Reliability-based optimization of river bridges using artificial intelligence techniques

Turan, K. Hakan
Yanmaz, Ali Melih
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.


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Current seismic design approach of bridge structures can be categorized into two distinctive methods: (i) force based and (ii) performance based. AASHTO LRFD seismic design specification is a typical example of force based design approach especially used in Turkey. Three different importance categories are presented as “Critical Bridges”, “Essential Bridges” and “Other Bridges” in AASHTO LRFD. These classifications are mainly based on the serviceability requirement of bridges after a design earthquake. The ...
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: