- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | ZHOU Ziji, ZHANG Nan, YAN Guobin. Application of Good Lattice Point with Power Generator Method in Stochastic Dynamic Analysis of Vehicle-Bridge System[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20220831
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Since it is difficult to accurately select representative super-high-dimensional random phase angles, the good lattice point with power generator method (GLPPGM) was utilized to generate samples of representative track irregularities, which were applied to the vehicle-bridge system to obtain the mean and standard deviation of random dynamic responses. Then, the calculation accuracy and efficiency of this method were explored by comparing the results of the pseudo-excitation method, deterministic time history method, and Monte Carlo method (MCM). Finally, the threshold value of the derailment factor considering the daily operation volume of trains was studied by using linear and nonlinear wheel-rail contact relationships. The Harmony train passing over a bridge was studied, and the results show that compared with that by the MCM, the uniformity between the samples of track irregularities generated by the GLPPGM in different directions is better. The probability characteristic parameters of the random dynamic response obtained by the GLPPGM have higher calculation accuracy than different methods, and its calculation efficiency is nearly five times higher than that of the MCM. When linear and nonlinear wheel-rail contact relationships are considered, the threshold value of the derailment factor differs by 4.68%, and the GLPPGM has a wider applicability.
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