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Update on the 2D-DIC challenge: Results and conclusions

Conference Proceedings of the Society for Experimental Mechanics Series

Reu, Phillip L.; Toussaint, E.; Jones, E.; Bruck, H.; Iadicola, M.; Balcaen, R.; Turner, Daniel Z.; Siebert, T.; Lava, P.; Simonsen, M.; Grewer, M.

The 2D-DIC Challenge is organized by an international committee working to understand the accuracy of digital image correlation (DIC) through standardized image sets. The DIC Challenge is run under the auspices of the Society for Experimental Mechanics (SEM) and the International DIC Society (iDICs). The 2D-Challenge incorporates 19 image sets that can be used in evaluating 2D-DIC algorithms. The full results of the study and description of the image sets may be found in Reu et al. (Exp Mech, 2017). A new round of the 2D Challenge is being launched at SEM 2018 and will seek to probe the concept of spatial resolution.

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TYPE Conference Poster YEAR 2019
ScopusOSTIDOI

Parameter covariance and non-uniqueness in material model calibration using the Virtual Fields Method

Computational Materials Science

Jones, Elizabeth M.; Carroll, Jay D.; Karlson, Kyle N.; Kramer, S.L.B.; Lehoucq, Richard B.; Reu, Phillip L.; Turner, Daniel Z.

Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Finally, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.

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TYPE Journal Article YEAR 2018
ScopusOSTIDOI

DIC Challenge: Developing Images and Guidelines for Evaluating Accuracy and Resolution of 2D Analyses

Experimental Mechanics

Reu, Phillip L.; Toussaint, E.; Jones, E.; Bruck, H.A.; Iadicola, M.; Balcaen, R.; Turner, Daniel Z.; Siebert, T.; Lava, P.; Simonsen, M.

With the rapid spread in use of Digital Image Correlation (DIC) globally, it is important there be some standard methods of verifying and validating DIC codes. To this end, the DIC Challenge board was formed and is maintained under the auspices of the Society for Experimental Mechanics (SEM) and the international DIC society (iDICs). The goal of the DIC Board and the 2D–DIC Challenge is to supply a set of well-vetted sample images and a set of analysis guidelines for standardized reporting of 2D–DIC results from these sample images, as well as for comparing the inherent accuracy of different approaches and for providing users with a means of assessing their proper implementation. This document will outline the goals of the challenge, describe the image sets that are available, and give a comparison between 12 commercial and academic 2D–DIC codes using two of the challenge image sets.

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TYPE Journal Article YEAR 2018
ScopusOSTIDOI

High-throughput Material Characterization using the Virtual Fields Method

Jones, Elizabeth M.; Carroll, Jay D.; Karlson, Kyle N.; Kramer, Sharlotte L.; Lehoucq, Richard B.; Reu, Phillip L.; Seidl, Daniel T.; Turner, Daniel Z.

Modeling material and component behavior using finite element analysis (FEA) is critical for modern engineering. One key to a credible model is having an accurate material model, with calibrated model parameters, which describes the constitutive relationship between the deformation and the resulting stress in the material. As such, identifying material model parameters is critical to accurate and predictive FEA. Traditional calibration approaches use only global data (e.g. extensometers and resultant force) and simplified geometries to find the parameters. However, the utilization of rapidly maturing full-field characterization tech- niques (e.g. Digital Image Correlation (DIC)) with inverse techniques (e.g. the Virtual Feilds Method (VFM)) provide a new, novel and improved method for parameter identification. This LDRD tested that idea: in particular, whether more parameters could be identified per test when using full-field data. The research described in this report successfully proves this hypothesis by comparing the VFM results with traditional calibration methods. Important products of the research include: verified VFM codes for identifying model parameters, a new look at parameter covariance in material model parameter estimation, new validation tech- niques to better utilize full-field measurements, and an exploration of optimized specimen design for improved data richness.

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TYPE SAND Report YEAR 2018
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The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

Experimental Mechanics

Turner, Daniel Z.; Lehoucq, Richard B.; Reu, Phillip L.

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.

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TYPE Journal Article YEAR 2017
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A nonlocal strain measure for DIC

Conference Proceedings of the Society for Experimental Mechanics Series

Turner, Daniel Z.; Lehoucq, Richard B.; Reu, Phillip L.

It is well known that the derivative-based classical approach to strain is problematic when the displacement field is irregular, noisy, or discontinuous. Difficulties arise wherever the displacements are not differentiable. We present an alternative, nonlocal approach to calculating strain from digital image correlation (DIC) data that is well-defined and robust, even for the pathological cases that undermine the classical strain measure. This integral formulation for strain has no spatial derivatives and when the displacement field is smooth, the nonlocal strain and the classical strain are identical. We submit that this approach to computing strains from displacements will greatly improve the fidelity and efficacy of DIC for new application spaces previously untenable in the classical framework.

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TYPE Conference Poster YEAR 2016
ScopusOSTI
Results 1–25 of 28
Results 1–25 of 28