Table of Content

25 May 2022, Volume 50 Issue 5

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2022, 50(5):  0-0. 

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Traffic & Transportation Engineering

Correlation Analysis and Prediction of Pedestrian Casualty Risk in Car-Pedestrian Collision Accident



LAN Fengchong, ZHANG Yue, CHEN Jiqing, et al

2022, 50(5):  1-10.  doi:10.12141/j.issn.1000-565X.210058

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A model for predicting the risks of pedestrian injuries after accidents based on clustering method and back-propagation neural network was proposed to study the factors that affect pedestrian injuries in car-pedestrian collision accidents.Firstly，the data of 372 car-pedestrian collision accidents between 2018 and 2019 in the National Vehicle Accident In-depth Investigation System（NAIS）database was collected as the research object.And it was statistically analyzed to obtain 9 accident characteristic parameters in three dimensions of vehicle，pedestrian and collision status.Then，combined with the characteristics of each accident，the K-means clustering method was selected for continuous eigenvalues，and the hierarchical clustering method was selected for discrete eigenvalues to obtain the correlation between pedestrian injury and death risks and various characteristic parameters.Finally，a BP neural network prediction model based on accident characteristics was established to predict pedestrian injuries and deaths.The test results show that the success rate of the pedestrian casualty risk prediction model is 86%.

Research on Spatiotemporal Characteristic and Risk of Lane-Changing Behaviors of Large Vehicles in Expressway Merging Area



WEN Huiying, LI Qiuling, ZHAO Sheng

2022, 50(5):  11-21.  doi:10.12141/j.issn.1000-565X.210489

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In order to study the characteristics and risks of lane-changing behaviors of large vehicles，trajectory data of large vehicles in the expressway merging area was collected based on drone shooting and image recognition technology，and lane-changing characteristics and spatiotemporal risks of large vehicles were analyzed.The results indicate that the average value of the lane change duration of large vehicles is 5.28s，the average value of the first half time is 2.60s，the average value of the last half time is 2.68s，and the average value of longitudinal lane change travel distance is 78.12 meters.They all obey Weibull Distribution，and are significantly related to lane-changing speed.The lane change duration and the first half time are significantly related to the distance between the large vehicle and the vehicle in front in the original lane and the distance between the large vehicle and the vehicle in front in the target lane.The first half time is also significantly related to the distance along the lane line.75.40% of large vehicles start to change lanes within 100 meters before the bottleneck section of the merging area，and the occurrence of lane-changing behavior spreads from the outer lane to the inner lane in turn.The ave-rage distance and relative speed between the large vehicle and the vehicle in front in the original lane are the smallest，which are 22.91 meters and -0.90m/s，respectively.If the lane change gap is small，the driver will be more inclined to change lane when the lane change gap shrinks slowly or continuously expands.The large vehicle has the highest risk of collision with the vehicle in front in the original lane，and approximately 15.32% of large vehicles change lanes when they are in an unsafe state with the vehicles in front.

Metro Transfer Passenger Flow Prediction Based on STL-GRU



ZHAO Jiandong, ZHU Dan, LIU Jiaxin

2022, 50(5):  22-31.  doi:10.12141/j.issn.1000-565X.210559

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A metro transfer passenger flow prediction model was proposed based on the seasonal decomposition of time series by loess（STL）and Gated Recurrent Unit（GRU），in order to enrich the research on metro internal transfer passenger flow prediction and to better formulate the metro operation plan.The prediction process was divided into three stages by the model.In the first stage，the raw automatic fare collection（AFC）data are preprocessed，where the travel path of passengers is identified using the graph-based depth-first search algorithm and the transfer passenger flow time series are constructed.In the second stage，the transfer passenger flow time series are decomposed into the trend component，seasonal component and remainder component by the STL；while the outliers of remainder component are eliminated and filled using the 3σ principle.In the third stage，the GRU model is built and the related training and prediction are processed through the deep learning library Keras.The model performance was validated with the passenger flow data of Xizhimen Station of Beijing metro.The result shows that，compared to the following 3 models which are long short-term memory neural network（LSTM），GRU and STL-LSTM model，the STL-GRU prediction model can improve the prediction accuracy of transfer passenger flow on weekdays（excluding Friday），Friday and weekends，and the mean absolute percentage errors of the prediction results can be reduced by at least 2.3%，1.36%，and 6.42%，respectively.

