pavement engineering in the world.The content includes asphalt binder performance and modeling,mixture performance and modeling of pavement materials,multi-scale mechanics,green and sustainable pavement,and intelligent pavement.Overall,this review paper is able to provide references and insights for researchers and engineers in the field of pavement engineering.
基金Foundation： National Natural Science Foundation of China, No.41501123, No.71703219
文摘The logistics nodes and logistics enterprises are the core carriers and organiza- tional subjects of the logistics space, and their location characteristics and differentiation strategies are of key importance to optimizing urban logistics spatial patterns and ensuring reasonable resource allocation. Based on Tencent Online Maps Platform from December 2014, 4396 logistics points of interest （POI） were collected in Beijing, China. By the methods of industrial concentration evaluation and kernel density analysis, the spatial distribution pattern of logistics in Beijing are explored, the interaction mechanism among the type differ- ence, supply-demand side factors and location choice behavior are clarified, and the internal mechanism of spatial differentiation under the combined influence of transportation, land rent and assets are revealed. The following conclusions are drawn in the paper. （1） Logistics en- terprises and logistics nodes exhibit the characteristic of both co-agglomeration and spatial separation in location, and logistics activities display the spatial pattern of ＂marginal area of downtown area, suburbs and exurban area＂, which have a weak coupling degree with logis- tics employment space. （2） The public logistics space, namely, logistics parks and logistics centers, is produced under the guidance of the government, and the terminal logistics space consisting of logistics distribution centers serving for the specific industries and terminal users is dominated by enterprises. The Iocational differentiation between the two modes of logistics space is significant. （3） In the formation of the logistics spatial location, the government can change the traffic condition by re-planning the transport routes and freight station locations, and control the land rent and availability of different areas by increasing or decreasing the land use of logistics, to impact the enterprise behavior and form different types of logistics space and function differentiation. In comparison, logistics enterp
基金supported by the National Natural Science Foundation of China(Grant Nos.71671033,71971052,71790614,and 71871207)the Fundamental Research Funds for the Central Universities(Grant No.N2006006)+2 种基金the Project of Promoting Talents in Liaoning Province(Grant No.XLYC1807252)the 111 Project(Grant No.B16009)the Project of Longgang Innovation Research Institute of Shenzhen University(Grant No.SZJR006).
文摘This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous reviews.This study proposes a classification framework for SOM research based on product flow,from its design to its final disposal.Although SOM has been studied for many years,most related research remains conceptual.Our criterion for choosing papers is that they must be relevant to practical problems.This review aims to provide readers a guide that will facilitate their search for papers in their field of interest.More importantly,we hope that this review can provide insightful managerial implications for SOM.
基金supported by the Research and Development Program,West China Hospital of Stomatology,Sichuan University(RD-02-202107)Sichuan Province Science and Technology Support Program(2022NSFSC0743)Sichuan Postdoctoral Science Foundation(TB2022005)grant to H.Huang.
文摘The ChatGPT,a lite and conversational variant of Generative Pretrained Transformer 4(GPT-4)developed by OpenAI,is one of the milestone Large Language Models(LLMs)with billions of parameters.LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks,which profoundly impact various fields.This paper mainly discusses the future applications of LLMs in dentistry.We introduce two primary LLM deployment methods in dentistry,including automated dental diagnosis and cross-modal dental diagnosis,and examine their potential applications.Especially,equipped with a cross-modal encoder,a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations.We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application.While LLMs offer significant potential benefits,the challenges,such as data privacy,data quality,and model bias,need further study.Overall,LLMs have the potential to revolutionize dental diagnosis and treatment,which indicates a promising avenue for clinical application and research in dentistry.
基金financially supported by the National Key R&D Program of China(No.2018YFE0197600)National Natural Science Foundation of China(No.52071244).
