Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Structural Engineering and Mechanics Volume 75, Number 4, August25 2020 , pages 519-527 DOI: https://doi.org/10.12989/sem.2020.75.4.519 |
|
|
|
Dynamic response uncertainty analysis of vehicle-track coupling system with fuzzy variables |
||
Ling Ye, Hua-Peng Chen, Hang Zhou and Sheng-Nan Wang
|
||
| Abstract | ||
| Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system\'s dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system\'s dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system\'s dynamic responses with fuzzy variables. | ||
| Key Words | ||
| vehicle-track coupling system; dynamic response; fuzzy variables; high dimensional representation approach; Monte Carlo method | ||
| Address | ||
| Ling Ye, Hua-Peng Chen, Hang Zhou: 1. Engineering Research Center of Railway Environment Vibration and Noise, Ministry of Education, East China Jiaotong University, Nanchang 330013, China 2. Institute for Smart Transportation Infrastructure, East China Jiaotong University, Jiangxi 330013, China Sheng-Nan Wang: Xiyi Road Sub-district Office, Organization Department, Xincheng District, Xi\'an, Shaanxi, China | ||