Table of Content

25 August 2021, Volume 49 Issue 8

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2021, 49(8):  0. 

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Traffic & Transportation Engineering

Freeway Travel Time Prediction Based on Spatial and Temporal Characteristics of Road Networks



LIN Peiqun XIA Yu ZHOU Chuhao

2021, 49(8):  1-11.  doi:10.12141/j.issn.1000-565X.200717

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In order to overcome the shortcomings of the existing prediction methods, such as short prediction steps and insufficient utilization of spatial-temporal characteristics of road networks, and to predict the freeway travel time accurately, five commonly used prediction models, namely RF(Random Forests),XGBoost(Extreme Gradient Boosting),LSTM(Long Short-Term Memory),KNN(K-Nearest Neighbor), and SVR(Support Vector Regression), were taken to carry out multi-steps prediction of freeway travel time based on the origin and destination data set. A fusion model based on Bayesian linear regression method was proposed. The Long-gang to Bu-long section of Shui-guan Expressway in Guangdong province was taken as a case study. We predicted the travel time of every 15 minutes in the next 2 hours. The results show that the prediction performance of RF model and XGBoost model is stable under multi-steps; the LSTM model has superior prediction performance in the case of short prediction steps; the fusion method integrates the advantages of various prediction methods and has higher accuracy and robustness. The experiments also demonstrate that it has the best prediction performance.

Influence Factor Analysis of Freeway Single-Vehicle Crash Severity



WEN Huiying ZHANG Xuan ZENG Qiang

2021, 49(8):  12-18.  doi:10.12141/j.issn.1000-565X.200699

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Single-vehicle crash, as a common crash type of freeway crash, leads to great loss to society every year.  To reduce the negative impact brought by this type of crash, this study took freeway single-vehicle crash severity as dependent variable and constructed a econometric model to investigate the major influence factors. And some engineering and management countermeasures were put forward. The single-vehicle crash data of Guangdong Kaiyang freeway in 2013—2015 was collected. To describe the weather condition at the time when crash occurred more comprehensively, specifically and accurately, real-time weather data was matched to each crash according to the crash time and location. In terms of methodology, considering that the crash severity was ordered and there might exist heterogeneity in crash data, random parameter ordered logit model was established to fit the data. The results show that, the impact of vehicle type and humidity on crash severity has significant heterogeneity. The significant variables also include driver type, emergency medical services (EMS) response time, wind speed and crash time. Compared to non-professional driver, professional driver has a 6.22% higher probability for severe crash. Compared to other vehicles like coach, truck has a 0.59% lower probability for severe crash. Compared to daytime, the probability of severe crash at night decreases 0.31%. When the EMS response time increases 1min, the humidity increases 1%, and the wind speed decreases 1m/s, the probability of severe crash would increase 0.01%, 0.02% and 0.10% respectively. Finally, according to the results, some safety countermeasures were put forward.

Evaluation and Analysis Model for Freeways Crash Risk Based on Real-Time Traffic Flow



MA Xinlu, FAN Bo, CHEN Shiao, et al

2021, 49(8):  19-25,34.  doi:10.12141/j.issn.1000-565X.200457

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A crash risk prediction model for freeway was developed with crash data and real-time traffic flow data to improve road active traffic management. The experimental sample sets were designed in matched case-control study and then the most significant traffic variables that have a crucial impact on the crash were selected by random forest algorithm. Based on the selected variables, the crash risk prediction model was developed in the support vector machine algorithm, and the performance of SVM models in the different kernel functions was compared. Meanwhile, in order to explore the effect of case-control matching ratios on the model performance, multiple sample sets with the different matching ratios were designed for the experiment. The results show that the model can effectively eva-luate the crash risk model according to the real-time traffic flow data. At the same time, the results show that increasing the case-control matching ratio has a particular effect on improving the models performance, and the ratio could be set explicitly according to traffic management needs.

