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Impact of measurement uncertainty from experimental load distribution factors on bridge load rating
Author(s): Michael V. Gangone; Matthew J. Whelan
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Paper Abstract

Load rating and testing of highway bridges is important in determining the capacity of the structure. Experimental load rating utilizes strain transducers placed at critical locations of the superstructure to measure normal strains. These strains are then used in computing diagnostic performance measures (neutral axis of bending, load distribution factor) and ultimately a load rating. However, it has been shown that experimentally obtained strain measurements contain uncertainties associated with the accuracy and precision of the sensor and sensing system. These uncertainties propagate through to the diagnostic indicators that in turn transmit into the load rating calculation. This paper will analyze the effect that measurement uncertainties have on the experimental load rating results of a 3 span multi-girder/stringer steel and concrete bridge. The focus of this paper will be limited to the uncertainty associated with the experimental distribution factor estimate. For the testing discussed, strain readings were gathered at the midspan of each span of both exterior girders and the center girder. Test vehicles of known weight were positioned at specified locations on each span to generate maximum strain response for each of the five girders. The strain uncertainties were used in conjunction with a propagation formula developed by the authors to determine the standard uncertainty in the distribution factor estimates. This distribution factor uncertainty is then introduced into the load rating computation to determine the possible range of the load rating. The results show the importance of understanding measurement uncertainty in experimental load testing.

Paper Details

Date Published: 27 March 2018
PDF: 5 pages
Proc. SPIE 10599, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII, 1059921 (27 March 2018); doi: 10.1117/12.2295607
Show Author Affiliations
Michael V. Gangone, The Univ. of Texas at Tyler (United States)
Matthew J. Whelan, The Univ. of North Carolina at Charlotte (United States)


Published in SPIE Proceedings Vol. 10599:
Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII
Peter J. Shull, Editor(s)

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