Abstract
Scouring around bridge piers is the important safety issue of bridge management since it could lead to bridge slanting and collapsing. Since the mechanism of water flow around the pier structure is so complicated, which makes it is very difficult to develop a generic model to determine the scour depth. Many researchers have tried to estimate the scour depths around bridge piers by simulating the bridge model with the consideration of various factors such as the depth of water, average velocity of flow, and diameter of sand. However most of models require predefined conditions and can only be applied to certain types of bridges. In this study, an integrated model that combines genetic algorithms and simulation technology is developed to estimate the scour depth around bridge piers by using the natural frequency of the bridge structure. A series of simulations are first performed on a concrete bridge by setting different scour depths and environmental conditions to determine the possible values of the natural frequency. Since simulations generate a huge amount of data, which makes it hard to analyze and find the relation between the scour depth and the natural frequency. Then, genetic algorithms are used to find the fitted generic formula that defines the relationship between the scour depth and the natural frequency. The result of this study provides the bridge management authority an efficient and effective method to determine the scour depths around bridge piers and so forth to evaluate the bridge status when the flood strikes.
Original language | English |
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Pages | 514-519 |
Number of pages | 6 |
Publication status | Published - 2011 Dec 1 |
Event | 28th International Symposium on Automation and Robotics in Construction, ISARC 2011 - Seoul, Korea, Republic of Duration: 2011 Jun 29 → 2011 Jul 2 |
Other
Other | 28th International Symposium on Automation and Robotics in Construction, ISARC 2011 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 11-06-29 → 11-07-02 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Building and Construction