Table of Content

25 March 2022, Volume 50 Issue 3

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Contents



2022, 50(3):  0. 

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Traffic & Transportation Engineering

Weather Recognition of Highway Surveillance Scenes Based on Light-Weight Deep Neural Network



FU Xinsha, ZENG Yanjie, MA Li, et al

2022, 50(3):  1-8.  doi:10.12141/j.issn.1000-565X.210352

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For the problem that deep convolutional neural network models are difficult to deploy at the edge due to their large number of parameters and high hardware device requirements, this paper researched on the weather re-cognition algorithm based on light-weight neural network with the application scenario of highway surveillance images. The light-weight neural network model MobileNet was first analyzed theoretically, and the difference between the deeply separable convolution operation and the standard convolution operation was analyzed in terms of the number of parameters and the number of computations. At the same time, a weather recognition dataset based on highway surveillance images was collected and labeled. Based on this, models including several light-weight neural networks were built and trained for comparison experiments, and the experimental results verified the advantages of MobileNet in terms of recognition accuracy, speed and number of model parameters. In addition, this paper explored the feature representation of MobileNet as well as the inter-class separability and intra-class clustering of features by the visualization algorithm t-SNE in terms of both class activation analysis and feature distribution, and the results further supported the above analysis.

Traffic Demand Prediction of Urban Public Bicycles with the Consideration of Land Use



ZHU Caihua, LI Yan, SUN Xiaoli, et al

2022, 50(3):  9-20,37.  doi:10.12141/j.issn.1000-565X.210083

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Aiming at the problem that newly built public bicycle stations cannot predict future use demand based on historical data, a modified geographically weighted regression model was proposed to explore the relationship between demand generation and accessibility at unit time nodes. The modified model took road network distance as the constraints to access the overlapping attraction area of docking stations based on Thiessen Polygon. Meantime, in order to reduce the prediction error caused by land location, the modified model added land mix degree and building strength as explanatory variables.The proposed model was utilized to analyze data from the docked bike-sharing system in Xian. The results indicate that the production rates of various land types are found to be maximum in the morning and evening peak hours with variable patterns in daily change. The production rate of bike-sharing system will gradually decrease as the distance between origin/destination and target docking stations increases, showing linear attenuation in the morning peak period, exponential attenuation in the evening peak period and cubic attenuation in the non-peak period. The findings can be utilized to determine the location and scale of new docking stations of bike-sharing system in Xian and predict relative usage demand rates.

Passenger Flow Forecast of Urban Rail Transit Based on Graph Convolution and Recurrent Neural Network



LIU Xiaolei, DUAN Zhengyu, YU Qing, et al

2022, 50(3):  21-27.  doi:10.12141/j.issn.1000-565X.210320

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Passenger flow forecast is of great significance to the organization and management of urban rail transit. This paper constructed a graph convolution and recurrent neural network (GCGRU model) by combining graph convolutional network with recurrent neural network. The graph convolutional network was used to learn the complex topological structure of an urban rail network and capture spatial correlation characteristics. Then one of the recurrent neural network variants called gated recurrent unit was used to learn the variation of multi-characteristics of traffic trends and to capture the temporal characteristics. An experiment was carried out with the passenger flow data obtained from the entire network with all subway cross-sections in Shanghai in a whole year, and the mean decrease impurity method provided by random forest was used for feature selection. The experimental results show that the GCGRU model can well capture the temporal and spatial correlation in the prediction of large-scale urban rail transit passenger flow, with a prediction accuracy of 89%. The prediction results can provide a basis for managers to manage and organize rail transit passenger flow as well as provide travelers with early warning information, ensuring the safe and efficient operation of the urban rail transit network.

Research on Self-Regulation Behavior of Elderly Drivers Based on Extended TPB Model



ZHAO Xiaohua, ZHU Hongzhen, BIAN Yang, et al

2022, 50(3):  28-37.  doi:10.12141/j.issn.1000-565X.210335

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With the increasing number of elderly drivers and their growing driving demand, China has abolished the age limit for applying for small car drivers license,and the travel safety of elderly drivers has become a hot research issue. Due to the biological and psychological decline related to driving behavior with aging, the elderly need to consider the impact of decreased physical function while maintaining mobility through self-regulation. Self-regulation is an effective compensation strategy for the elderly to prolong driving life and reduce driving risk. Based on the theory of planned behavior(TPB), this study introduced four extended variables, including physical condition, risk perception, driving skills and alternative traffic quality, to establish an extended TPB model and analyzed elderly drivers self-regulation behavior and its influencing factors. Cronbach's α coefficient and confirmatory factor were used to verify the reliability and validity of the self-regulation behavior questionnaires collected from 849 elderly drivers, and path analysis was used to explore the factors influencing elderly drivers self-regulation behavior. The results show that the relationship among basic TPB variables is consistent with the assumptions of the basic model. Physical condition, alternative traffic quality, driving ability and risk perception all indirectly affect the self-regulation behavior of the elderly. The results are helpful to understand elderly drivers self-regulation behavior and influencing factors, and provide the theoretical basis for further research on elderly drivers driving behavior training and safety education. 

