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| Abstract: |
| Scour has been widely accepted as a key reason for bridge failures. Bridges are susceptible and sensitive to the scour phenomenon, which describes the loss of riverbed sediments around the bridge supports because of flow. The carrying capacity of a deep-water foundation is influenced by the formation of a scour hole, which means that a severe scour can lead to a bridge failure without warning. Most of the current scour predictions are based on deterministic models, while other loads at bridges are usually provided as probabilistic values. To integrate scour factors with other loads in bridge design and research, a quantile regression model was utilized to estimate scour depth. Field data and experimental data from previous studies were collected to build the model. Moreover, scour estimations using the HEC-18 equation and the proposed method were compared. By using the “CCC (Calculate, Confirm, and Check)” procedure, the probabilistic concept could be used to calculate various scour depths with the targeted likelihood according to a specified chance of bridge failure. The study shows that with a sufficiently large and continuously updated database, the proposed model could present reasonable results and provide guidance for scour mitigation. |
| Key words: bridge scour scour estimation quantile regression probabilistic model deterministic models |
| DOI：10.11916/j.issn.1005-9113.2019040 |
| Clc Number:U442.59 |
| Fund: |
