Calibration of the finite element model of a long span cantilever through truss bridge using artificial neural networks

Download

index.pdf

Date

2008

Author

Yücel, Ömer Burak

Metadata

Show full item record

Item Usage Stats

48
views

54
downloads

In recent years, Artificial Neural Networks (ANN) have become widely popular tools in various disciplines of engineering, including civil engineering. In this thesis, Multi-layer perceptron with back-propagation type of network is utilized in calibration of the finite element model of a long span cantilever through truss called Commodore Barry Bridge (CBB). The essence of calibration lies in the phenomena of comparing and correlating the structural response of an analytical model with experimental results as closely as possible. Since CBB is a very large structure having complex structural mechanisms, formulation of mathematical expressions representing the relation between dynamics of the structure and the structural parameters is very complicated. Furthermore, when the errors in the structural model and noise in the experimental data are taken into account, a calibration study becomes more tedious. At this point, ANNs are useful tools since they have the capability of learning with noisy data and ability to approximate functions. In this study, firstly sensitivity analyses are conducted such that variations in dynamic properties of the bridge are observed with the changes in its structural parameters. In the second part, inverse relation between sensitive structural parameters and modal frequencies of CBB is approximated by training of a neural network. This successfully trained network is then fed up with experimental frequencies to acquire the as-is structural parameters and model updating is achieved accordingly.

Subject Keywords

Civil engineering.

URI

http://etd.lib.metu.edu.tr/upload/3/12609850/index.pdf
https://hdl.handle.net/11511/18210

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Approximate analysis and condition assesment of reinforced concrete t-beam bridges using artificial neural networks Dumlupınar, Taha; Hasançebi, Oğuzhan; Department of Civil Engineering (2008) In recent years, artificial neural networks (ANNs) have been employed for estimation and prediction purposes in many areas of civil/structural engineering. In this thesis, multilayered feedforward backpropagation algorithm is used for the approximate analysis and calibration of RC T-beam bridges and modeling of bridge ratings of these bridges. Currently bridges are analyzed using a standard FEM program. However, when a large population of bridges is concerned, such as the one considered in this project (Pen...
An improved finite grid solution for plates on generalized foundations Karaşin, Abdulhalim; Gülkan, Polat; Department of Civil Engineering (2004) In many engineering structures transmission of vertical or horizontal forces to the foundation is a major challenge. As a first approach to model it may be assumed that the foundation behaves elastically. For generalized foundations the model assumes that at the point of contact between plate and foundation there is not only pressure but also moments caused by interaction between the springs. In this study, the exact stiffness, geometric stiffness and consistent mass matrices of the beam element on two-para...
Predicting the shear strength of reinforced concrete beams using artificial neural networks Mansour, MY; Dicleli, Murat; Lee, JY; Zhang, J (Elsevier BV, 2004-05-01) The application of artificial neural networks (ANNs) to predict the ultimate shear strengths of reinforced concrete (RC) beams with transverse reinforcements is investigated in this paper. An ANN model is built, trained and tested using the available test data of 176 RC beams collected from the technical literature. The data used in the ANN model are arranged in a format of nine input parameters that cover the cylinder concrete compressive strength, yield strength of the longitudinal and transverse reinforc...
A Web based multi user framework for the design and detailing of reinforced concrete frames - beams Anıl, Engin Burak; Kılıç, Özgür; Department of Civil Engineering (2009) Structural design of reinforced concrete structures requires involvement of many engineers who contribute to a single project. During the design process engineers have to exchange wide variety of information. Unmanaged data exchange may result in loss of resources. Developing a data model and setting up protocols for the management of data related to various structural design tasks can help to improve the quality of the structural design. In this study, an object oriented data model was developed for reinfo...
Evaluation of cement mortars by ultrasound Paksoy, Nesibe Gözde; Yaman, İsmail Özgür; Department of Civil Engineering (2006) Ultrasonic testing of concrete is often used for the assessment of its uniformity, strength, modulus of elasticity, durability and etc. therefore, the related parameters of testing such as the transducer frequency, the specimen geometry and etc. are well-known. On the other hand, most of the concrete properties are affected by the cement and the mechanical as well as some durability properties of cements are determined through cement mortars. Applications of ultrasound on determining the properties of cemen...

Citation Formats

Ö. B. Yücel, “Calibration of the finite element model of a long span cantilever through truss bridge using artificial neural networks,” M.S. - Master of Science, Middle East Technical University, 2008.