Reliability-based optimization of river bridges using artificial intelligence techniques

Date

2011-10-01

Author

Turan, K. Hakan
Yanmaz, Ali Melih

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Proper bridge design is based on joint consideration of structural, hydraulic, and geotechnical conformities. An optimization-based methodology has been developed to obtain appropriate dimensions of a river bridge to meet these aspects. Structural and geotechnical design parts use a statistically-based artificial neural network (ANN) model. Therefore, relevant data were collected from many bridge projects and analyzed to form a matrix. Artificial neural network architectures are used in the objective function of the optimization problem, which is modeled using genetic algorithms (GA) with penalty functions. Bridge scouring reliability is performed using Monte-Carlo simulations. All the techniques are assembled in a software framework. Finally, an application is presented to assess the outputs of the software by focusing on the evaluations of hydraulic-structure interactions.

Subject Keywords

Civil and Structural Engineering, General Environmental Science

URI

https://hdl.handle.net/11511/48695

Journal

CANADIAN JOURNAL OF CIVIL ENGINEERING

DOI

https://doi.org/10.1139/l11-069

Collections

Department of Civil Engineering, Article

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Citation Formats

K. H. Turan and A. M. Yanmaz, “Reliability-based optimization of river bridges using artificial intelligence techniques,” CANADIAN JOURNAL OF CIVIL ENGINEERING, pp. 1103–1111, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48695.