Modeling of Stochastic Dynamic Excitations and the Probability Density Evolution Theory for Nonlinear Stochastic Dynamics

Author(s):  
J. Li ◽  
Q. Yan ◽  
J. B. Chen
2017 ◽  
Vol 17 (10) ◽  
pp. 1750113 ◽  
Author(s):  
Zhongming Jiang ◽  
Jie Li

Stochastic dynamic analysis of structures with random parameters continues to be an open question in the field of civil engineering. As a newly developed method, the probability density evolution method (PDEM) can provide the probability density function (PDF) of the dynamic responses of highly nonlinear structures. In this paper, a new method based on PDEM and the kriging surrogate model, named the K-PDEM, is proposed to study the stochastic response of a structure. Being an exact interpolation method, the Gaussian process regression or the so-called kriging method is capable of producing highly accurate results. Unlike the traditional PDEM numerical method whose numerical precision is strongly influenced by the number of representative points, the K-PDEM employs the kriging method at each instant to generate additional time histories. Then, the PDEM, which is capable of capturing the instantaneous PDF of a dynamic response and its evolution, is employed in nonlinear stochastic dynamic systems. Because of the decoupling properties of the K-PDEM, the numerical precision of the result is improved by the enrichment of the generalized density evolution equations without increasing the computation time. The result shows that the new method is capable of calculating the stochastic response of structures with efficiency and accuracy.


Author(s):  
Zhi-ping Zeng ◽  
Xu-dong Huang ◽  
Jun-dong Wang ◽  
Fu-shan Liu ◽  
Wei-dong Wang ◽  
...  

Compared with ordinary railways, the curve radius of tram lines tends to be smaller, with minimum values of only 30 m. Therefore, wheel–rail interaction is more intense and complicated in sections of small radius tram line curves. Using a stochastic variable sample set based on a generalized probability density evolution method, the stochastic variable–spectrum representation method was used to generate a time-domain sample set of stochastic track irregularities. By inputting the stochastic set of track irregularities into a tram-track coupled dynamic system model, the stochastic dynamic response of the coupled dynamic system can be obtained. Moreover, by substituting the stochastic dynamic system response into the generalized probability density evolution formula, the process of probability density evolution of each evaluation index can be obtained by the finite difference method. Finally, the dynamic response of the tram-track coupled dynamic system can be evaluated by the probability distribution of each index. By setting a series of specific groove rail wear values, a tram-track coupled dynamic analysis was carried out, and compared with the specification requirements, vehicle safety limits under different wear values were obtained. This research has great engineering value for guiding the routine maintenance of small radius curve sections of trams.


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