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  5. Adaptation of Cross Entropy optimisation to a dynamic Bridge WIM calibration problem
 
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Adaptation of Cross Entropy optimisation to a dynamic Bridge WIM calibration problem

Author(s)
Dowling, Jason  
O'Brien, Eugene J.  
González, Arturo  
Uri
http://hdl.handle.net/10197/4858
Date Issued
2012-11
Date Available
2013-11-08T09:10:42Z
Abstract
Moving Force Identification (MFI) theory can be used to create an algorithm for a Bridge Weigh-in-Motion (WIM) system that can produce complete force histories of the loads that have traversed a bridge structure. MFI is based on general inverse theory, however, and calibration of such a system requires a complete Finite Element (FE) model of the bridge to be available for implementation in the field. This is something that is often infeasible in practice as FE models created using theoretical values for material properties bear a poor relation to reality. The Cross Entropy optimisation method has been adapted here to address this calibration problem. The general system FE global mass and stiffness matrices of the bridge FE model are found by best fit optimisation to match field measurements. In this fashion a fully automated calibration procedure is developed for an MFI algorithm. This system is tested theoretically using three different FE plate models, coupled with a 3-dimensional vehicle model, allowing for Vehicle–Bridge Interaction (VBI).
Type of Material
Journal Article
Publisher
Elsevier
Journal
Engineering Structures
Volume
44
Issue
44
Start Page
13
End Page
22
Copyright (Published Version)
2012 Elsevier
Subjects

Bridge WIM

Weigh-in-Motion

Cross Entropy

Optimisation

Vehicle–Bridge Intera...

VBI

DOI
10.1016/j.engstruct.2012.05.047
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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J64 - rep vers.pdf

Size

707.12 KB

Format

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Checksum (MD5)

c83fe50dfc3c2bc7061dfa5bb4a3d535

Owning collection
Civil Engineering Research Collection
Mapped collections
Earth Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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