Reliability-based optimization of river bridges using artificial intelligence techniques

Turan K. H., YANMAZ A. M.

CANADIAN JOURNAL OF CIVIL ENGINEERING, vol.38, no.10, pp.1103-1111, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 10
  • Publication Date: 2011
  • Doi Number: 10.1139/l11-069
  • Journal Name: CANADIAN JOURNAL OF CIVIL ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1103-1111
  • Keywords: bridge, optimization, artificial intelligence, reliability, Monte-Carlo simulation, NEURAL NETWORKS, SCOUR
  • Middle East Technical University Affiliated: Yes

Abstract

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.