Proper bridge design is based on consideration of structural, hydraulic, and
geotechnical conformities at an optimum level. The objective of this study is to
develop an optimization-based methodology to select appropriate dimensions for
components of a river bridge such that the aforementioned design aspects can be
satisfied jointly. The structural and geotechnical design parts uses a statisticallybased
technique, artificial neural network (ANN) models. Therefore, relevant data
of many bridge projects were collected and analyzed from different aspects to put
them into a matrix form. ANN architectures are used in the objective function of
the optimization problem, which is modeled using Genetic Algorithms with penalty
functions as constraint handling method. Bridge scouring reliability comprises one
of the constraints, which is performed using Monte-Carlo Simulation technique. All
these mechanisms are assembled in a software framework, named as AIROB.
Finally, an application built on AIROB is presented to assess the outputs of the
software by focusing on the evaluations of hydraulic &ndash / structure interactions.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613062/index.pdf |
| Date | 01 February 2011 |
| Creators | Turan, Kamil Hakan |
| Contributors | Yanmaz, A. Melih |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | Ph.D. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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