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Experimental validation of equations for 2D DIC uncertainty quantification.

Conference ·
OSTI ID:988962
Uncertainty quantification (UQ) equations have been derived for predicting matching uncertainty in two-dimensional image correlation a priori. These equations include terms that represent the image noise and image contrast. Researchers at the University of South Carolina have extended previous 1D work to calculate matching errors in 2D. These 2D equations have been coded into a Sandia National Laboratories UQ software package to predict the uncertainty for DIC images. This paper presents those equations and the resulting error surfaces for trial speckle images. Comparison of the UQ results with experimentally subpixel-shifted images is also discussed.
Research Organization:
Sandia National Laboratories
Sponsoring Organization:
USDOE
DOE Contract Number:
AC04-94AL85000
OSTI ID:
988962
Report Number(s):
SAND2010-1482C
Country of Publication:
United States
Language:
English