Connection Scheme Optimization of Last Trains of Urban Mass Transit Network Based on Considering the Transfer Passengers



ZHENG Yajing, LI Yaohui, JIN Wenzhou

2022, 50(5):  32-39.  doi:10.12141/j.issn.1000-565X.210567

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Focusing on the transfer connection problem of last trains of urban mass transit network，this paper analyzed the complexity of the connection relationship of last trains of urban mass transit network and established an optimization model for the connection scheme of last trains of urban mass transit aiming at maximizing the number of passengers.The essence of the model is to solve the maximum directed acyclic subgraph of the weighted directed graph.And then，an appropriate coding method was designed，the ox like method was used for cross operation，and a genetic algorithm suitable for the optimization model of last trains connection scheme of urban mass transit was proposed.Finally，the proposed genetic algorithm was verified with an example.The result shows that the algorithm can quickly obtain a more optimized last trains connection scheme，which is easy to be realized by computer.This method can be used as an auxiliary means for the preparation of last trains schedule，and provides a certain decision-making basis for the preparation of last trains schedule of each line in the urban mass transit network.

Adaptive Release Strategy of VMS Information for Pedestrian Walking in the Road Network of Competition Area in Low Temperature Environment



HUANG Wenbo, CHEN Yanyan

2022, 50(5):  40-48.  doi:10.12141/j.issn.1000-565X.210397

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This study proposed an adaptive information release strategy of VMS（variable message signs）in road network based on the real-time response of the passenger flow，in order to improve the travel efficiency and reduce the safety risk of pedestrians in the competition area under low temperature environment.First of all，from the perspective of information intervention，the dynamic feedback mechanism between the VMS information release and the crowded state of the passenger flow was established，and the dynamic optimization model of the VMS information release layout was formulated.The in response to the strategy，a scene simulation method based on multi-agents was proposed.A cold competition area was taken as an example to simulate the ingress and egress scenes with and without the VMS information release strategy.The results show that the proportion of short-term passenger flow increases，compared with that without the VMS information release strategy.For the ingress scene，the ave-rage walking time of pedestrians can be reduced by about 2.6%，and the maximum road congestion can be reduced by about 20.45%；while for the egress scene，the average walking time of pedestrians can be reduced by about 7.0%，and the maximum road congestion can be reduced by about 10.51%.The research can provide theoretical foundation and data support for the competition area managers to control passenger flow and improve the experience of spectating experience.

Method of Traffic Flow Fusion Under the Condition of Connected Vehicles Mixed with Non-Connected Vehicles



LI Xiao, WANG Tao, ZHANG Yi, et al

2022, 50(5):  49-55.  doi:10.12141/j.issn.1000-565X.210490

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In the future，the combination of intelligent connected vehicles and traditional vehicles will bring more multi-source traffic data.In order to improve the reliability of data，a multi-source traffic data fusion method based on particle swarm optimization radial basis function neural network was proposed by combining traditional traffic data obtaining method.Firstly，the data from different sources were selected to construct multi-source data set and a group of contrast data.The multi-source data set was clustered by the Elbow Method and K-means algorithm，and then the corresponding radial basis function neural network was constructed with the reference of the cluster center coordinates.Finally，the particle swarm algorithm was introduced in the neural network training process，the difference between the fusion result and the control data was used as the objective function of the particle swarm algorithm iteration to help solve the parameters in neural network.The neural network was realized by MATLAB，and a group of multi-source traffic flow was selected for test.The same data was fused by Kalman filter algorithm at the same time，and the fusion results of the two methods were compared.The results show that，compared with the traditional Kalman filter，the data error is increased by more than 60% when the particle swarm optimization radial basis function neural network is employed to fuse multi-source traffic flow under mixed traffic conditions.

Influences of Train to Tunnel Area Ratio on Aerodynamic Pressure Characteristics of High-Speed Railway Tunnel Wall



