Model and response updating of stochastic nonlinear dynamic systems using strong vibration data
There has long been interests to improve the behavior of structure under strong vibration generated by earthquake. As deriving the relevant character of structures through physics experiment will be costly, great attention is drawn to develop algorithm to improve the predictive capability of stru...
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| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
2016
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| 主題: | |
| 在線閱讀: | http://hdl.handle.net/10356/68021 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | There has long been interests to improve the behavior of structure under strong
vibration generated by earthquake. As deriving the relevant character of
structures through physics experiment will be costly, great attention is drawn to
develop algorithm to improve the predictive capability of structural model
mathematically based on historical data. Bayesian statistical framework is one
of the guiding idea that current research focus on. In this approach, the
probability of all models are treated as a set of candidate, and they are selected
based on their possibility of appearance. Based on the idea of Bayesian
updating, numbers mathematical algorism and its application have been
developed. Among all these methods, Transitional Markov Chain Monte Carlo
(TMCMC) method is one of the techniques that could solve the non-normalized
posterior PDF problems. Therefore, this research focus on the application of
TMCMC method to examine the feasibility of the technique. Two cases with
different number of parameters are examined by applying TMCMC method.
And it is found that the method works well on the case of less number of
parameters. However, the algorithm may not be suitable to apply on the case
with large number of parameters as the time needed to complete the calculation
would be too long. |
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