Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained promi...Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained prominence across various engineering sectors,including the manufacturing and construction industries.Specifically,road engineering has demonstrated a growing interest in DT and has achieved promising results in DT-related applications over the past several years.This paper systematically introduces the development of DT and examines its current state in road engineering by reviewing research articles on DT-enabling technologies,such as model creation,condition sensing,data processing,and interaction,as well as its applications throughout the lifecycle of road infrastructure.The findings indicate that research has primarily focused on data perception and virtual model creation,while realtime data processing and interaction between physical and virtual models remain underexplored.DT in road engineering has been predominantly applied during the operation and maintenance phases,with limited attention given to the construction and demolition phases.Future efforts should focus on establishing uniform standards,developing innovative perception and data interaction techniques,optimizing development costs,and expanding the scope of lifecycle applications to facilitate the digital transformation of road engineering.This review provides a comprehensive overview of state-of-the-art advancements in this field and paves the way for leveraging DT in road infrastructure lifecycle management.展开更多
The authors apologize for the erroneous transcription of the average chemical composition data of Apollo lunar soil samples in Table 4.The difference in chemical composition between lunar regolith simulants and actual...The authors apologize for the erroneous transcription of the average chemical composition data of Apollo lunar soil samples in Table 4.The difference in chemical composition between lunar regolith simulants and actual lunar samples is an important indicator for evaluating their similarity.For comparison,Table 4 lists the chemical compositions of Apollo 12,Apollo 14,Apollo 15,Apollo 16,and other classic lunar regolith simulants.However,the Apollo lunar soil data in the original Table 4 contained errors,which have been corrected in this corrigendum.展开更多
The increase in population and vehicles exacerbates traffic congestion and management difficulties.Therefore,achieving accurate and efficient traffic flow prediction is crucial for urban transportation.For that reason...The increase in population and vehicles exacerbates traffic congestion and management difficulties.Therefore,achieving accurate and efficient traffic flow prediction is crucial for urban transportation.For that reason,we propose a graph federated learning-based digital twin traffic flow prediction method(GFLDT)by integrating the benefits of collaborative intelligence and computation of intelligent IoT.Specifically,we construct a digital twin network for predicting traffic flow,which is divided into client twin and global twin.Based on this,we adopt the concept of graph federated learning to learn the temporal dependence of traffic flow using local data from client twins,and the spatial dependence of traffic flow using global information from global twins.In addition,we validate on a real traffic dataset,and the results show that through collaborative training of the client twins and the global twins,GFLDT achieves accurate traffic flow prediction while protecting data security.展开更多
Pre-chamber ignition technology can address the issue of uneven in-cylinder mixture combustion in large-bore marine engines.The impact of various pre-chamber structures on the formation of the mixture and jet flames w...Pre-chamber ignition technology can address the issue of uneven in-cylinder mixture combustion in large-bore marine engines.The impact of various pre-chamber structures on the formation of the mixture and jet flames within the pre-chamber is explored.This study performed numerical simulations on a large-bore marine ammonia/hydrogen pre-chamber engine prototype,considering pre-chamber volume,throat diameter,the distance between the hydrogen injector and the spark plug,and the hydrogen injector angle.Compared with the original engine,when the pre-chamber volume is 73.4 ml,the throat diameter is 14 mm,the distance ratio is 0.92,and the hydrogen injector angle is 80°.Moreover,the peak pressure in the pre-chamber increased by 23.1%,and that in the main chamber increased by 46.3%.The results indicate that the performance of the original engine is greatly enhanced by altering its fuel and pre-chamber structure.展开更多
The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is m...The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.展开更多
The addition of high-content crumb rubber(HCCR)in asphalt can effectively address waste tire pollution and provide sustainable environmental and economic advantages.However,the practical application of conventional ru...The addition of high-content crumb rubber(HCCR)in asphalt can effectively address waste tire pollution and provide sustainable environmental and economic advantages.However,the practical application of conventional rubberized binders is significantly limited by high viscosity and poor storage stability.To address these issues,researchers have pretreated crumb rubber(CR)with oil,but high-temperature performance remains insufficient.Therefore,this study aimed to optimize the viscosity,storage stability,and rheological properties of high-content crumb rubber-modified asphalt(HCCRMA)by varying the pretreatment levels of CR and incorporating various additives,including styrene-butadiene-styrene(SBS),deoiled asphalt(DA),or recycled low-density polyethylene(RLDPE).In