Speed Characteristics and Prediction of Trucks on Long and Steep Downgrade Sections



ZHANG Chi, REN Shipeng, WANG Bo, et al

2022, 50(3):  38-49.  doi:10.12141/j.issn.1000-565X.210385

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The cross-section speed data of a continuous long downhill section of an expressway in Southwest China was collected, in order to study the operating characteristics of trucks on the long downhill section, improve the effectiveness of the operating speed prediction model, and ensure that vehicles can drive safely on the long downhill section. The temporal and spatial distribution characteristics of truck speed and the degree of dispersion of vehicle speed were analyzed, and the speed distribution characteristics of trucks on the long and large downhill road was tested through Q-Q probability diagram and single-sample K-S test, thus the speed distribution characteristics of trucks on the long downhill section were obtained. The error analysis of the operating speed model was carried out according to the distribution characteristics, so as to determine the cause of the error and correct the variable. Finally, a prediction and correction model of truck operating speed was established, and the effectiveness of the mo-del was compared and analyzed before and after the correction. The results show when the truck is traveling on a long downhill section, the speed gradually decreases first and then tends towards stability as the downhill distance increases; the degree of dispersion of vehicle speed increases with the increase of downhill distance and traffic vo-lume. Truck speed characteristics do not change significantly over time; truck speed in the long and large downhill sections conforms to the law of Logistic distribution, and the speed is highly concentrated and symmetrical to the peak speed value. The existing speed prediction model has deviations mainly because these models do not consider the influence of traffic density. The relative error of the truck running speed prediction correction model established based on this is reduced by 4% to 14%, which significantly improved the effectiveness. This can provide a theore-tical basis for the study of the long downhill running speed and improve the downhill safety of trucks.

Intelligent Detection of Asphalt Pavement Roughness with kNN Method



ZENG Jingxiang, ZHANG Jinxi, CAO Dandan, et al

2022, 50(3):  50-56.  doi:10.12141/j.issn.1000-565X.210326

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Roughness is one of the main technical indexes of pavement performance. Accurate and rapid IRI detection has great significance for pavement maintenance and management. In this paper, the self-developed smart phone App was used to collect driving status and other relevant datas. Driving datas such as vibration acceleration and speed were collected through driving experiments in real road, and the feasibility of detecting road roughness IRI by using these driving datas was studied. It proposed a method to take the composite vibration acceleration as the index of driving vibration acceleration and established the normalized kNN eigenvector space . The results show that the proposed method is simple and easy to apply and it improves the detection accuracy of pavement roughness IRI by using smart phones. The absolute evaluation accuracy of IRI detection reaches more than 78%, and the re-lative accuracy after considering adjacent evaluations reaches more than 96%, which meets the real-time detection and monitoring of pavement roughness IRI in the road network. It has a promising application prospects in improving the pertinence of IRI detection of pavement roughness and reducing the overall detection amount of pavement performance, thus can provide macroscopic guidance for the maintenance decision and management of road network pavement.

Application of Improved Radial Basis Interpolation Method in Ship Shape Optimization



FENG Baiwei WANG Shouming FENG Mei

2022, 50(3):  57-64.  doi:10.12141/j.issn.1000-565X.210364

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Surface deformation of the hull is a prerequisite for the optimization of the ship shape. Surface deformation method based on the radial basis function interpolation is suitable for the optimization of the hydrodynamic performance of the ship. This paper mainly improved the method of obtaining the support radius in radial basis interpolation, and proposed a dynamic method for obtaining the support radius. It considered the influence of the distribution of variable points and the change of coordinates on the support radius. On this basis, the improved radial basis interpolation method was applied to the ship hydrodynamic performance multi-disciplinary comprehensive optimization platform developed by the authors team. The Series 60 ship type was used as the research object to complete the ship type optimization study under the given constraints and the feasibility of the method was proved.

