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This content will become publicly available on November 27, 2018

Title: The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.
Authors:
 [1] ;  [2] ;  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Diagnostic Science & Engineering
Publication Date:
Report Number(s):
SAND-2017-5602J
Journal ID: ISSN 0014-4851; PII: 360
Grant/Contract Number:
AC04-94AL85000; NA0003525
Type:
Accepted Manuscript
Journal Name:
Experimental Mechanics
Additional Journal Information:
Journal Name: Experimental Mechanics; Journal ID: ISSN 0014-4851
Publisher:
Springer
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
Digital image correlation; Uncertainty quantification; Spatial resolution; Error estimates; Ill-posed inverse problems
OSTI Identifier:
1421608