addition,CR was pretreated with waste cooking oil(WCO)at various ratios,pre-swelling temperatures,and times.The results show that DA exhibits excellent storage stability and lower viscosity compared with other modifiers in HCCRMA,and the 4%RLDPE with pretreated HCCR has the greatest high-temperature rutting resistance.The inclusion of RLDPE increases the stiffness and elasticity of the modified asphalt,which results in greater high-temperature performance.Additionally,the fluorescence microscopy(FM)test confirms that SBS exhibits better dispersion than other modifiers and forms a more homogeneous phase separation in the HCCRMA.All in all,this research achieved an optimal balance of storage stability and rheological properties in asphalt modified with pretreated HCCR and 6%SBS,which provides a valuable reference for performance improvement of HCCR-modified binders.展开更多
Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sen...Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.展开更多
Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements ...Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.展开更多
Waste plastics,such as waste polyethylene terephthalate(PET)beverage bottles and waste rubber tyres are major municipal solid wastes,which may lead to various environmental problems if they are not appropriately recyc...Waste plastics,such as waste polyethylene terephthalate(PET)beverage bottles and waste rubber tyres are major municipal solid wastes,which may lead to various environmental problems if they are not appropriately recycled.In this study,the feasibility of collectively recycling the two types of waste into performance-increasing modifiers for asphalt pavements was analyzed.This study aimed to investigate the recycling mechanisms of waste PET-derived additives under the treatment of two amines,triethylenetetramine(TETA)and ethanolamine(EA),and characterize the performances of these additives in modifying rubberized bitumen,a bitumen modified by waste tyre rubber.To this end,infrared spectroscopy and thermal analyses were carried out on the two PET-derived additives(PET–TETA and PET–EA).In addition,infrared spectroscopy,viscosity,dynamic shear rheology,and multiple stress creep recovery tests were performed on the rubberized bitumen samples modified by the two PET-derived additives.We concluded that waste PET can be chemically upcycled into functional additives,which can increase the overall performance of the rubberized bitumen.The recycling method developed in this study not only helps alleviate the landfilling problems of both waste PET plastic and scrap tyres,but also turns these wastes into value-added new materials for building durable pavements.展开更多
To improve the level of active traffic management,a short-term traffic flow prediction model is proposed by combining phase space reconstruction(PSR)and extreme gradient boosting(XGBoost)algorithms.Firstly,the traditi...To improve the level of active traffic management,a short-term traffic flow prediction model is proposed by combining phase space reconstruction(PSR)and extreme gradient boosting(XGBoost)algorithms.Firstly,the traditional data preprocessing method is improved.The new method uses hierarchical clustering to determine the traffic flow state and fills in missing and abnormal data according to different traffic flow states.Secondly,one-dimensional data are mapped into a multidimensional data matrix through PSR,and the time series complex network is used to verify the data reconstruction effect.Finally,the multidimensional data matrix is inputted into the XGBoost model to predict future traffic flow parameters.The experimental results show that the mean square error,average absolute error,and average absolute percentage error of the prediction results of the PSR-XGBoost model are 5.399%,1.632%,and 6.278%,respectively,and the required running time is 17.35 s.Compared with mathematical-statistical models and other machine learning models,the PSR-XGBoost model has clear advantages in multiple predictive indicators,proving its feasibility and superiority in short-term traffic flow prediction.展开更多
Accurate prediction of road traffic flow is a significant part in the intelligent transportation systems.Accurate prediction can alleviate traffic congestion,and reduce environmental pollution.For the management depar...Accurate prediction of road traffic flow is a significant part in the intelligent transportation systems.Accurate prediction can alleviate traffic congestion,and reduce environmental pollution.For the management department,it can make effective use of road resources.For individuals,it can help people plan their own travel paths,avoid congestion,and save time.Owing to complex factors on the road,such as damage to the detector and disturbances from environment,the measured traffic volume can contain noise.Reducing the influence of noise on traffic flow prediction is a piece of very important work.Therefore,in this paper we propose a combination algorithm of denoising and BILSTM to effectively improve the performance of traffic flow prediction.At the same time,three denoising algorithms are compared to find the best combination mode.In this paper,the wavelet(WL) denoising scheme,the empirical mode decomposition(EMD) denoising scheme,and the ensemble empirical mode decomposition(EEMD) denoising scheme are all introduced to suppress outliers in traffic flow data.In addition,we combine the denoising schemes with bidirectional long short-term memory(BILSTM)network to predict the traffic flow.The data in this paper are cited from performance measurement system(PeMS).We choose three kinds of road data(mainline,off ramp,on ramp) to predict traffic flow.The results for mainline show that data denoising can improve prediction accuracy.Moreover,prediction accuracy of BILSTM+EEMD scheme is the highest in the three methods(BILSTM+WL,BILSTM+EMD,BILSTM+EEMD).The results for off ramp and on ramp show the same performance as the results for mainline.It is indicated that this model is suitable for different road sections and long-term prediction.展开更多