Mechanical Engineering

Analysis of the Powertrain Mount Systems of Electric Vehicles by Considering the Correlation of Probabilistic Parameters



LÜ​ Hui, ZHAO Jiawei, MAO Haikuan, et al

2022, 50(3):  65-72.  doi:10.12141/j.issn.1000-565X.210445

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Aiming at the complex situation where the parameters of powertrain mounting system (PMS) of electric vehicle are both uncertain and correlated, this paper investigated the inherent characteristics of electric vehicle PMS considering the correlation of probabilistic parameters. Firstly, the correlation matrix and probabilistic parameters were employed to describe the correlation and uncertainty of PMS parameters. Then, the Monte-Carlo method (MCM) was developed to calculate the PMS inherent characteristics with correlated probabilistic parametersbased on Monte-Carlo sampling. Then, an efficient method for calculating the statistical moments of PMS inherent characteristics was put forward based on sparse grid numerical integration (SGNI). Finally, the effectiveness of the proposed approach was demonstrated by the numerical example of an electric vehicle PMS. The analysis results show that, the SGNI method has good accuracy and efficiency in solving statistical moments and bounds of PMS natural frequencies and decoupling ratios, compared with MCM. The correlation of probabilistic parameters has a great influence on the upper and lower bounds of decoupling ratios. More reasonable analysis results can be obtained by taking the correlation of the probabilistic parameters into consideration. 

Study on Residual Stress Control of Damaged Aircraft Component Based on Non-uniform Overlap Ratio Laser Shock Peening



ZHANG Junhao, CHENG Xiuquan, XIA Qinxiang, et al

2022, 50(3):  73-79.  doi:10.12141/j.issn.1000-565X.210309

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Based on the fitting relationship between residual compressive stress and overlap ratio, the laser spot path was designed under non-uniform overlap ratio. A laser shock peening finite element (FE) model for laser shock peening damaged 7075 aluminum alloy component was established based on ABAQUS software. The non-uniform overlap ratio laser shock peening simulation was realized and the distribution of residual stress was obtained. The results show that the non-uniform overlap ratio laser shock peening can keep the surface of the specimen in a state of uniform stress after grinding or under tensile load. By increasing the overlap ratio to control residual stress, the surface of the repaired component can be kept in a state of uniform compressive stress under tensile load, so as to inhibit the initiation and propagation of fatigue cracks. The experimental results are consistent with the simulation results, which verifies the reliability of the model.

Die Electrode Scheduling Problem Solution Based on Genetic Algorithm



XIA Qinxiang, LI Kai, MA Jun, et al

2022, 50(3):  80-87.  doi:10.12141/j.issn.1000-565X.210284

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In view of the scheduling problem of die electrode in CNC and EDM stages, a mathematical model with batch processing and correlation characteristics was established. To minimize the tardiness of die parts, the solving process of die electrode scheduling problem was divided into two stages: batch processing and batch scheduling. In the first stage, the batch processing problem was solved according to the principle of correlation, and the correlation priority batch algorithm was designed. In the second stage, the batch scheduling problem was solved by genetic algorithm, and a strategy based on animal breeding was proposed to improve the traditional genetic algorithm. The die electrode scheduling program was developed based on MATLAB software to realize the above two stages of solving process, and the test was carried out under 24 kinds of simulation examples. The results show that, the designed die electrode scheduling algorithm is effective for solving the batch processing and batch scheduling problem of die electrode; the proposed strategy of breeding can significantly improve the quality of traditional genetic algorithm solution; and the tardiness of die parts in the examples can be reduced by 16.71% at most.

Multiphysics Coupling Simulation of ECM Temperature Based on Different Turbulence Models



CHEN Yuanlong, LIN Hua, CHEN Peixuan, et al

2022, 50(3):  88-94,126.  doi:10.12141/j.issn.1000-565X.210219

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In view of the difficulties in the prediction and measurement of machining gap temperature distribution in the process of electrochemical machining (ECM), this paper established and analyzed a temperature multiphy-sics coupling model for profile ECM. The turbulence models of SA, k-ε, k-ω, SST and low-Reynolds-number k-ω were used to calculate the flow field distribution, and the temperature distribution was obtained by coupling electrical field, flow field and temperature field. The simulated value was compared with the experimental value. Results show that the near-wall region flow field solution accuracy of the low-Reynolds-number wall treatment is higher than that of the wall-function and the temperature in the ECM gap can reach a quasi-stable state in a relatively short time. The calculated temperature values based on SST and low-Reynolds-number k-ω models are very close to each other, and the simulated temperature values of the model coupled with the bubble rate are closer to the experimental values.