文摘With the development of green tribology in the shipping industry,the application of water lubrication gradually replaces oil lubrication in stern bearings and thrust bearings.In terms of large-scale and high-speed ships,water-lubricated bearings with high performance are more strictly required.However,due to the lubricating medium,water-lubricated bearings have many problems such as friction,wear,vibration,noise,etc.This review focuses on the performance of marine water-lubricated bearings and their failure prevention mechanism.Furthermore,the research of marine water-lubricated bearings is reviewed by discussing its lubrication principle,test technology,friction and wear mechanism,and friction noise generation mechanism.The performance enhancement methods have been overviewed from structure optimization and material modification.Finally,the potential problems and the perspective of water-lubricated bearings are given in detail.
基金Project(50175110) supported by the National Natural Science Foundation of ChinaProject(2009bsxt019) supported by the Graduate Degree Thesis Innovation Foundation of Central South University, China
文摘In order to analyze the influence rule of experimental parameters on the energy-absorption characteristics and effectively forecast energy-absorption characteristic of thin-walled structure, the forecast model of GA-BP hybrid algorithm was presented by uniting respective applicability of back-propagation artificial neural network （BP-ANN） and genetic algorithm （GA）. The detailed process was as follows. Firstly, the GA trained the best weights and thresholds as the initial values of BP-ANN to initialize the neural network. Then, the BP-ANN after initialization was trained until the errors converged to the required precision. Finally, the network model, which met the requirements after being examined by the test samples, was applied to energy-absorption forecast of thin-walled cylindrical structure impacting. After example analysis, the GA-BP network model was trained until getting the desired network error only by 46 steps, while the single BP-ANN model achieved the same network error by 992 steps, which obviously shows that the GA-BP hybrid algorithm has faster convergence rate. The average relative forecast error （ARE） of the SEA predictive results obtained by GA-BP hybrid algorithm is 1.543%, while the ARE of the SEA predictive results obtained by BP-ANN is 2.950%, which clearly indicates that the forecast precision of the GA-BP hybrid algorithm is higher than that of the BP-ANN.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3010803)the National Nature Science Foundation of China(Grant No.52272424)+1 种基金the Key R&D Program of Hubei Province of China(Grant No.2023BCB123)the Fundamental Research Funds for the Central Universities(Grant No.WUT:2023IVB079)。
文摘Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.
基金funds from the National Key R&D Program of China(2018YFB1600100)the National Natural Science Foundation of China(52178417)。
文摘The temperature and moisture of the pavement structure can be greatly influenced by the wind speed above pavement surface.The wind speed above pavement surface not only is dominated by the wind speed of atmosphere,but also it is highly related to the landform and buildings around road.However,currently there are no studies about the wind field above pavement surface in consideration of the effect of the landform and buildings.A simulation method,which is combined with geographic information system(GIS),wind data from meteorological observatory and computational fluid dynamics(CFD)software,is employed to study the effect of the landform and the wind speed of atmosphere on the wind field above pavement surface.Three cases are studied,including an urban road,a coastal road and a mountainous road.Furthermore,the wind field distribution above road surface in different wind directions was studied in our work.Results indicate that the wind field above pavement surface can be greatly affected by the landforms,buildings and wind direction.This simulation method can provide reliable results for the wind field above pavement surface.The maximum relative errors between simulated and measured wind speed can be less than 20%in the analysis of the three cases.It is recommended that the CFD simulation method is a good tool to accurately know the wind field above pavement surface.
基金State Railway Corporation of China Limited under the Science and Technology Research and Development Programme(2021X007)China Academy of Railway Research(2021YJ012)+1 种基金National Natural Science Foundation of China(52302417)Natural Science Foundation of Sichuan Province of China(2023NSFSC0906).
文摘Purpose-The design goal for the tracking interval of high-speed railway trains in China is 3 min,but it is difficult to achieve,and it is widely believed that it is mainly limited by the tracking interval of train arrivals.If the train arrival tracking interval can be compressed,it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval.The goal of this article is to study how to compress the train arrival tracking interval.Design/methodologylapproach-By simulating the process of dense train groups arriving at the station and stopping,the headway between train arrivals at the station was calculated,and the pattern of train arrival headway was obtained,changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.Findings-When the running speed of trains is high,the headway between trains is short,the length of the station approach throat area is considerable and frequent train arrivals at the station,the arrival headway for the first group or several groups of trains will exceed the headway,but the subsequent sets of trains will havea headway equal to the arrival headway.This convergence characteristic is obtained by appropriately increasing the running time.Originality/value-According to this pattern,there is no need to overly emphasize the impact of train arrival headway on the headway.This plays an important role in compressing train headway and improving high-speedrailwaycapacity.