The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and cons...The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.展开更多
In order to investigate enhancements to cell transmission model (CTM) as a tool for traffic signal timing in oversaturated conditions, randomly distributed saturation flow rates and arrival rates were used instead of ...In order to investigate enhancements to cell transmission model (CTM) as a tool for traffic signal timing in oversaturated conditions, randomly distributed saturation flow rates and arrival rates were used instead of constant values to simulate traffic flow movement, estimate the average delay of the network and search for an optimal traffic signal timing plan. A case study was given to demonstrate that the proposed methodology can capture unique phenomena in oversaturated conditions such as forward wave, spillback and lane entrance blockage. The results show that CTM underestimates travel time by 25% when compared to Simtraffic, while the enhanced CTM underestimates by only 3%. A second case study shows that a dynamic signal timing plan is superior to a fixed signal timing plan in the term of average delay.展开更多
To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS...To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS is proposed,whereby the network reliability and experiential learning theory are introduced into the decision process for the travelers’route choice.The intelligent highway serves all the travelers who drive on it,whereas ATIS serves vehicles equipped with information systems.Travelers who drive on intelligent highways or vehicles equipped with ATIS determine their trip routes based on real-time traffic information,whereas other travelers use both the road network conditions from the previous day and historical travel experience to choose a route.Both roadway capacity degradation and travel demand fluctuations are considered to demonstrate the uncertainties in the network.The theory of traffic network flow is developed to build a DTD model considering information from intelligent highway and ATIS.The fixed point theorem is adopted to investigate the equivalence,existence and stability of the proposed DTD model.Numerical examples illustrate that using a high confidence level and weight parameter for the traffic flow reduces the stability of the proposed model.The traffic flow reaches a steady state as travelers’routes shift with repetitive learning of road conditions.The proposed model can be used to formulate scientific traffic organization and diversion schemes during road expansion or reconstruction.展开更多
Short-term traffic flow is one of the core technologies to realize traffic flow guidance. In this article, in view of the characteristics that the traffic flow changes repeatedly, a short-term traffic flow forecasting...Short-term traffic flow is one of the core technologies to realize traffic flow guidance. In this article, in view of the characteristics that the traffic flow changes repeatedly, a short-term traffic flow forecasting method based on a three-layer K-nearest neighbor non-parametric regression algorithm is proposed. Specifically, two screening layers based on shape similarity were introduced in K-nearest neighbor non-parametric regression method, and the forecasting results were output using the weighted averaging on the reciprocal values of the shape similarity distances and the most-similar-point distance adjustment method. According to the experimental results, the proposed algorithm has improved the predictive ability of the traditional K-nearest neighbor non-parametric regression method, and greatly enhanced the accuracy and real-time performance of short-term traffic flow forecasting.展开更多
In civil engineering, the nonlinear dynamic instability of structures occurs at a bifurcation point or a limit point. The instability at a bifurcation point can be analyzed with the theory of nonlinear dynamics, and t...In civil engineering, the nonlinear dynamic instability of structures occurs at a bifurcation point or a limit point. The instability at a bifurcation point can be analyzed with the theory of nonlinear dynamics, and that at a limit point can be discussed with the theory of elastoplasticity. In this paper, the nonlinear dynamic instability of structures was treated with mathematical and mechanical theories. The research methods for the problems of structural nonlinear dynamic stability were discussed first, and then the criterion of stability or instability of structures, the method to obtain the bifurcation point and the limit point, and the formulae of the directions of the branch solutions at a bifurcation point were elucidated. These methods can be applied to the problems of nonlinear dynamic instability of structures such as reticulated shells, space grid structures, and so on. Key words nonlinear dynamic instability - engineering structures - non-stationary nonlinear system - bifurcation point - instability at a bifurcation point - limit point MSC 2000 74K25 Project supported by the Science Foundation of Shanghai Municipal Commission of Education (Grant No. 02AK04), the Science Foundation of Shanghai Municipal Commission of Science and Technology (Grant No. 02ZA14034)展开更多