Large Eddy Simulation Flow Field Analysis and Visualization Test Verification of Hydraulic Torque Converter Under Braking Condition



CHAI Bosen, WANG Guangyi, ZHU Guoren, et al

2022, 50(3):  95-105.  doi:10.12141/j.issn.1000-565X.210232

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In order to accurately reveal the spatio-temporal evolution mechanism of the flow field of the hydraulic torque converter, five different Large Eddy Simulation models (SL, WALE, WMLES, WMLES S-Omega, KET) were used to simulate the three-dimensional flow field of hydraulic torque converter under braking conditions based on computational fluid dynamics theory. It identified and extracted the unsteady multiscale three-dimensional vortex structure inside the turbine, and then analyzed the characteristics of spatiotemporal multiscale vortex evolution and its influence laws on the evolution of flow field structure. Based on Particle Image Velocimetry (PIV) technology, dynamic real-time calibration method was used to measure the flow field inside the turbine of hydraulic torque converter. Based on the velocity and vorticity information extracted from the post processing, the simulation results of large eddy simulation were compared and the simulation applicability of five subgrid-scale turbulence models was analyzed. The results show that under braking conditions, the multiscale eddy simulation results of SL and WMLES models for the main flow area of the turbine channel are similar, the flow velocity ranges from 0.32m/s to 0.85m/s and the vorticity ranges from 250.77s-1 to 792.95s-1; for the turbine blade pressure surface near the wall high velocity area, the simulation results of WMLES model meet the PIV test results, the flow velocity ranges from 3.7m/s to 4.4m/s, while WMLES S-omega model is better for the simulation of vorticity field is better and the vorticity is 526.47s-1. From the perspective of three-dimensional vortex simulation, WMLES and WMLES S-omega models have more abundant numerical simulation results of three-dimensional vortex near the suction surface of blades, and they are more accurate in capturing small-scale vortex structures near the wall of blades. The KET model simulation results reproduce the obvious vortex shedding phenomenon at the turbine blade outlet, while other models are not accurate enough to identify the structure of three-dimensional vortex. The research results can provide theoretical guidance for high precision numerical simulation of hydraulic torque converter.

Modeling Simulation and Characteristics Analysis of Pump Control System of Concrete Pump Truck



HUANG Minghui, WANG Zhaozhuo, PAN Qing, et al

2022, 50(3):  106-118.  doi:10.12141/j.issn.1000-565X.210330

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This study carried out digital modeling, simulation and verification analysis on the piston pump which is the key hydraulic component of concrete pump truck system. Based on the analysis of its motion law and working principle, it took the swash plate axial piston pump with conical cylinder blocks as the research object, and characterized the kinematic characteristics and flow characteristics of the piston with the method of space geometry and established a variable pump plunger model with AMESim simulation software. Based on the analysis of constant power control, constant pressure compensator control and electro-hydraulic proportional control variable displacement principle of variable pump, etc., this study established a power-pressure-electro-hydraulic proportional compound controlled variable pump AMESim simulation digital model including sub-models such as the pump body piston model, valve plate model, sliding shoe model, variable mechanism model, etc. The outlet flow characteristics, pressure displacement characteristics, current displacement characteristics and transient response characteristics of the plunger pump were studied through the coordinated control of control of the swash plate inclination angle, motor speed, system load and control current. The research results show that the simulation characteristic curve obtained by using the established hydraulic pump digital model is in good agreement with the test results, and the maximum relative errors of the pressure displacement characteristic and current displacement characteristic prediction are 6.31% and 7.73%, respectively. Thus it verifies the accuracy of the model and provides model supports for digital twins and performance optimization upgrades of construction machinery.