DU Jianming, FANG Qian, LI Jianye

2022, 50(5):  56-64.  doi:10.12141/j.issn.1000-565X.210472

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To further study the characteristics of aerodynamic pressure acting on the tunnel wall，the entire process of a high-speed train passing through the double-track tunnel was simulated based on the RNG k-ε two-equation turbulence model and the sliding mesh technique.Then，the accuracy of numerical method was verified by comparing the results between numerical simulation and field measurement.Finally，the influences of the train-to-tunnel area ratio on the characteristics of aerodynamic pressure acting on the tunnel wall were analyzed in detail.The results show that：the maximum gradient and positive peak values of the initial pressure wave both increase exponentially with the increase of train-to-tunnel area ratio，and the correlation coefficient R2 is greater than 0.998；at two stages of before or after the train tail leaving the tunnel exit，the relationship between the typical peak values of aerodynamic pressure（positive peak，negative peak，and peak-to-peak）acting on the tunnel wall and the train-to-tunnel area ratio is the exponential function with the ε as the base，and the correlation coefficient R2 is greater than 0.9995.After the train tail leaving the tunnel exit，the difference between the positive and negative peak values of the aerodynamic pressure acting on the tunnel wall at different train-to-tunnel area ratio decreases with time.Taking the measurement point there 500m away from the tunnel entrance as an example，when the train-to-tunnel area ratio increases from 0.0801 to 0.1122（1.4 times），the increments of the maximum gradient and positive peak values of the initial pressure wave are 2.92 and 0.30kPa，respectively；the increments of the positive and negative peak values of the aerodynamic pressure before train tail leaving the tunnel exit are 0.35 and 0.60kPa，respectively；the increments of the positive and negative peak values of the aerodynamic pressure after train tail leaving the tunnel exit are 0.53 and 0.46kPa，respectively.

Research on the Compatibility of Bio-Asphalt Based on Molecular Dynamics



XU Ning, WANG Hainian, CHEN Yu, et al

2022, 50(5):  65-72.  doi:10.12141/j.issn.1000-565X.210595

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Molecular models of base asphalt，bio-oil，and bio-asphalt were constructed based on molecular dynamics in order to study the compatibility of wood chip based bio-oil and asphalt，and the compatibility of bio-oil with asphalt and its components was quantitatively analyzed by molecular polarity，solubility parameters，and binding energy.The simulation results were validated with the help of the segregation test.The results show that the solubility parameters of bio-oil are closer to those of asphaltene fraction，both of them having stronger polarities and more susceptible to adsorption.As the temperature increases，the difference in solubility parameters between bio-oil and asphalt gradually becomes larger and the binding energy gradually decreases.The difference of parameters in solubility and the binding energy significantly deteriorates when the system temperature exceeds 433K，and the storage stability of bio-asphalt decreases obviously when the temperature reaches 453K.To ensure the compatibility between bio-oil and asphalt and avoid serious segregation during high-temperature storage，it is recommended that the storage temperature of bio-asphalt should not exceed 433K.

Architecture & Civil Engineering

Mechanical Properties of Hydrochloric Acid Corroded Concrete Under Cyclic Loading



LUO Xiaoyong, CHENG Qian, CHENG Junfeng, et al

2022, 50(5):  73-85.  doi:10.12141/j.issn.1000-565X.210604

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Most of the existing studies on acid corrosion of concrete focus on the mechanical behavior of concrete structures without loading or under monotonic loading.In order to study the variation law of mechanical properties of in-service concrete members under cyclic loading，six groups of concrete prism specimens were prepared and immersed in hydrochloric acid of 1%（mass fraction）for accelerated corrosion.The monotonic and cyclic axial compression loading tests were carried out to examine the influence of corrosion on the mechanical properties of concrete under cyclic axial compression loading.Then，the concept of effective load-bearing cross-area ratio was proposed，and the descending correction coefficient of effective load-bearing cross-area ratio was introduced to establish the practical constitutive model of hydrochloric acid corrosion concrete under cyclic loading.And the model was verified.The results show that hydrochloric acid corrosion has a significant effect on the failure characteristics of concrete.The surface of corroded concrete is easy to peel off under loading effects，and the area of spalling enlarges gradually with the increase of loading.Meanwhile，with the increase of corrosion period，the compressive strength reduces of concrete obviously，and the bearing capacity decreases rapidly.The envelope of stress-strain curve of concrete with different corrosion ages under cyclic loading is basically consistent with that of the monotonic loading.However，the degradation rate of descending section for the stress-strain curve of concrete under cyclic loading is larger than that under monotonic loading due to the accumulation of internal damage of corroded concrete，and the failure is relatively more prominent.The peak strain of concrete under cyclic loading is slightly less than that of the monotonic loading.As the continuing increases of the corrosion period，the peak strain and ultimate strain of concrete under cyclic loading increase observably，while the peak stress and elastic modulus decrease significantly.Compared with uncorroded concrete，the test peak stress and elastic modulus of corroded concrete decreases by 53.25% and 74.1%，respectively，and meanwhile the peak strain and ultimate strain increased by 55.7% and 77.87%，respectively.The stress-strain curves calculated by using the model established in this paper match well with the test results，indicating the desirable fitting effect of the model.

