A BAYESIAN UPDATING BASED PROBABILISTIC MODEL FOR THE DYNAMIC RESPONSE OF DEEPWATER BRIDGE PIERS UNDER WAVE LOADING

Deepwater bridge piers suffer from long-term irregular and dynamic wave loading in ocean environment. Although the static wave calculation approach based on characteristic waves used in the traditional design practice is simple and efficient, the effect of randomness and dynamics on the structures cannot be considered. This paper focuses on the probabilistic relationship between dynamic response and static response of a deepwater pier under wave loading. A probabilistic model based on Bayesian updating was proposed. The accuracy of the probabilistic model was verified through the comparison with the dynamic results of time-domain analyses. The selection of sample size and the model formulations were then discussed. This research showed that the proposed probabilistic model could calculate dynamic response of the deepwater pier under wave loading quickly and efficiently and corrected the inherent bias of the conventional static method. The proposed model is also able to estimate the dynamic response of the deepwater pier even if the sample size is very small.