The expressway traffc incidents have the characteristics of high harmful, strong destructive and refractory.Incident detection can guarantee smooth operation of the expressway, reduce traffc congestion and avoid secon...The expressway traffc incidents have the characteristics of high harmful, strong destructive and refractory.Incident detection can guarantee smooth operation of the expressway, reduce traffc congestion and avoid secondary accident by informing the accident, detection and treatment timely. In this paper, an incident detection method is proposed using the toll station data that takes into account the traffc ratio at the entrances and crossway in the network. The expressway traffc simulation model is improved and a simulation algorithm is established to describe the movement of the vehicles. A numerical example is experimented on the expressway network of Shandong province. The proposed method can effectively detect the expressway incidents, and dynamically estimate the traffc network states so as to provide advice for the highway management department.展开更多
An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation d...An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation duration, variations of fixation points, and the distribution of glance zone. It was found that driving experience had a significant effect on driver eye movement behavior. The percentage of fixation duration to total glance time for inexperienced drivers was 61.5%, while the percentage for experienced drivers was 50.2%. Moreover, the majority of drivers paid attention to the left region of the field of view more frequently than the central and the right regions. This study indicates that it takes inexperienced drivers more time to recognize traffic signs. The findings from this study will assist traffic engineers in designing and installing the traffic signs in an optimal way.展开更多
Most of the current studies on drunk driving accidents focus on law making and public education. However, especially in China, there is less statistical analysis on the severity of drunk driving accidents between driv...Most of the current studies on drunk driving accidents focus on law making and public education. However, especially in China, there is less statistical analysis on the severity of drunk driving accidents between driving under the influence of alcohol (DUI) and driving while intoxicated (DWI). 3368 drunk driving related crashes were collected from the blood-alcohol test report in a city of China at 2012 and 2013. After data pre-processing, Chi-square tests were used to analyze the association between different variables and the type of drunk driving. The logistic regression model is conducted to estimate the effect of the variables under DUI and DWI. The results show that Hour of the day, Driver’s age, Driver’s casualties and Accident area have significant correlation with drunk driving. There was a slightly decrease by 0.995 per year with age and a slightly increase by 1.014 with time in the possibility of DWI. DWI is more likely to cause death in traffic accidents (OR = 1.316) than DUI. Driver’s deaths (OR = 2.346) is more likely to happen than the injuries (OR = 1.910) under DWI cases. These findings show that more attention should be paid to strengthen controls on the DWI. It also can provide important basis for accident prevent, traffic law enforcement and traffic management.展开更多
A new car-following model is proposed based on the full velocity difference model（FVDM） taking the influence of the friction coefficient and the road curvature into account. Through the control theory, the stability...A new car-following model is proposed based on the full velocity difference model（FVDM） taking the influence of the friction coefficient and the road curvature into account. Through the control theory, the stability conditions are obtained,and by using nonlinear analysis, the time-dependent Ginzburg-Landau（TDGL） equation and the modified Korteweg-de Vries（mKdV） equation are derived. Furthermore, the connection between TDGL and mKdV equations is also given. The numerical simulation is consistent with the theoretical analysis. The evolution of a traffic jam and the corresponding energy consumption are explored. The numerical results show that the control scheme is effective not only to suppress the traffic jam but also to reduce the energy consumption.展开更多
基金supported by the National Key Research and Development Program of China(2022YFB2602103 and 2023YFA1008900)。
文摘Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained prominence across various engineering sectors,including the manufacturing and construction industries.Specifically,road engineering has demonstrated a growing interest in DT and has achieved promising results in DT-related applications over the past several years.This paper systematically introduces the development of DT and examines its current state in road engineering by reviewing research articles on DT-enabling technologies,such as model creation,condition sensing,data processing,and interaction,as well as its applications throughout the lifecycle of road infrastructure.The findings indicate that research has primarily focused on data perception and virtual model creation,while realtime data processing and interaction between physical and virtual models remain underexplored.DT in road engineering has been predominantly applied during the operation and maintenance phases,with limited attention given to the construction and demolition phases.Future efforts should focus on establishing uniform standards,developing innovative perception and data interaction techniques,optimizing development costs,and expanding the scope of lifecycle applications to facilitate the digital transformation of road engineering.This review provides a comprehensive overview of state-of-the-art advancements in this field and paves the way for leveraging DT in road infrastructure lifecycle management.
文摘The authors apologize for the erroneous transcription of the average chemical composition data of Apollo lunar soil samples in Table 4.The difference in chemical composition between lunar regolith simulants and actual lunar samples is an important indicator for evaluating their similarity.For comparison,Table 4 lists the chemical compositions of Apollo 12,Apollo 14,Apollo 15,Apollo 16,and other classic lunar regolith simulants.However,the Apollo lunar soil data in the original Table 4 contained errors,which have been corrected in this corrigendum.
基金supported by the National Natural Science Foundation of China(U23A20272,U22A2069,62272146)Natural Science Foundation of Henan(252300421237).
文摘The increase in population and vehicles exacerbates traffic congestion and management difficulties.Therefore,achieving accurate and efficient traffic flow prediction is crucial for urban transportation.For that reason,we propose a graph federated learning-based digital twin traffic flow prediction method(GFLDT)by integrating the benefits of collaborative intelligence and computation of intelligent IoT.Specifically,we construct a digital twin network for predicting traffic flow,which is divided into client twin and global twin.Based on this,we adopt the concept of graph federated learning to learn the temporal dependence of traffic flow using local data from client twins,and the spatial dependence of traffic flow using global information from global twins.In addition,we validate on a real traffic dataset,and the results show that through collaborative training of the client twins and the global twins,GFLDT achieves accurate traffic flow prediction while protecting data security.
基金Supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions under Grant No.014000319/2018-00391.
文摘Pre-chamber ignition technology can address the issue of uneven in-cylinder mixture combustion in large-bore marine engines.The impact of various pre-chamber structures on the formation of the mixture and jet flames within the pre-chamber is explored.This study performed numerical simulations on a large-bore marine ammonia/hydrogen pre-chamber engine prototype,considering pre-chamber volume,throat diameter,the distance between the hydrogen injector and the spark plug,and the hydrogen injector angle.Compared with the original engine,when the pre-chamber volume is 73.4 ml,the throat diameter is 14 mm,the distance ratio is 0.92,and the hydrogen injector angle is 80°.Moreover,the peak pressure in the pre-chamber increased by 23.1%,and that in the main chamber increased by 46.3%.The results indicate that the performance of the original engine is greatly enhanced by altering its fuel and pre-chamber structure.
基金supported by the Science and Technology Research Project of Henan Province(242102241055)the Industry-University-Research Collaborative Innovation Base on Automobile Lightweight of“Science and Technology Innovation in Central Plains”(2024KCZY315)the Opening Fund of State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ2024A03-ZZU).
文摘The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.
基金supported by the Transportation Science and Technology Program of Henan Province(grant number:2023-4-2)the Key Research and Development Program of Ningxia Science and Technology Department(grant number:2022BEG02008)+2 种基金China Communications Construction Group Co.,Ltd.Science and Technology R&D Project(grant number:2021KJW02)the Research and Development Program of Henan Transportation Investment Group Co.,Ltd.(grant number:HNJT2025-1-9)the Postdoctoral Fellowship Program of CPSF(grand number:GZC20251139).
文摘The addition of high-content crumb rubber(HCCR)in asphalt can effectively address waste tire pollution and provide sustainable environmental and economic advantages.However,the practical application of conventional rubberized binders is significantly limited by high viscosity and poor storage stability.To address these issues,researchers have pretreated crumb rubber(CR)with oil,but high-temperature performance remains insufficient.Therefore,this study aimed to optimize the viscosity,storage stability,and rheological properties of high-content crumb rubber-modified asphalt(HCCRMA)by varying the pretreatment levels of CR and incorporating various additives,including styrene-butadiene-styrene(SBS),deoiled asphalt(DA),or recycled low-density polyethylene(RLDPE).In addition,CR was pretreated with waste cooking oil(WCO)at various ratios,pre-swelling temperatures,and times.The results show that DA exhibits excellent storage stability and lower viscosity compared with other modifiers in HCCRMA,and the 4%RLDPE with pretreated HCCR has the greatest high-temperature rutting resistance.The inclusion of RLDPE increases the stiffness and elasticity of the modified asphalt,which results in greater high-temperature performance.Additionally,the fluorescence microscopy(FM)test confirms that SBS exhibits better dispersion than other modifiers and forms a more homogeneous phase separation in the HCCRMA.All in all,this research achieved an optimal balance of storage stability and rheological properties in asphalt modified with pretreated HCCR and 6%SBS,which provides a valuable reference for performance improvement of HCCR-modified binders.
基金supported by the National Natural Science Foundation of China(Grant No.52402430,52572380)the Natural Science Foundation of Shanghai(Grant No.23ZR1466300).
文摘Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.
基金the support of the Major Science and Technology Project of Yunnan Province,China(Grant No.202502AD080007)the National Natural Science Foundation of China(Grant No.52378288)。
文摘Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.
基金support from the Hong Kong Environment and Conservation Fund through ECF Project(84/2017)Science and Technology Project of Henan Provincial Department of Transportation(2020J6).
文摘Waste plastics,such as waste polyethylene terephthalate(PET)beverage bottles and waste rubber tyres are major municipal solid wastes,which may lead to various environmental problems if they are not appropriately recycled.In this study,the feasibility of collectively recycling the two types of waste into performance-increasing modifiers for asphalt pavements was analyzed.This study aimed to investigate the recycling mechanisms of waste PET-derived additives under the treatment of two amines,triethylenetetramine(TETA)and ethanolamine(EA),and characterize the performances of these additives in modifying rubberized bitumen,a bitumen modified by waste tyre rubber.To this end,infrared spectroscopy and thermal analyses were carried out on the two PET-derived additives(PET–TETA and PET–EA).In addition,infrared spectroscopy,viscosity,dynamic shear rheology,and multiple stress creep recovery tests were performed on the rubberized bitumen samples modified by the two PET-derived additives.We concluded that waste PET can be chemically upcycled into functional additives,which can increase the overall performance of the rubberized bitumen.The recycling method developed in this study not only helps alleviate the landfilling problems of both waste PET plastic and scrap tyres,but also turns these wastes into value-added new materials for building durable pavements.
基金The National Natural Science Foundation of China (No.71771019, 71871130, 71971125)the Science and Technology Special Project of Shandong Provincial Public Security Department (No. 37000000015900920210010001,37000000015900920210012001)。
文摘To improve the level of active traffic management,a short-term traffic flow prediction model is proposed by combining phase space reconstruction(PSR)and extreme gradient boosting(XGBoost)algorithms.Firstly,the traditional data preprocessing method is improved.The new method uses hierarchical clustering to determine the traffic flow state and fills in missing and abnormal data according to different traffic flow states.Secondly,one-dimensional data are mapped into a multidimensional data matrix through PSR,and the time series complex network is used to verify the data reconstruction effect.Finally,the multidimensional data matrix is inputted into the XGBoost model to predict future traffic flow parameters.The experimental results show that the mean square error,average absolute error,and average absolute percentage error of the prediction results of the PSR-XGBoost model are 5.399%,1.632%,and 6.278%,respectively,and the required running time is 17.35 s.Compared with mathematical-statistical models and other machine learning models,the PSR-XGBoost model has clear advantages in multiple predictive indicators,proving its feasibility and superiority in short-term traffic flow prediction.
