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Collecting and using Weigh-in-Motion data in LRFD bridge design

Collecting and using Weigh-in-Motion data in LRFD bridge design The HL-93, a combination of the HS20 truck and lane loads along with the AASHTO LRFD live load factors were calibrated using 1975 truck data from the Ontario Ministry of Transportation to project a 75-year live load occurrence. Because truck traffic volume and weights have increased and truck configurations have become more complex, the 1975 Ontario data do not represent present US traffic loadings. Updating bridge live load models needs representative samples of unbiased truck weight data that meet accepted quality standards. A method that has been developed over the last three decades to capture truck loads in an undetected manner and obtain a true unbiased representation of actual highway loads is known as the Weigh-in-Motion, or WIM technology. The implementation of WIM systems in recent years has led to improving the quality and quantity of traffic data, which can be used to update the bridge design loads. The goal of NCHRP Project 12–76 was to develop a set of protocols and methodologies for using available recent WIM data collected at different US sites and recommend a step-by-step procedure that can be followed to obtain live load models for LRFD bridge design. The protocols are geared to address the collection, processing and use of national WIM data to develop and calibrate vehicular loads for LRFD superstructure design, fatigue design, deck design and design for overload permits. The recommended protocols were implemented using recent traffic data from 26 WIM sites in five states across the country. The states were California, Texas, Florida, Indiana and Mississippi. The states and WIM sites were chosen to capture a variety of geographic locations and functional classes, ranging from urban interstates, rural interstates and state routes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bridge Structures IOS Press

Collecting and using Weigh-in-Motion data in LRFD bridge design

Bridge Structures , Volume 5 (4) – Jan 1, 2009

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Publisher
IOS Press
Copyright
Copyright © 2009 by IOS Press, Inc
ISSN
1573-2487
eISSN
1744-8999
DOI
10.1080/15732480903143045
Publisher site
See Article on Publisher Site

Abstract

The HL-93, a combination of the HS20 truck and lane loads along with the AASHTO LRFD live load factors were calibrated using 1975 truck data from the Ontario Ministry of Transportation to project a 75-year live load occurrence. Because truck traffic volume and weights have increased and truck configurations have become more complex, the 1975 Ontario data do not represent present US traffic loadings. Updating bridge live load models needs representative samples of unbiased truck weight data that meet accepted quality standards. A method that has been developed over the last three decades to capture truck loads in an undetected manner and obtain a true unbiased representation of actual highway loads is known as the Weigh-in-Motion, or WIM technology. The implementation of WIM systems in recent years has led to improving the quality and quantity of traffic data, which can be used to update the bridge design loads. The goal of NCHRP Project 12–76 was to develop a set of protocols and methodologies for using available recent WIM data collected at different US sites and recommend a step-by-step procedure that can be followed to obtain live load models for LRFD bridge design. The protocols are geared to address the collection, processing and use of national WIM data to develop and calibrate vehicular loads for LRFD superstructure design, fatigue design, deck design and design for overload permits. The recommended protocols were implemented using recent traffic data from 26 WIM sites in five states across the country. The states were California, Texas, Florida, Indiana and Mississippi. The states and WIM sites were chosen to capture a variety of geographic locations and functional classes, ranging from urban interstates, rural interstates and state routes.

Journal

Bridge StructuresIOS Press

Published: Jan 1, 2009

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