Experimental validation of equations for 2D DIC uncertainty quantification

Abstract

Uncertainty quantification (UQ) equations have been derived for predicting matching uncertainty in twodimensional 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.