基金supported by the National Natural Science Foundation of China(Grant Nos.52275020,62293514,and 91948301).
文摘Knowledge graph technology is widely applied in the domain of general knowledge reasoning with an excellent performance.For fine-grained professional fields,professional knowledge graphs can provide more accurate information in practical industrial scenarios.Based on an aviation assembly domain-specific knowledge graph,the article constructs a joint knowledge reasoning model,which combines a named entity recognition model and a subgraph embedding learning model.When performing knowledge reasoning tasks,the two models vectorize entities,relationships and entity attributes in the same space,so as to share parameters and optimize learning efficiency.The knowledge reasoning model,which provides intelligent question answering services,is able to reduce the assembly error rate and improve the assembly efficiency.The system can accurately solve general knowledge reasoning problems in the assembly process in actual industrial scenarios of general assembly and component assembly under interference-free conditions.Finally,this paper compares the proposed knowledge reasoning model based on knowledge representation learning and the question-answering system based on large-scale pre-trained models.In the application scenario of system functional testing in general assembly,the joint model attains an accuracy rate of 95%,outperforming GPT with 78%accuracy and enhanced representation through knowledge integration with 71%accuracy.
基金one of the key parts of an NNFF (Na-tional Natural Science Foundation) project under grant 60776827:‘Train network operation program with optimization theory and method research’meanwhile is the key research in ‘Study of optimization method and adjustment theory of high-speed train operation’ supported by the Doctoral Program Foundation of Ministry of Education under grant 20090184110011
文摘Cross-line trains, as a link between high-speed and conventional rail networks, will increase the complexity of transport organization and lead to significant challenges in dispatch coordination between the two systems. Based on the characteristics of high-speed transport organization, this paper deals with the necessity of dispatch coordination between high-speed and conventional lines from the following two perspectives： the operation of cross-line trains and work coordination in connection stations. An adjustment model for the operation of high-speed trains, taking cross-line trains into account, is established. Finally, the dispatch system is described in terms of construction and process. Methods for organizing dispatch are proposed, and the processes of coordination adjustment under normal and unexpected situations are analyzed. The discussion in this paper may serve as a theoretical basis for the development of high-speed rail dispatch systems.
基金the financial support for this work from the National Natural Science Foundation of China(grant No.52104340)China Postdoctoral Science Foundation(grant No.2020M672425)+1 种基金The Key Research and Development Program of Hubei Province(grant No.2022BCA058)Natural Science Foundation of Hubei Province(grant No.2020CFB133).
文摘A resolved CFD-DEM method is proposed to simulate the fluid-particle interaction for large complex granules.The airflow in a vertical sinter fixed bed is numerically studied using this method.The multi-sphere clumped method is used to create irregular sinter particles in DEM.The immersed boundary method and dynamic cell refinement are applied to describe the fluid flow around particles with higher resolution,by which the fluid-particle interaction can be simulated more accurately.The simulation results presented the packing voidage distributions and the airflow fields in the sinter beds of different single and mixed particle size ranges.The bed pressure drops were simulated and the results were compared with the corresponding experimental ones.The good agreement indicated that the proposed resolved CFD-DEM method is an effective tool to model the fluid-particle interaction for irregular large granules in the gas-solid multi-phase systems.
基金The study was supported by the National Natural Science Foundation of China(No.52105396).The authors thank the State Key Laboratory of Materials Processing and Die&Mould Technology,and the Analytical&Testing Center,Huazhong University of Science&Technology for the extensive experiments.
