@inproceedings{c8da7c826e3546aea1ada7e9556d70b8,
title = "Use of structural health monitoring system for assessment of bridge load rating",
abstract = "A technical framework that uses a Structural Health Monitoring (SHM) system, which continuously measures bridge response to unknown ambient trucks, was proposed to calculate load ratings based upon finite element model simulations coupled with a statistical backbone. A steel bridge located in Iowa was selected to demonstrate this technical framework. Critical locations of the bridge were instrumented with a network of fiber optic sensors that collect real-time strain data from ambient trucks. As their characteristics were unknown, they were statistically characterized in terms of configuration and weight using Weigh-In-Motion (WIM) data collected in Iowa. Subsets of strain data were randomly selected to optimize computational models created with finite element software. The optimized models were used to determine distributions of load ratings following the AASHTO Load Factor Rating (LFR) methodology. Distributions were created for each strain set. The distributions, which account for variability in unknown trucks, can be used to evaluate the structural capacity of the bridge.",
keywords = "Bridge, Load rating distribution, Optimization, Strain data, Structural health monitoring system, Unknown trucks",
author = "Junwon Seo and Phares, {Brent M.} and Ping Lu and Wipf, {Terry J.} and Justin Dahlberg",
year = "2013",
doi = "10.1061/9780784412640.003",
language = "English",
isbn = "9780784412640",
series = "Forensic Engineering 2012: Gateway to a Better Tomorrow - Proceedings of the 6th Congress on Forensic Engineering",
pages = "18--27",
booktitle = "Forensic Engineering 2012",
note = "null ; Conference date: 31-10-2012 Through 03-11-2012",
}