Traffic & Transportation Engineering

Study on Dynamic Collapse Performance of Prefabricated Steel-Concrete Composite Frame Structures



YANG Tao, HUANG Junren, ZHANG Yun, et al

2022, 50(5):  86-95.  doi:10.12141/j.issn.1000-565X.210756

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Prefabricated steel-concrete composite frames are increasingly applied in engineering day by day.However，research on their anti-collapse performance is less reported.To investigate their dynamic collapse perfor-mance，two reduced-scale prefabricated composite frame substructures were designed and tested by dynamically removing a column in this paper.Collapse behaviors of such frame structures under different load conditions were studied，and the effect of the division of precast concrete（PC）slabs on the dynamic collapse behaviors was also assessed.Then，a calculation model of the equivalent dynamic increase factor（DIF）of collapse load was built based on the experimental results for prefabricated composite frames.The results show that under the effects of one time collapse load（30 kN）and twice collapse load（60 kN），the primary structural damage for prefabricated steel-concrete frame substructures is the cracking of concrete slab at the beam ends close to the side column.After the middle column failed，the residual structures still have the superior load-bearing capacity and overall stiffness.The structures will not collapse under the two load conditions.The prefabricated composite frames are subjected to a greater impact effect under the same collapse load compared to the composite frames using cast-in-situ concrete.Division of the PC slabs slightly affect the dynamic characteristics of the composite frame substructures.However，it will lead to the increase of the strain dynamic increase factors of the steel girders and the longitudinal slab reinforcement.The increase factors of vertical displacement at the failed columns vary between 1.38 and 1.65 for the two substructures，and the dynamic increase factors of strain are even greater than 2.0 in some cases.The calculation model of the equivalent DIFs of collapse load for prefabricated composite frames developed based on the experimental results can provide a reference for the revision of the collapse load when the static collapse analysis is conducted.The calculated DIF of collapse load based on this model is conservative.

Architecture & Civil Engineering

Axial Compression Test of Seawater Sea-Sand Concrete Circular Column Inner-Confined by BFRP Spiral Strip



ZHENG Hongyu, YU Yuqi, XU Dixin, et al

2022, 50(5):  96-108.  doi:10.12141/j.issn.1000-565X.210498

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In order to study the axial compression behavior of a new type of sea water sea-sand concrete circular column reinforced by BFRP longitudinal bars and confined by continuous BFRP spiral strip，also with concrete cover，8 short columns were test under axial compressive load.The influence of reinforcement ratio of BFRP longitu-dinal bars and the width and spacing of BFRP spiral strip on the axial compression performance of the columns was studied.According to the study results，the failure process and mechanism of such new type of column are that the concrete cover cracks and fell off first at middle of its height，then the spiral strips were fractured，finally the core concrete was crushes and the BFRP longitudinal bars are buckling；the damage ranges of concrete covers of the specimens confined by strips are smaller than that of the specimen without strip confining；the BFRP spiral strips can provide some constraint effect on the core concrete and BFRP longitudinal bars and improve the utilization rate of the compressive strength of BFRP bars；the bearing capacity of the new type of column increases with the increase of reinforcement ratio of BFRP longitudinal bars；under the restraint of the strips，the bearing capacity of the specimens is increased by 0.9%~10.4%，and the ultimate displacements is increased by 16.39%~130.82%；reducing the spacing or increasing the width of strips can improve the bearing capacity of the column；the displacement ductility coefficients of the specimens are generally not high.The calculated values from the expression for predicting the axial compression bearing capacity of such column derived in this paper are in good agreement with the experimental values.

Selection of Reconstruction Parameters for Sound Insulation Measurement Based on Near-Field Acoustic Holography



XIONG Wei, WANG Hongwei, ZHANG Guangyao, et al

2022, 50(5):  109-117.  doi:10.12141/j.issn.1000-565X.210435

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Near-field acoustic holography has wide application prospects in the field measurement related to sound insulation of prefabricated buildings and components.In order to reduce the complexity of holographic measurement and improve the accuracy of sound field reconstruction，this study firstly used point sound source as an example to explore the variation law of sound insulation measurement accuracy with parameters by means of numerical simulation and experimental verification.Then it discussed the optimization range of parameters.Finally，this study veri-fied the effectiveness of the reconstruction parameters selected in this paper about sound insulation measurement.The results show that the simulation values are basically consistent with the experimental values.That is，the accuracy decreases with the increase of reconstruction distance and sampling spacing，while increases with the increase of holographic aperture.In addition，to best improve accuracy，the values of reconstruction distance and sampling spacing should not exceed the half-wavelength corresponding to the highest frequency，and the aperture of the holographic plane should be 1.5 times of the component size.By optimizing the reconstruction parameters，it can not only reduce the complexity of sound insulation measurement，but also improve the measurement accuracy，as well as obtain better sound insulation measurement accuracy，improving the engineering practicability of the near-field acoustic holographic sound insulation measurement technology.

