A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction

2022 ◽  
Vol 170 ◽  
pp. 108799
Author(s):  
Huile Li ◽  
Tianyu Wang ◽  
Gang Wu
ICTE 2015 ◽  
2015 ◽  
Author(s):  
Hanfei Guo ◽  
Xiaoxue Liu ◽  
Wei Tong ◽  
Youwei Zhang ◽  
Yanlei Zhang

2017 ◽  
Vol 400 ◽  
pp. 481-507 ◽  
Author(s):  
Yanbin Li ◽  
Sameer B. Mulani ◽  
Rakesh K. Kapania ◽  
Qingguo Fei ◽  
Shaoqing Wu

1985 ◽  
Vol 107 (2) ◽  
pp. 196-202
Author(s):  
M. C. Leu ◽  
M. Jirapongphan

Two types of flow-induced vibrations in idling circular saws, random vibration and resonant vibration, were modeled and analyzed. The excitation source, which is the flow pressure fluctuations, was modeled as discrete forces acting at the saw teeth. The response was assumed to be uncoupled from the excitation in the random vibration analysis but coupled with the excitation in the resonant vibration analysis. The random vibration was solved in terms of statistical rms amplitudes and the resonant vibration as a time function. The analytical results captured many characteristics of vibration phenomena observed in idling saw experiments.


Sign in / Sign up

Export Citation Format

Share Document