Information
Edited & Published: Editorial Office of Journal of Dalian Jiaotong University
Publication Period: Bimonthly
Publisher: Dalian, Liaoning Province, China
Language: Chinese
Superintendent: Liaoning Provincial Department of Education
Sponsored by: Dalian Jiaotong University
Editor in Chief: Chen Bingzhi
Executive Editor in Chief: Guo Ruijun
China National unified serial number: CN 21-1550/U
International Standard Serial Number: ISSN 1673-9590
Periodical website: https://dltd.cbpt.cnki.net
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Development of Mechanical Model of Rubber Spring
CHI Maoru;ZHOU Di;DAI Liangcheng;LIANG Shulin;GAO Hongxing;CAI Wubin;WU Xingwen;Rubber springs are widely used in key parts of rail vehicles such as high-frequency vibration isolation, shock mitigation and elastic positioning. Therefore, the mechanical model of rubber springs is of great significance for the parameter design of rubber springs and the prediction of dynamic performance during vehicle operation. At home and abroad, the equivalent mechanical model and finite element model of rubber springs have developed from the initial simple characterization of static viscoelastic mechanical behavior to the current better description of their nonlinear dynamic characteristics under changing external load conditions. Meanwhile, neural network models have also been gradually applied in the prediction of mechanical properties of rubber springs in related research. However, the equivalent mechanical model and finite element model are difficult to balance structural dimensions and nonlinear mechanical characteristics, while neural network models lack specific physical meaning. Then, the prospect is put forward that the finite element neural network model is the development direction of the mechanical model of rubber springs. This model can not only more accurately characterize the influence of the dynamic characteristics of rubber springs on the dynamic performance of vehicles, but also provide guidance for the development of rubber springs.
Pure Electric Vehicle Routing Optimization Considering Impact of Ambient Temperature and Nonlinear Energy Consumption
WU Huirong;OUYANG Chao;YANG Yinuo;With the growth of urban logistics demand and the promotion of environmental protection policies, the proportion of electric vehicles in urban distribution has increased significantly. The traditional EV energy consumption model often ignores the nonlinear energy consumption characteristics of multi-factor coupling, and does not take into account the capacity degradation of the battery in low-temperature environment. A nonlinear energy consumption model is constructed by considering the factors such as air temperature, driving speed, real-time load and air conditioner operation status, and the battery capacity decay characteristics with temperature are incorporated into the EV path optimization problem to establish a pure EV path optimization model with time window constraints. An improved hybrid adaptive genetic algorithm(HAGA) is designed to validate the constructed model and algorithm by combining the set of cases and examples, and a sensitivity analysis is conducted to analyze the influence of temperature, load, air conditioning status and speed on the distribution scheme. The results show that this study proposes a pure electric vehicle path model and solution method considering the influence of temperature and nonlinear energy consumption, which can provide a decision basis for pure electric vehicle distribution in low-temperature cities.
Research on Multi-Modal Transport Path Optimization under Dual Uncertainties of Transportation Demand and Time
DU Jian;YANG Yuanyuan;ZHANG Ran;ZHANG Xian;WEN Xinran;Both of the container transportation demand and time in multimodal transport are uncertain. Under the arrival time window of node and the limitation of transport and transfer capacity, the dual-uncertainties will generate transportation delays or interruptions and cause economic losses. Therefore, a robust optimization study on transportation demand uncertainty is carried out according to the demand characteristics of multimodal transport in peak and off-peak seasons. Based on the random distribution characteristics of the multimodal transportation time, a random optimization study on the transportation time uncertainty is conducted. Aiming at the dual-uncertainties of robust transportation demand and random transportation time, the designed algorithm carries out the determination of uncertain models and the linearization of nonlinear functions in turn, and then uses CPLEX for model solving. Taking the multimodal transport network composed of 18 cities in China as the background, the results of four uncertain models are compared and analyzed, and the sensitivity of time variance and robust deviation values are also analyzed. The results show that the multimodal path can satisfy the time window constraints under transportation time randomness. With the increase in the time variance, multimodal transport prefers to choose the transport mode with higher speed. With the decrease in the robust deviation value, road transport is gradually replaced by railway and waterway transports due to the lack of transport capacity. Therefore, the freight enterprises can shorten the transportation time via road and railway for absorbing the time uncertainty, and they can use railway transport and water transport to improve the robustness of scheme for solving the fluctuation of transportation demand.
A Safety Management Method for Production Organization of Heavy Haul Railway Line Operation and Maintenance Based on Game Theory Combination Weighting Algorithm
CHEN Yang;SHI Lizhu;In order to improve the operation and maintenance efficiency of heavy-duty railway lines and ensure their safe and stable operation, a safety management method for heavy-duty railway line operation and maintenance production organization based on game theory combination weighting algorithm is proposed to enhance the operational stability. The various departments of railway line operation and maintenance production organization are divided, the conditions based on game theory combination weighting algorithm are defined, the mapping expression between production organizations is solved, and the mapping relationship between line operation and maintenance production organizations is analyzed. A production organization data warehouse is built, the sampled operation and maintenance production data fields are used to determine the management mode of line operation and maintenance production organization information, and the design of a safety management method is completed for heavy-duty railway line operation and maintenance production organization based on game theory combination weighting algorithm. The experiment results show that applying the above methods to manage various levels of operation and maintenance, production organizations can significantly improve the operation and maintenance production efficiency of heavy-duty railway lines, thereby ensuring their operational stability.
Structure Classification Optimization of Double Bathtub Gondola Car Body Based on Performance Characteristics
XIE Suming;YANG Wenbo;ZHANG Qiang;ZHANG Luying;Based on finite element analysis and structural optimization technology, the improvement of the performance index of heavy haul double bathtub gondola car body is studied. Firstly, the finite element analysis model of gondola car body is established according to the structure and load characteristics. According to TB/T3550.2-2019 standard and design task book, the overall vertical stiffness and overall structural modal analysis and evaluation of the car body are carried out. Aiming at the problem of low first-order frequency of the car body, the frequency optimization design variables are selected through the sensitivity analysis of the frequency to the car body components, and the structural optimization of the first-order frequency of the car body is conducted. After optimization, the first order frequency of the car body is increased by 1.3 Hz, and the mass is increased by 0.49 t. Under the calculation load of the strength index of the car body, the strength of the car body parts is analyzed and evaluated. Structural improvement and size optimization are carried out for the support bar support of the lower beam in the middle of the car body. In view of the safety factor does not meet the requirements of the car body in the middle of the lower beam strut support and the middle beam and the bathtub end area, the local structural reinforcement and the best stiffness matching and the optimal design of the ideal reinforcement shape are carried out. After the size optimization of the lower side beam strut support area and the partial step topology optimization of the middle beam and the bathtub end, the safety factor of the components meets the design requirements.
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