文摘Directed energy deposition-arc(DED-Arc)technology has the advantages of simple equipment,low manufacturing cost and high deposition rate,while the use of DED-Arc has problems of microstructure inhomogeneity,position dependence of macroscopic mechanical properties and anisotropy.Therefore,it is necessary to carry out a subsequent heat treatment to improve its microstructure uniformity,mechanical properties and superelasticity.In this investigation,the DED-Arc 15-layer NiTi alloy thin-walled parts with the solution treatment at different process parameters were studied to analyze the effects of solution heat treatment on microstructure,phase composition,phase transformation,microhardness,tensile and superelasticity.The temperature range of solution treatment is 800-1050℃,and the treatment time range is 1-5.5 h.The results show that after solution treatment at 800℃/1 h,the content of precipitated phase decreases,the grain is refined,the microhardness increases,and the mechanical properties in the 0°direction are improved.The strain recovery rate after 10 tensile cycles has increased from 37.13%(as-built)to 49.25%(solid solution treatment).This research provides an effective post treatment method for high-performance DED-Arc NiTi shape memory alloys.
基金State Key Laboratory of Automotive Safety and Energy,Grant/Award Number:KFY2208National Natural Science Foundation of China,Grant/Award Numbers:U2013601,U20A20225+1 种基金Key Research and Development Plan of Anhui Province,Grant/Award Number:202004a05020058the Natural Science Foundation of Hefei,China(Grant No.2021032)。
文摘Disturbance observer-based control method has achieved good results in the carfollowing scenario of intelligent and connected vehicle(ICV).However,the gain of conventional extended disturbance observer(EDO)-based control method is usually set manually rather than adjusted adaptively according to real time traffic conditions,thus declining the car-following performance.To solve this problem,a car-following strategy of ICV using EDO adjusted by reinforcement learning is proposed.Different from the conventional method,the gain of proposed strategy can be adjusted by reinforcement learning to improve its estimation accuracy.Since the“equivalent disturbance”can be compensated by EDO to a great extent,the disturbance rejection ability of the carfollowing method will be improved significantly.Both Lyapunov approach and numerical simulations are carried out to verify the effectiveness of the proposed method.
基金This study has been sponsored by the Fire Bureau of the Ministry of Public Security(Grant No.2016XFGG05)the Sichuan Mineral Resources Research Center(Grant No.SCKCZY2022-YB010)the Key Laboratory of Flight Techniques and Flight Safety,CAAC(Grant No.FZ2021KF05).
文摘Because of its large capacity,high efficiency and energy savings,the subway has gradually become the primary mode of transportation for citizens.A high density of passengers exists within a large-passenger-flow subway station,and the number of casualties and injuries during a fire emergency is substantial.In this paper,Pathfinder software and on-site measured data of Pingzhou station in Shenzhen(China)were utilized to simulate a fire emergency evacuation in a large-passenger-flow subway station.The Required Safe Egress Time(RSET),number of passengers and flow rates of stairs and escalators were analysed for three fire evacuation scenarios:train fire,platform fire and hall fire.The evacuation time of the train fire,which was 1173 s,was the longest,and 3621 occupants needed to evacuate when the train was fully loaded.Occupants could not complete the evacuation within 6 mins in all three fire evacuation scenarios,which does not meet the current standard requirements and codes.By changing the number of passengers and the number of stairs for evacuation,the flow rate capacity and evacuation time were explored,which have reference values for safety management and emergency evacuation plan optimization during peak hours of subway operation.
基金This work was supported by the National Natural Science Foundation of China(Grant No.71871188)The authors also acknowledge the Open Fund of Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle and the support of the State Key Laboratory of Rail Traffic Control(Grant No.RCS2019K007).Finally,the authors are grateful for the useful contributions made by their project partners.