Correlation Model of the Influence of Freeway Spatial Curvature Continuity Decline on Accident Frequency



WANG Xiaofei LIU Yong LI Siyu

2021, 49(8):  26-34.  doi:10.12141/j.issn.1000-565X.200685

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In order to analyze the impact of freeway three-dimensional spatial alignment continuity decline on traffic safety, this paper collected and statistically processed the alignment data and accident data of five interstate freeways in Washington State, USA from 2011 to 2018. The freeways were segmented with 100 meters length as the fixed length unit. The average spatial curvature of each unit (ASC), the absolute value of the curvature difference with the previous adjacent freeway unit(AVDP), and the absolute value of the curvature difference with the next adjacent freeway unit(AVDN) were calculated as descriptive variables, and the number of freeway unit accidents was used as the described variable. The traditional negative binomial model, zero-inflated negative binomial model, and zero-truncated negative binomial model were used to perform fitting analysis on all freeway units data and the freeway units data where accidents occurred. The results show that: the negative binomial model fits better than the zero-inflated negative binomial model based on all units data; the zero-truncated negative binomial model fits better than the negative binomial model based on the accident-occurring units data. In the four models, there is a large positive correlation between the absolute value of the curvature difference of the adjacent freeway unit and the safety level of the freeway unit, that is, increasing the continuous performance of the three-dimensional curvature of the freeway can improve the traffic safety level. It indicates that AVDP and AVDN can be used as a freeway alignment level evaluation index to provide support for the optimization of freeway alignment design.

Architecture & Civil Engineering

Experimental Investigation on Fatigue Properties of Q690D High Strength Steel



KANG Lan HONG Shutao

2021, 49(8):  35-42.  doi:10.12141/j.issn.1000-565X.200633

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One of the main failure modes of steel structure is fatigue failure, which is often accompanied by sudden fracture of steel. At present, there are little research on fatigue properties of Q690D high strength steel. In order to obtain the fatigue characteristic curve of Q690D high-strength steel, the high-cycle fatigue test of Q690D high-strength steel was carried out in this study. The S-N (stress-life) fatigue curve of Q690D high-strength steel was fitted based on the test results and compared with the existing fatigue test curves of standard fatigue formula and other strength grades of steel. The test results show that the fatigue performance of Q690D high strength steel is much better than that of ordinary steel, and is larger than the calculated values of the American steel structure specification (ANSI/AISC 360-10) and the European steel structure specification (BS EN 1993-1-9). It indicates that the fatigue performance of Q690D high strength steel is superior, and the calculated values of the specification are conservative. The fatigue curve of steel is highly correlated with its yield strength and has strong discreteness.





Axial Compression Behavior of the Stiffened Concrete-Filled Thin-Walled High-Strength Square Steel Tube Stub Columns



YANG Youfu GUO Hongxin

2021, 49(8):  43-52.  doi:10.12141/j.issn.1000-565X.200587

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To evaluate the effectiveness of different stiffening measures, the comparative study on the axial compression behavior of the stiffened and unstiffened concrete-filled thin-walled high-strength square steel tube stub co-lumns was carried out in this paper. Firstly, the axial compression experiments of the stiffened specimens and the reference unstiffened specimens were designed and carried out, and the influence of yield strength of steel tube and type of stiffening measures on the failure patterns, load versus axial displacement (strain) curves and the mechanical indexes, e.g. bearing capacity, composite elastic modulus and ductility index, of the specimens was investigated. The results show that the stiffening measures can alter the destruction process of the specimens and the failure patterns of steel tube and improve the mechanical indexes of the specimens. However, there are no stiffening mea-sures that can thoroughly enhance the mechanical indexes of the specimens. Secondly, by determining the reasonable constitutive model of steel and core concrete, the finite element model of the stiffened and unstiffened concrete-filled thin-walled high-strength square steel tube stub columns under axial compression was developed and verified through experiments. Eventually, the effect of major parameters on the axial compression behavior of the stiffened concrete-filled thin-walled high-strength square steel tube stub columns was further analyzed with the verified finite element model. The results show that, the demarcation points in different stages of load versus axial displacement curves and mechanical indexes of the stiffened composite stub columns are different, and the stiffening measure of diagonal binding ribs is more effective to improve bearing capacity and ductility, while the stiffening measure of double-row steel ribs is more effective to improve composite elastic modulus.