基金Project supported by the Program of Humanities and Social Science of the Education Ministry of China(Grant No.20YJA630008)the Natural Science Foundation of Zhejiang Province,China(Grant No.LY20G010004)the K C Wong Magna Fund in Ningbo University,China。
文摘Accurate prediction of road traffic flow is a significant part in the intelligent transportation systems.Accurate prediction can alleviate traffic congestion,and reduce environmental pollution.For the management department,it can make effective use of road resources.For individuals,it can help people plan their own travel paths,avoid congestion,and save time.Owing to complex factors on the road,such as damage to the detector and disturbances from environment,the measured traffic volume can contain noise.Reducing the influence of noise on traffic flow prediction is a piece of very important work.Therefore,in this paper we propose a combination algorithm of denoising and BILSTM to effectively improve the performance of traffic flow prediction.At the same time,three denoising algorithms are compared to find the best combination mode.In this paper,the wavelet(WL) denoising scheme,the empirical mode decomposition(EMD) denoising scheme,and the ensemble empirical mode decomposition(EEMD) denoising scheme are all introduced to suppress outliers in traffic flow data.In addition,we combine the denoising schemes with bidirectional long short-term memory(BILSTM)network to predict the traffic flow.The data in this paper are cited from performance measurement system(PeMS).We choose three kinds of road data(mainline,off ramp,on ramp) to predict traffic flow.The results for mainline show that data denoising can improve prediction accuracy.Moreover,prediction accuracy of BILSTM+EEMD scheme is the highest in the three methods(BILSTM+WL,BILSTM+EMD,BILSTM+EEMD).The results for off ramp and on ramp show the same performance as the results for mainline.It is indicated that this model is suitable for different road sections and long-term prediction.
基金supported by the National Basic Research Program of China(Grand No.2012CB723303)the Beijing Committee of Science and Technology,China(Grand No.Z1211000003120100)
文摘The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.
基金Project(51108343) supported by the National Natural Science Foundation of ChinaProject(06121) supported by University of Transportation Center for Alabama, USA
文摘In order to investigate enhancements to cell transmission model (CTM) as a tool for traffic signal timing in oversaturated conditions, randomly distributed saturation flow rates and arrival rates were used instead of constant values to simulate traffic flow movement, estimate the average delay of the network and search for an optimal traffic signal timing plan. A case study was given to demonstrate that the proposed methodology can capture unique phenomena in oversaturated conditions such as forward wave, spillback and lane entrance blockage. The results show that CTM underestimates travel time by 25% when compared to Simtraffic, while the enhanced CTM underestimates by only 3%. A second case study shows that a dynamic signal timing plan is superior to a fixed signal timing plan in the term of average delay.
基金Project(71801115)supported by the National Natural Science Foundation of ChinaProject(2021M691311)supported by the Postdoctoral Science Foundation of ChinaProject(111041000000180001210102)supported by the Central Public Interest Scientific Institution Basal Research Fund,China。
文摘To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS is proposed,whereby the network reliability and experiential learning theory are introduced into the decision process for the travelers’route choice.The intelligent highway serves all the travelers who drive on it,whereas ATIS serves vehicles equipped with information systems.Travelers who drive on intelligent highways or vehicles equipped with ATIS determine their trip routes based on real-time traffic information,whereas other travelers use both the road network conditions from the previous day and historical travel experience to choose a route.Both roadway capacity degradation and travel demand fluctuations are considered to demonstrate the uncertainties in the network.The theory of traffic network flow is developed to build a DTD model considering information from intelligent highway and ATIS.The fixed point theorem is adopted to investigate the equivalence,existence and stability of the proposed DTD model.Numerical examples illustrate that using a high confidence level and weight parameter for the traffic flow reduces the stability of the proposed model.The traffic flow reaches a steady state as travelers’routes shift with repetitive learning of road conditions.The proposed model can be used to formulate scientific traffic organization and diversion schemes during road expansion or reconstruction.
文摘Short-term traffic flow is one of the core technologies to realize traffic flow guidance. In this article, in view of the characteristics that the traffic flow changes repeatedly, a short-term traffic flow forecasting method based on a three-layer K-nearest neighbor non-parametric regression algorithm is proposed. Specifically, two screening layers based on shape similarity were introduced in K-nearest neighbor non-parametric regression method, and the forecasting results were output using the weighted averaging on the reciprocal values of the shape similarity distances and the most-similar-point distance adjustment method. According to the experimental results, the proposed algorithm has improved the predictive ability of the traditional K-nearest neighbor non-parametric regression method, and greatly enhanced the accuracy and real-time performance of short-term traffic flow forecasting.
