摘要
为提高列车—轨道—桥梁耦合系统动力分析的计算效率,基于耦合时变法及分离迭代法,提出了1种混合算法。该算法将列车—轨道—桥梁耦合系统分解为车辆—轨道子系统和桥梁子系统。其中,车辆—轨道子系统在每一时间步需根据车辆位置对系统刚度系数矩阵进行更新,具有时变的特性;桥梁子系统的系统动力系数矩阵在整个动力分析过程中保持不变;车辆—轨道子系统与桥梁子系统通过钢轨与桥梁间作用力的平衡迭代实现耦合。利用朔黄重载铁路32m简支梁桥现场试验数据与由混合算法计算得到的分析结果进行对比,验证了混合算法的可行性。采用耦合时变法和混合算法分别计算列车通过蒙华重载铁路黄河龙门大桥的动力响应,结果表明:采用相同的时间积分步长时,2种方法拥有相同的计算精度,但混合算法比耦合时变法具有更高的计算效率,求解耗时降低了75%。
In order to increase the computational efficiency for the dynamic analysis of the train-trackbridge coupled system,a hybrid algorithm was proposed based on the Coupled Time-varying Method（CTM）and the Separation-Iteration Method（SIM）.The train-track-bridge coupled system was separated into the train-track subsystem and the bridge subsystem by hybrid algorithm.The stiffness coefficient matrix of train-track subsystem was updated at every time step according to train position,thus the traintrack subsystem is time-varying.The dynamic coefficient matrix of bridge subsystem remained unchanged during the whole dynamic analysis process.The train-track subsystem and bridge subsystem were coupled by the equilibrium iteration of the forces between the rail and the bridge.The feasibility of hybrid algorithm was validated by comparing field data of a 32 msimply-supported beam bridge on Shuo-Huang heavy haul railway and the analysis results calculated by the hybrid algorithm.The dynamic responses of a train passing through the Longmen Yellow River Bridge on Meng-Hua heavy haul railway were calculated by the CTM and the hybrid method,respectively.Results show that,by applying the same time step,the two methods have the same computational accuracy,but the hybrid algorithm is more efficient than CTM.The computational time of the hybrid method is 75% shorter than that of the CTM.
出处
《中国铁道科学》
EI
CAS
CSCD
北大核心
2018年第1期66-74,共9页
China Railway Science
基金
国家重点研发计划项目(2017YFB1201204)
国家自然科学基金资助项目(51378511
51678576)
中南大学牵引动力国家重点实验室开放课题(TPL1601)
关键词
列车—轨道—桥梁耦合系统
动力学计算
动力响应
混合算法
分离迭代法
耦合时变法
计算效率
Train-track-bridge coupled system
Dynamic calculation
Dynamic response
Hybrid algo-rithm
Separation iterative method
Coupled time-varying method
Computational efficiency