Damage of Concrete Sandwich Wall Subjected to Synergistic Effects of Blasts and Fragments



TIAN Li LI Jie LI Menghui

2021, 49(8):  53-64.  doi:10.12141/j.issn.1000-565X.200441

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The finite element model of concrete steel wire skeleton sandwich wall was established by ANSYS/LS-DYNA. The difference of displacement response of concrete steel wire skeleton sandwich wall under the action of shock wave, fragment, and a combination of the two was analyzed. And the influence of different axial compressive strength of concrete, steel wire skeleton yield strength, polystyrene foam density, angle of the inclined plug wire and arrangement, the thickness of the concrete on both sides and the bubble, the proportion of explosive distance and height and fragment size on the displacement response of concrete steel wire skeleton sandwich wall was investigated. The comparative test results show that the modeling method is reliable. The displacement of the wall under the action of single shock wave is greater than that under the action of single fragment and the combined action of the two, but the combined action of the two causes more serious damage to the wall. With the increase of the axial compressive strength of concrete and the thickness of concrete on both sides, the anti-explosion performance of the structure is enhanced. The steel wire skeleton yield strength and the density of polystyrene foam have little influence on the anti-explosion performance of the structure. The different angle and arrangement of diagonal filaments have great influence on the anti-explosion performance of the structure. The explosive height has little effect on the wall damage. When the proportional distance is fixed, the larger the explosive amount is, the more serious the wall damage will be. From the angle of wall damage, the larger the fragment size, the more serious the damage.

Anchorage Performance of Post-Installed Steel Bars Using Geopolymer Mortar as Adhesive



ZHANG Haiyan, LI Qiyu, JIANG Weian, et al

2021, 49(8):  65-74,84.  doi:10.12141/j.issn.1000-565X.200417

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Compared with ordinary Portland cement, geopolymer has the advantages of environmental friendliness, fast hardening and high early strength, smaller shrinkage, and better bond behavior. To investigate the feasibility of using geopolymer mortar as anchorage adhesive, pull-out tests were conducted on post-installed steel bars anchored by geopolymer mortar. Influences of substrate type (concrete, granite), anchorage depth, rebar diameter, and loading mode (monotonic, repeated) on anchorage performance of geopolymer mortar were investigated. Geopolymer mortar was compared with usual cement mortar and commercial organic adhesive, and its bond strength was compared with that of inorganic adhesive reported in literature. The results show that the anchorage performance of geopolymer mortar is significantly better than that of cement mortar and is almost equivalent to that of commercial organic adhesive. For a ribbed rebar with a diameter (d) of 16mm, when using geopolymer mortar as adhesive in concrete and granite substrate, a minimum embedded depth of 12d required by code can already satisfy the ancho-rage quality requirements. Furthermore, it is also showed that the anchorage performance of geopolymer mortar has no significant degradation under repeated loading, at a repeated loading level not higher than 70% of the ultimate load. Thus, geopolymer mortar can be used as anchorage adhesive for post-installed steel bars in the concrete substrate and granite substrate in practice.

Rotation Angle-Based Identification Method of Initial Bending Stiffness of Simply Supported Beams



YANG Yuhou, YANG Lufeng, QIN Bingxian, et al

2021, 49(8):  75-84.  doi:10.12141/j.issn.1000-565X.200557

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In order to develop an optimal method to identify the initial bending stiffness of a simply supported beam, the beam was segmented to directly measure or indirectly calculate the rotation angles at the segmentation cross-sections under a known static load based on the idea of virtual segmentation. The bending stiffness of various girder segments was inversely obtained by establishing a relationship between the rotation angle and bending stiffness of each girder segment. The correctness and validity of the proposed method was proved by a finite element analysis and the experiment data. The condition number of a matrix was applied to analyze the influence of the number of girder segments and the magnitudes, types, numbers, and positions of the acting forces on the stability of the identification equation set, and the influence of rotation angle measurement error on identification accuracy. The results show that the number of girder segments, number of forces, and positions of the forces were the key factors influencing the stability of the identification equation set; the acceptable rotation angle measurement noise increased with the decrease of the number of girder segments and the increase of sensor accuracy; under proper loading and test conditions, the proposed method shows high robustness in identification of initial bending stiffness of beams. The proposed method is simple and practical because it requires no complex inversion algorithm, support of a finite element model, or pre-measurement of parameters such as girder cross-section dimension, reinforcement, or mate-rial properties.

