This report evaluates several interpolants implemented in the Digital Image Correlation Engine (DICe), an image correlation software package developed by Sandia. By interpolants we refer to the basis functions used to represent discrete pixel intensity data as a continuous signal. Interpolation is used to determine intensity values in an image at non - pixel locations. It is also used, in some cases, to evaluate the x and y gradients of the image intensities. Intensity gradients subsequently guide the optimization process. The goal of this report is to inform analysts as to the characteristics of each interpolant and provide guidance towards the best interpolant for a given dataset. This work also serves as an initial verification of each of the interpolants implemented.
Digital image correlation (DIC) uses images from a camera and lens system to make quantitative measurements of the shape, displacement, and strain of test objects. This increasingly popular method has had little research on the influence of the imaging system resolution on the DIC results. This paper investigates the entire imaging system and studies how both the camera and lens resolution influence the DIC results as a function of the system Modulation Transfer Function (MTF). It will show that when making spatial resolution decisions (including speckle size) the resolution limiting component should be considered. A consequence of the loss of spatial resolution is that the DIC uncertainties will be increased. This is demonstrated using both synthetic and experimental images with varying resolution. The loss of image resolution and DIC accuracy can be compensated for by increasing the subset size, or better, by increasing the speckle size. The speckle-size and spatial resolution are now a function of the lens resolution rather than the more typical assumption of the pixel size. The paper will demonstrate the tradeoffs associated with limited lens resolution.
Full-field axial deformation within molten-salt batteries was measured using x-ray imaging with a sampling moiré technique. This method worked for in situ testing of the batteries because of the inherent grid pattern of the battery layers when imaged with x-rays. High-speed x-ray imaging acquired movies of the layer deformation during battery activation. Numerical validation of the technique, as implemented in this paper, was done using synthetic and numerically shifted images. Typical results of a battery are shown for one test. Ongoing work on validation and more test results are in progress.
After the meetings at SEM and ICEM this year, which were both well attended by participants, it was decided by the participants that a first round of scoring the codes would be done using the Sample 14 and Sample 15 images. There was plenty of discussion on how we (the DIC Challenge Board) were going to score the results. What is going to be the balance between noise and filtering? And so forth. So it was decided to use a sub-group of the participants to help figure out if the submission guidelines were working, and how we would score the results. An additional benefit of this is that we can fix any submission guideline issues before getting results more broadly, and begin writing automated analysis codes. I expect that there will be a discussion on both subjects after I create a draft document of the scoring. This document is a draft of that report.
There are numerous scenarios where critical systems could be subject to penetration by projectiles or fixed objects (e.g., collision, natural disaster, act of terrorism, etc.). It is desired to use computational models to examine these scenarios and make risk-informed decisions; however, modeling of material failure is an active area of research, and new models must be validated with experimental data. The purpose of this report is to document the experimental work performed from FY07 through FY08 on the Campaign Six Plate Puncture project. The goal of this project was to acquire experimental data on the puncture and penetration of metal plates for use in model validation. Of particular interest is the PLH failure model also known as the multilinear line segment model. A significant amount of data that will be useful for the verification and validation of computational models of ductile failure were collected during this project were collected and documented herein; however, much more work remains to be performed, collecting additional experimental data that will further the task of model verification.