文摘In civil engineering, the nonlinear dynamic instability of structures occurs at a bifurcation point or a limit point. The instability at a bifurcation point can be analyzed with the theory of nonlinear dynamics, and that at a limit point can be discussed with the theory of elastoplasticity. In this paper, the nonlinear dynamic instability of structures was treated with mathematical and mechanical theories. The research methods for the problems of structural nonlinear dynamic stability were discussed first, and then the criterion of stability or instability of structures, the method to obtain the bifurcation point and the limit point, and the formulae of the directions of the branch solutions at a bifurcation point were elucidated. These methods can be applied to the problems of nonlinear dynamic instability of structures such as reticulated shells, space grid structures, and so on. Key words nonlinear dynamic instability - engineering structures - non-stationary nonlinear system - bifurcation point - instability at a bifurcation point - limit point MSC 2000 74K25 Project supported by the Science Foundation of Shanghai Municipal Commission of Education (Grant No. 02AK04), the Science Foundation of Shanghai Municipal Commission of Science and Technology (Grant No. 02ZA14034)
基金Supported by the National Natural Science Foundation of China under Grant Nos.71871130,71471104,71771019,71571109the University Science and Technology Program Funding Projects of Shandong Province under Grant No.J17KA211the Project of Public Security Department of Shandong Province under Grant No.GATHT2015-236
文摘The expressway traffc incidents have the characteristics of high harmful, strong destructive and refractory.Incident detection can guarantee smooth operation of the expressway, reduce traffc congestion and avoid secondary accident by informing the accident, detection and treatment timely. In this paper, an incident detection method is proposed using the toll station data that takes into account the traffc ratio at the entrances and crossway in the network. The expressway traffc simulation model is improved and a simulation algorithm is established to describe the movement of the vehicles. A numerical example is experimented on the expressway network of Shandong province. The proposed method can effectively detect the expressway incidents, and dynamically estimate the traffc network states so as to provide advice for the highway management department.
文摘An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation duration, variations of fixation points, and the distribution of glance zone. It was found that driving experience had a significant effect on driver eye movement behavior. The percentage of fixation duration to total glance time for inexperienced drivers was 61.5%, while the percentage for experienced drivers was 50.2%. Moreover, the majority of drivers paid attention to the left region of the field of view more frequently than the central and the right regions. This study indicates that it takes inexperienced drivers more time to recognize traffic signs. The findings from this study will assist traffic engineers in designing and installing the traffic signs in an optimal way.
文摘Most of the current studies on drunk driving accidents focus on law making and public education. However, especially in China, there is less statistical analysis on the severity of drunk driving accidents between driving under the influence of alcohol (DUI) and driving while intoxicated (DWI). 3368 drunk driving related crashes were collected from the blood-alcohol test report in a city of China at 2012 and 2013. After data pre-processing, Chi-square tests were used to analyze the association between different variables and the type of drunk driving. The logistic regression model is conducted to estimate the effect of the variables under DUI and DWI. The results show that Hour of the day, Driver’s age, Driver’s casualties and Accident area have significant correlation with drunk driving. There was a slightly decrease by 0.995 per year with age and a slightly increase by 1.014 with time in the possibility of DWI. DWI is more likely to cause death in traffic accidents (OR = 1.316) than DUI. Driver’s deaths (OR = 2.346) is more likely to happen than the injuries (OR = 1.910) under DWI cases. These findings show that more attention should be paid to strengthen controls on the DWI. It also can provide important basis for accident prevent, traffic law enforcement and traffic management.
基金Project supported by the National Natural Science Foundation of China(Grant No.11372166)the Scientific Research Fund of Zhejiang Province,China(Grant Nos.LY15A020007 and LY15E080013)+1 种基金the Natural Science Foundation of Ningbo,China(Grant Nos.2014A610028 and 2014A610022)the K.C.Wong Magna Fund in Ningbo University,China
文摘A new car-following model is proposed based on the full velocity difference model（FVDM） taking the influence of the friction coefficient and the road curvature into account. Through the control theory, the stability conditions are obtained,and by using nonlinear analysis, the time-dependent Ginzburg-Landau（TDGL） equation and the modified Korteweg-de Vries（mKdV） equation are derived. Furthermore, the connection between TDGL and mKdV equations is also given. The numerical simulation is consistent with the theoretical analysis. The evolution of a traffic jam and the corresponding energy consumption are explored. The numerical results show that the control scheme is effective not only to suppress the traffic jam but also to reduce the energy consumption.
