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Validation of Scenario Modelling for Bridge Loading
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File | Description | Size | Format | |
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j_93_rep_ver.pdf | 811.56 KB |
Date Issued
September 2016
Date Available
22T17:04:44Z February 2018
Abstract
Accurate estimates of characteristic bridge load effects are required for efficient design and assessment of bridges, and long-run traffic simulations are an effective method for estimating the effects. For multi-lane same-direction traffic, truck weights and locations on the bridge are correlated and this affects the calculated load effects. Scenario Modelling is a recently developed method which uses weigh-in-motion (WIM) data to simulate multi-lane same-direction traffic while maintaining location and weight correlations. It has been unclear however whether the method may produce unrealistic driver behaviour when extrapolating beyond the weigh-in-motion measuring period. As weigh-in-motion databases with more than about a year of data are not available, a microsimulation traffic model, which can simulate driver behaviour, is used here to assess the accuracy of extrapolating traffic effects using Scenario Modelling. The microsimulation is used to generate an extended reference dataset against which the results of Scenario Modelling are compared. It is found that the characteristic load effects obtained using Scenario Modelling compare well with the reference dataset. As a result, for the first time researchers and practitioners can model two-lane same-direction traffic loading on bridges while being confident that the approach is generating accurate estimates of characteristic load effects as well as effectively reproducing the complex traffic correlations involved.
Other Sponsorship
Irish National Roads Authority
6th Framework European Project, ARCHES
Type of Material
Journal Article
Publisher
Technika, Vilnius Gediminas Technical University
Journal
The Baltic Journal of Road and Bridge Engineering
Volume
11
Issue
3
Start Page
233
End Page
241
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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