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  5. The Influence of Correclation on the Extreme Traffic Loading of Bridges
 
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The Influence of Correclation on the Extreme Traffic Loading of Bridges

Author(s)
O'Brien, Eugene J.  
Enright, Bernard  
Dempsey, Anthony T.  
Uri
http://hdl.handle.net/10197/4071
Date Issued
2010
Date Available
2013-06-01T03:00:09Z
Abstract
Accurate traffic loading models based on measured data are essential for the accurate assessment
of existing bridges. There are well-established methods for the Monte Carlo simulation of single lanes
of traffic, and this can easily be extended to model the loading on bridges with two independent streams of
traffic in opposing directions. However, a typical highway bridge will have multiple lanes in the same direction,
and various types of correlation are evident in measured traffic. This paper analyses traffic patterns using
multi-lane WIM data collected at two European sites. It describes an approach to the Monte Carlo simulation
of this traffic which applies variable bandwidth kernel density estimators to empirical traffic patterns of vehicle
weights, gaps and speeds. This method provides a good match with measured data for multi-truck bridge
loading events, and it is shown that correlation has a small but significant effect on lifetime maximum load effects.
Type of Material
Conference Publication
Publisher
CRC Press
Copyright (Published Version)
2012, Taylor and Francis Group
Subjects

Traffic loads

Monte Carlo simulatio...

Bridge loads

Language
English
Status of Item
Not peer reviewed
Journal
D.M. Frangopol, R. Sause & C.S. Kusko (eds.). Bridge Maintenance, Safety Management and Life-Cycle Optimization
Conference Details
Bridge Maintenance, Safety and Management (IABMAS'10) the Fifth International IABMAS Conference, Philadelphia, USA, 11-15 July 2010
ISBN
9780415621243
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
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Format

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Checksum (MD5)

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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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