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Reliability-based optimization of river bridges using artificial intelligence techniques
Date
2011-10-01
Author
Turan, K. Hakan
Yanmaz, Ali Melih
Metadata
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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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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.