Structural Parameter Identification and Seismic Input Inversion Based on Transform Space Method



YANG Jipeng XIA Ye SUN Limin

2021, 49(8):  85-94.  doi:10.12141/j.issn.1000-565X.200573

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Aiming at the problem of structural parameter identification and unknown input inversion under earthquake, this paper proposed a method of structural parameter identification and seismic input inversion using only partial absolute acceleration measurements as the observation. Firstly, based on transform space method and least squares method, structural parameters above the first story were identified directly. Then, the stiffness of the first story was identified based on the identified modal information. Finally, the dynamic  equation was transformed into the transform space in which the correlation model of seismic input at adjacent sampling time was established and a simplified input inversion algorithm is presented. Results of numerical simulation and shaking table tests on a two-story reinforced concrete frame show that the proposed method has high accuracy and robustness for linear systems, and for nonlinear systems, the inversion results reflect the low-frequency characteristics of seismic input which can be used on seismic performance deductive analysis for regional structures and buildings.

Influence of Saturated Permeability Coefficient Variation on Failure Probability of Slope



WEI Hongwei ZHAO Fan

2021, 49(8):  95-102.  doi:10.12141/j.issn.1000-565X.200240

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Under the long-term geological action, the saturated permeability coefficient of soil shows natural strong spatial variability. In order to explore the influence of saturated permeability coefficient variation on the failure probability of slope, the Green-Ampt model was improved and the relationship among the depth of wetting front, the safety factor of slope and the duration of rainfall was determined. Then, Monte Carlo method was used to establish the analysis framework of variation of saturated permeability coefficient, and the  influence of saturated permeability coefficient variation on the failure probability of slope under different rainfall intensity was discussed. The results show that in the initial stage of rainfall, the smaller of the coefficient of variation of saturated permeability is, the smaller the failure probability of the slope is. With the increase of rainfall duration, the failure probability of the slope increases gradually, and with the increase of the coefficient of variation of saturated permeability, the failure probability of the slope becomes smaller. In the critical rainfall range, the failure probability of slope instability rises suddenly, and the critical rainfall range becomes concentrated with the increase of rainfall intensity.





Mechanical Engineering

Deep Neural Network Input Shaper for Residual Vibration Suppression



ZHANG Tie, KANG Zhongqiang, ZOU Yanbiao, et al

2021, 49(8):  103-112.  doi:10.12141/j.issn.1000-565X.200690

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A widely applicable post-adaptive input shaper algorithm was proposed to solve the residual vibration of multi-axis servo system caused by the flexibility of the system in the emergency stop section of high-speed motion. The algorithm does not need to identify the system modal parameters and it is based on the recursive least square method (RLS). The residual vibration signal was used as the input of the algorithm to optimize the shaper coefficient vector with the best vibration suppression effect under the current trajectory. The adaptive forgetting factor updating algorithm was introduced to improve the tracking performance of the shaper in non-stationary environment. A full connection multilayer neural network model was established and trained by using multiple sets of excitation tra-jectory samples. It solves the problem of the original algorithm that the cost of time is significantly increased due to multiple changes of trajectory and reoptimization. The experimental results show that the residual vibration amplitude of the post adaptive input shaper with adaptive forgetting factor is reduced by 28.3% averagely and 36.9% maximally, and the convergence time of residual vibration is reduced by 28.4%, compared with the traditional post adaptive input shaper. The residual vibration amplitude of the input shaper predicted by the multilayer perceptron model is reduced by 21.6% averagely and 29.8% maximally, and the convergence time of residual vibration is reduced by 23.7%, compared with the ordinary post adaptive input shaper. The algorithm proposed in this paper has certain application significance for improving the positioning accuracy of multi-axis servo system and shortening the positioning waiting time. The introduction of multilayer neural network model improves the overall work efficiency under the condition that the expected trajectory changes frequently.

Optimal Control Strategy for Lateral Stability of Port Heavy-Duty AGV



LIU Xuan, WANG Zihang, ZHANG Tongrui, et al

2021, 49(8):  113-121.  doi:10.12141/j.issn.1000-565X.200480

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A horizontal stability optimization control strategy of port overload AGV under low attachment coefficient road surface was proposed based on three-layer control structure. The MPC algorithm was used in the upper controller, which can continuously sample and predict the AGV dynamic parameters and alleviate the time lag problem of the control system caused by the series connection with the middle and lower-level controllers. The genetic algorithm was used in middle-level controller to optimize the parameters of the fuzzy controller for application to the stable control of the port AGV body. The SQP algorithm was applied in the lower-level controller to convert the driving torque optimal distribution problem into a quadratic programming sub-problem  and find an online solution. The Matlab / Simulink and Trucksim joint simulation platform based on port AGV was constructed to verifies the validity and robustness of the proposed strategy.





Fatigue Analysis of Hydraulic Excavator Working Device Based on Experiment Data



CAO Leilei, GUO Chengchen, WANG Yan, et al

2021, 49(8):  122-128,139.  doi:10.12141/j.issn.1000-565X.200634

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Aiming at the problem that the real working load is difficult to obtain in the fatigue analysis of hydraulic excavator working device, a method based on the measuring data and rigid-flexible coupling model was proposed to evaluate the fatigue life of working device. Taking a 21-ton excavator working device as the research object, the actual working pressures and displacements were measured by the pressure and displacement sensors during the digging process for different working mediums. Next, the excavating resistance on the bucket tip was calculated by the mechanical equilibrium equation. The forces of each hinge point was obtained by the rigid-flexible coupling virtual prototype simulation in ADAMS, then the real load-time history of hinge points for multi-working conditions was composed acoording to the proportion of the working mediums. Finally, the fatigue analysis for the boom and bucket rod were conducted in nCode, and the results were compared with that of the fatigue bench test. The results show that there is a good agreement between them. The method proposed in this paper can provide basis for anti-fatigue design of hydraulic excavator working device.

Torque Coordinated Control Strategy of PHEV Engine Starting in Motion Process



ZHANG Xin CUI Yuxuan XUE Qicheng

2021, 49(8):  129-139.  doi:10.12141/j.issn.1000-565X.200517

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When the plug-in hybrid electric vehicle (PHEV) starts the engine in motion process, the driving torque fluctuates greatly due to the different torque response characteristics of the motor and the engine. A torque coordinated control strategy was proposed in this paper to solve this problem. First of all, the hybrid electric vehicle power system model was established on the LMS.AMESim platform. Then, a torque coordination control strategy model of “clutch oil pressure fuzzy control + motor torque compensation + engine speed control + engine torque change rate limit” based on engine idling speed ignition was built on the Matlab/Simulink platform. Finally, based on the built co-simulation platform, the mode transition co-simulation was carried out and compared with different control strategies. The results show that the proposed mode switching control strategy can greatly improve the vehicle impact and clutch friction work, and improve the smoothness of mode transitions.

Multi-Dimensional Random Load Time Domain Simulation Based on Spectrum Correction Method



DOU Shuo LIU Zhiming MAO Liyong

2021, 49(8):  140-148.  doi:10.12141/j.issn.1000-565X.200643

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Engineering structures are often subjected to multi-dimensional random loads, and the accurate simulation of multi-dimensional random load time history is of great significance to the reliability design of structures. Based on the rigorous theoretical formula derivation of spectrum representation method about the multi-dimensional random load, the cause for the large deviation between the spectrum density matrix of the synthetic load and that of target load was analyzed in detail, providing a theory support for the multi-dimensional random load time domain simulation correction. A multi-dimensional random load time domain simulation algorithm based on the spectrum correction method was proposed. By calculating the deviation between the spectrum density matrix of the synthetic time domain load and that of the target load, the iterative technique was developed to modify the spectrum density matrix of the synthetic time domain load through feedback of errors. Furthermore, the spectrum density matrix of the synthetic time domain load was made to approach to that of the target load. Finally, a numerical analysis about three dimensional random load model was carried out. The results show that the spectrum density matrix of the synthetic multi-dimensional random load time history based on the spectrum correction method can accurately match the spectrum density matrix of the target load.