重載鐵路車—軌—橋系統(tǒng)垂向建模及動力性能優(yōu)化
[Abstract]:The development demand of speed increase, large axle load and long marshalling of heavy load railway transportation puts forward higher requirements for the safety and durability of vehicle-rail-bridge system. The dynamic simulation model is established to study and optimize the dynamic response of vehicle-rail-bridge system, which can provide the relevant design basis for line design to meet its development needs. In this paper, the vehicle is regarded as a multi-rigid-body system, and the finite element equation of ballasted track-bridge of heavy-duty railway is derived. the vertical dynamic model of heavy-duty railway vehicle-rail-bridge system is established by using Hertz nonlinear wheel-rail relationship. The iterative solution of dynamic response of vehicle-rail-bridge system is realized by Matlab program, and the reliability of the model is verified by comparing with the measured data. Then the vehicle, track and bridge parameters are selected to simulate the dynamics of the vehicle-rail-bridge system, and the variation of the peak value of the system response under different track structure parameters is studied. Based on the change law, the single objective and multi-objective dynamic response optimization conditions are set up, and the dynamic performance of the vehicle-rail-bridge system is optimized by using the genetic algorithm optimization method of Pareto ranking, and the optimal parameters under different working conditions are obtained. The main conclusions are as follows: (1) the change of track structure parameters has different degrees of influence on the response peak value of each component of the vehicle-rail-bridge system. When the rail underlying stiffness kp and the track bed thickness hb change, the rail, sleeper, track bed vertical acceleration, velocity response peak value, especially the vertical acceleration response peak value, has little effect on the bridge response peak value, and has little effect on the vertical displacement response of the whole system. (2) the peak value of rail acceleration response is the smallest, and the rail underlying cushion stiffness kp is 160 MN/m,. (2) the peak value of rail acceleration response is the smallest, and the rail underlying layer stiffness kp is 160 MN/m,. The thickness of track bed hb is 0.31m; The peak acceleration response of the ballast block is the smallest, and the stiffness of the underlying layer of the rail kp is 60 MN/m, and the thickness of the track bed is 0.60 m. When different optimization results are compared, the optimal values of rail underlying stiffness kp or track bed thickness hb are different, and the system response level should be taken into account in practical engineering. (3) the optimization results of multiple kinds of dynamic response peaks show that when the rail acceleration response and sleeper acceleration response, or the combination of rail acceleration response and ballast block acceleration response, the reasonable stiffness kp of rail underlying layer is 180mm, and the reasonable thickness hb of track bed is 0.39m. When the acceleration response of sleeper and ballasted block is combined, the reasonable stiffness kp of underlying layer is 160mn m, and the reasonable thickness of track bed hb is 0.60m. In this paper, from the point of view of dynamic response of vehicle-rail-bridge system, combined with different optimization objectives, the reference values of track bed thickness and cushion stiffness under rail are given. (4) in terms of optimization efficiency, the optimization results of three times of independent repeated optimization for each working condition are consistent, which shows that the genetic algorithm proposed in this paper can optimize the dynamic performance of vehicle-rail-bridge system, and the optimization efficiency is remarkable.
【學位授予單位】:北京交通大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:U211;U441.7;U239.4
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