Energy Harvesting Characteristics of Preloaded Piezoelectric Beams Based on Multi-Scale Approach



HUANG Huaiwei, HE Wanli, CAO Yajun

2022, 50(5):  118-126.  doi:10.12141/j.issn.1000-565X.210218

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Low frequency，broad bandwidth and adjustable frequency have always been adopted as crucial indexes to measure the performance of piezoelectric energy harvesters（PEHs）.The axial preload is deemed as one of the effective ways to improve these indexes.To explore the effect of preload on the energy harvesting characteristics，the electromechanical coupling governing equations were derived based on the Euler-Bernoulli beam theory and Gauss Theorem.The asymptotically analytic solutions of the displacement，the voltage and the average output po-wer were obtained with Galerkin discretization and the multi-scale approach.Then，through theoretical analysis，this paper obtained the expressions of the short-circuit and open-circuit resonance frequencies，the open-circuit voltage amplitude，the optimal output power and the optimal load resistance.For the cantilever beam model，the validity of the theory was verified by numerical simulation.Finally，the influence of preload on open-circuit voltage and optimal output power was analyzed.The results reveal that the axial preload can improve the energy harvesting efficiency of piezoelectric cantilever beam.Compared with the case without preload，the resonant frequency decreases by 31.6%，the amplitude of open-circuit voltage increases by 120.8%，and the optimal output power increases by 40.0%，when the preload is 20N.

Concrete Crack Image Recognition System Based on Improved Seed Filling Algorithm



SUN Xiaohe, SHI Chenghua, LIU Linghui, et al

2022, 50(5):  127-136,146.  doi:10.12141/j.issn.1000-565X.210602

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In order to solve the problems of poor anti-interference ability and low recognition accuracy of traditional crack identification algorithms，an image identification system for concrete surface existing cracks was established by improving the existing seed filling algorithm to achieve accurate extraction of crack information.In the pre-processing，the illumination uneven coefficient screening algorithm was proposed to quickly screen the image，which improves the efficiency of uniform light processing.In the crack identification，the existing seed filling algorithm was improved，so that it can automatically determine the growth point of the crack.And the image segmentation of the crack was realized by combining the eight-direction search method with the boundary judgment of the relative threshold method.Then a series of complex background interference were eliminated with the connected domain filter.In the feature extraction stage，by introducing morphological processing，burr removal and node Euclidean distance，the quantitative information of the number of cracks，length and width was accurately obtained.Compared with traditional concrete crack image recognition algorithms，this algorithm achieves a greater degree of unification of efficiency and accuracy，and the extraction error of the crack length and width values is controlled within 10%.

Mechanical Property of Reworked Part of Locally Corroded Steel Plate Repaired with Laser Cladding Technology



KANG Lan, WU Bin, CHEN Zhibang

2022, 50(5):  137-146.  doi:10.12141/j.issn.1000-565X.210317

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In order to study the mechanical property of reworked coupons of locally corroded steel plate repaired with laser cladding technology，this paper studied the effect law of forms of corrosion，treatment of corrosion interface，corrosion depth，and scanning path of laser cladding on the mechanical property of reworked coupons through uniaxial tensile test.And it obtained the force-displacement curve and mechanical property reduction factors of the locally corroded steel plate and its reworked coupons repaired by laser cladding.The results show that the modulus of elasticity，yield strength and ultimate strength of locally corroded steel plate coupons repaired by laser cladding technology are roughly equivalent to those of intact coupons，and its ultimate elongation can be recovered to more than 70% of that of intact coupons.Soft treatment of cladding layer side-substrate interface or increasing the overlap region can move fracture location from the cladding layer side-substrate interface to the substrate and further enhance the mechanical properties of the repaired coupons.Laser cladding technology can repair steel plates of different depth of corrosion and the mechanical performance of the repaired coupons is not sensitive to the scanning path.