文摘This study presents a hybrid data-mining framework based on feature selection algorithms and clustering methods to perform the pattern discovery of high-speed railway train rescheduling strategies(RSs).The proposed model is composed of two states.In the first state,decision tree,random forest,gradient boosting decision tree(GBDT)and extreme gradient boosting(XGBoost)models are used to investigate the importance of features.The features that have a high influence on RSs are first selected.In the second state,a K-means clustering method is used to uncover the interdependences between RSs and the influencing features,based on the results in the first state.The proposed method can determine the quantitative relationships between RSs and influencing factors.The results clearly show the influences of the factors on RSs,the possibilities of different train operation RSs under different situations,as well as some key time periods and key trains that the controllers should pay more attention to.The research in this paper can help train traffic controllers better understand the train operation patterns and provides direction for optimizing rail traffic RSs.
基金supported by the Sichuan Mineral Resources Research Center(Gr ant No.SCKCZY2023-ZC010)the Gansu Tec h-nological Innovation Guidance Plan(Grant No.22CX8JA142)+2 种基金the Sc hool Enter prise Cooperation Program of Southwest Jiao-tong Univ ersity(Grant No.LG-YY-CW-2020010)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety(Grant No.FZ2021KF05)the Key Research Base of Humanistic and Social Sciences of Deyang-Psychology and Behavior Science Research Center(Grant No.XLYXW2023202).
文摘Previous studies have found that drivers’physiological conditions can deteriorate under noise conditions,which poses a potential hazard when driving.As a result,it is crucial to identify the status of drivers when exposed to different noises.However,such explo-rations are rarely discussed with short-term physiological indicators,especially for rail transit drivers.In this study,an experiment involving 42 railway transit drivers was conducted with a driving simulator to assess the impact of noise on drivers’physiological responses.Considering the individuals’heterogeneity,this study introduced drivers’noise annoyance to measure their self-noise-adaption.The variances of drivers’heart rate variability(HRV)along with different noise adaptions are explored when exposed to different noise conditions.Several machine learning approaches(support vector machine,K-nearest neighbour and random forest)were then used to classify their physiological status under different noise conditions according to the HRV and drivers’self-noise adaptions.Results indicate that the volume of traffic noise negatively affects drivers’performance in their routines.Drivers with different noise adaptions but exposed to a fixed noise were found with discrepant HRV,demonstrating that noise adaption is highly associated with drivers’physiological status under noises.It is also found that noise adaption inclusion could raise the accuracy of classifications.Overall,the random forests classifier performed the best in identifying the physiological status when exposed to noise conditions for drivers with different noise adaptions.
文摘Purpose – Straightness measurement of rail weld joint is of essential importance to railway maintenance. Dueto the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a5-m wavelength range, leaving a significant knowledge gap in this field.Design/methodology/approach – In this study, the authors used the well-established inertial referencemethod (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methodshave been applied in different types of rail straightness measurement trollies, respectively. These instrumentswere tested in a high-speed rail section within a certain region of China. The test results were ultimatelyvalidated through using traditional straightedge and feeler gauge methods as reference data to evaluate the railweld joint straightness within the 5-m wavelength range.Findings – The research reveals that IR-method and MCR-method produce reasonably similar measurementresults for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy forwavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed,carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.Originality/value – The research compare two methods’ measurement effects in a longer wavelength rangeand demonstrate the superiority of MCR-method.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71473207,51178445,and 71103148)the Research Grant Council,Government of Hong Kong,China(Grant No.City U119011)the Fundamental Research Funds for the Central Universities,China(Grant Nos.2682014CX103 and 2682014RC05)
文摘A series of accidents caused by crowds within the last decades evoked a lot of scientific interest in modeling the movement of pedestrian crowds. Based on the discrete element method, a granular dynamic model, in which the human body is simplified as a self-driven sphere, is proposed to simulate the characteristics of crowd flow through an exit. In this model, the repulsive force among people is considered to have an anisotropic feature, and the physical contact force due to body deformation is quantified by the Hertz contact model. The movement of the human body is simulated by applying the second Newton＇s law. The crowd flow through an exit at different desired velocities is studied and simulation results indicated that crowd flow exhibits three distinct states, i.e., smooth state, transition state and phase separation state. In the simulation, the clogging phenomenon occurs more easily when the desired velocity is high and the exit may as a result be totally blocked at a desired velocity of 1.6 m/s or above, leading to faster-to-frozen effect.
