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  5. Non-Linear Response of Structures to Characteristic Loading Scenarios
 
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Non-Linear Response of Structures to Characteristic Loading Scenarios

Author(s)
Hajializadeh, Donya  
O'Brien, Eugene J.  
Enright, Bernard  
Sheils, Emma  
Uri
http://hdl.handle.net/10197/4069
Date Issued
2012-06-17
Date Available
2013-01-21T16:52:58Z
Abstract
To assess the safety of an existing bridge, the traffic loads to which it may be subjected in its lifetime
need to be accurately quantified. In this paper the 75 year characteristic maximum traffic load effects are
found using a carefully calibrated traffic load simulation model. To generate the bridge loading scenarios,
an extensive weigh in motion (WIM) database, from three different European countries, is used.
Statistical distributions for vehicle weights, inter-vehicle gaps and other characteristics are derived from
the measurements, and are used as the basis for Monte Carlo simulations of traffic representing many
years. An advantage of this “long-run” simulation approach is that it provides information on typical
extreme traffic loading scenarios. This makes possible a series of nonlinear finite element analyses of a
reinforced concrete bridge to determine the response to typical characteristic maximum loadings.
Type of Material
Conference Publication
Copyright (Published Version)
2012, authors
Subjects

Weigh in motion

Bridge loads

Monte Carlo simulatio...

Language
English
Status of Item
Not peer reviewed
Conference Details
EMI/PMC Joint Conference of the Engineering Mechanics Instiatue and the 11th ASCE Joint Specialty Conference on Probalistic Mechanics and Structural Reliability, June 17-20, 2012, Notre Dame, USA
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
File(s)
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Thumbnail Image
Name

c128.pdf

Size

1.12 MB

Format

Adobe PDF

Checksum (MD5)

f4d8030c621fe21bc72a7850b941864a

Owning collection
Civil Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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