Eugene J. OBrien, Cathal Leahy, Bernard Enright, Colin C. Caprani - Validation of scenario modelling for bridge loading (Vol XI, No 3)

Vilnius Gediminas Technical UniversityRiga Technical UniversityTallinn University of TechnologyBaltic Road Association

 

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2015 Impact Factor: 0.519 ©2015 Thomson Reuters, 2015 Journal Citation Report®

ISSN 1822-427X print
ISSN 1822-4288 online
 

 

 
 

"The Baltic Journal of Road and Bridge Engineering"
Vilnius: Technika, 2016, Vol XI, No 3, p. 233-241


Eugene J. OBrien, Cathal Leahy, Bernard Enright, Colin C. Caprani

Validation of scenario modelling for bridge loading

DOI: 10.3846/bjrbe.2016.27
 
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 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 weighin-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.
 
Keywords: bridges, highway, loads, scenario modelling, traffic, trucks.

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