Modal Analysis and Structure Optimization of Scissor Deployable Element Under Vibration Conditions



WU Shangsheng, CHEN Zhe, ZHOU Yunqi

2022, 50(3):  119-126.  doi:10.12141/j.issn.1000-565X.210409

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In order to study the response characteristics of the scissor-type deployable element under vibration conditions, the study used the ship rust removal device as the vibration source and firstly established the mechanical model of the scissor-type deployable element. And the reliability of the element members under extreme conditions was studied. Then it used numerical modal analysis method and dynamic stress test analysis method under random vibration to study the random excitation problem and response of the scissor expandable unit under vibration conditions. It proposed a method to eliminate the second-order transverse bending vibration and excitation resonance of the scissor expandable unit and carried out dynamic stress simulation for each structural optimization scheme. The results show that the second-order modal vibration (306.15Hz) of the scissor-type deployable unit and the random excitation resonance generated by rust removal are the main reasons for the vibration fatigue of the scissor-type deployable unit. The dynamic stress level of the unit can be reduced most significantly by increasing the thickness of the upper worktable from 10mm to 14mm, reducing the rigidity of the worktable from 20GPa to 19.5GPa, and adding a connecting shaft between the two connecting rods. The research results can provide a theoretical basis for the stable and reliable operation of the scissor deployable unit in engineering applications.

Physics

Thermodynamic Characteristics of a Single-Phase Dielectric System with the Action of Electrostatic Filed



HAN Guangze, XING Yukun, HU Qiuxia, et al

2022, 50(3):  127-132,139.  doi:10.12141/j.issn.1000-565X.210077

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Electrostatic field can modify transfer the physical properties of dielectric system, and the related researches and applications attracted more and more attention. This paper discussed in detail the actions of uniform electrostatic field on the pressure and mole fractions of a fluid dielectric system with a model of a single-phase fluid dielectric system with a parallel plate capacitor inside. Based on the principle of phase equilibrium, the variations of pressure and mole fractions of gas and liquid dielectric system with electric field intensity were derived by using the expression of chemical potential with the influence of electric field. The results show that the changes in pressure and mole fraction are not only proportional to the square of electric field strength, but also related to the temperature and the molar mass, density, and permittivity of the dielectric. The actions of electrostatic field can increase the pressure of the system and change the mole fraction of the mixture. However, whether the mole fraction of the component increases or decreases is determined by the relative magnitude of the molar mass and density of the components. Under the actions of electrostatic field, variation of liquid system is more significant than that of gas system. The findings of this research provide a new idea for measuring the dielectric constant, gas enrichment and composition controlling of mixture.

On the Relationship Between Stress/Excited Magnetic Field and Magneto-Mechanical Effect



ZHANG Fuchen, LI Hongmei, ZHAO Chuntian, et al

2022, 50(3):  133-139.  doi:10.12141/j.issn.1000-565X.200562

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In order to study the influence of stress and excited magnetic field on the magnetization and magnetic output of ferromagnetic materials, this study deduced the differential relationship model between magnetization and stress under constant excited magnetic field and the differential relationship model between the magnetization and excited magnetic field under constant stress condition,respectively, based on J-A theoretical model. The above models were verified by numerical simulation and experiment. The results show that the magnetization increases firstly and then decreases with the increase of the stress under the constant excited magnetic field, and the magne-tization increases with the increase of the excited magnetic field under the constant stress. In order to verify the correctness of the two above models, the corresponding verification experiments were designed to verify the relationship between magnetic output and stress under the constant excited magnetic field, and the relationship between magnetic output and excited magnetic field under the constant stress, respectively. The experiment results are consistent with the theoretical calculation results. This study provides a theoretical reference for the study of the physical mechanism of the stress-test by magnetic method, and guide the new thinking on the magneto-mechanical effect.

Research on Graphene-based Heat Transfer in Nanochannel by Using Non-equilibrium Molecular Dynamics



ZHAO Jin, QIN Yangjun, LIU Chang, et al

2022, 50(3):  140-146.  doi:10.12141/j.issn.1000-565X.210530

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With the characteristics of high thermal conductivity, Graphene has a good application prospect in the field of heat transfer, and it’s of great significance to study graphene thermal conductivity theory and application. This paper investigated the heat transfer behavior of graphene at the solid-liquid interface by using the molecular dynamics method, and studied the effect of graphene heat transfer layer on the wall-liquid interface thermal resistance and flow characteristics under different wall temperatures. The results show that a single graphene heat transfer la-yer can significantly reduce the temperature jump of the solid-liquid interface and the interfacial thermal resistance in a static fluid. The higher the wall temperature is, the more significant the reducing effects of the graphene layer on the interfacial thermal resistance will be. The a reduction rate is as high as 48% and 45.9%, respectively. The external force was applied to the fluid to keep fluid flowing, and the results show that, as the graphene-fluid inte-raction is weaker than the wall-fluid interaction, the velocity slip at the solid-liquid wall is increased. And graphene has the feature of a large specific surface area, so the number of molecules near the wall is increasead, and the thermal motion and the temperature jump near the wall is enhanced.