The virtual fields method has been developed for extracting constitutive parameters from full-field measurements provided by optical non-contact techniques for instance. It is based on the principle of virtual work written with some particular virtual fields. This paper can be regarded as a general review summarising some 15 years of developments of this method. The main aspects of the method are first recalled in the case of both linear and non-linear constitutive equations. They are then illustrated by some recent relevant examples. Some studies underway as well as relevant issues to be addressed in the near future are eventually discussed.
Background: The DIC Challenge 2.0 follows on from the work accomplished in the first Digital Image Correlation (DIC) Challenge [1]. The second challenge was required to better quantify the spatial resolution of 2D-DIC codes. Objective : The goal of this paper is to outline the methods and images for the 2D-DIC community to use to evaluate the performance of their codes and improve the implementation of 2D-DIC. Methods : This paper covers the creation of the new challenge images and the analysis and discussion of the results. It proposes a method of unambiguously defining spatial resolution for 2D-DIC and explores the tradeoff between displacement and strain noise (measurement resolution) and spatial resolution for a wide variety of DIC codes by a combination of the images presented here and a performance factor called Metrological Efficiency Indicator (MEI). Results : The performance of the 2D codes generally followed the expected theoretical performance, particularly in the measurement of the displacement. The comparison did however show that even with fairly uniform displacement performance, the calculation of the strain spatial resolution varied widely. Conclusions : This work provides a useful framework for understanding the tradeoff and analyzing the performance of the DIC software using the provided images. It details some of the unique errors associated with the analysis of these images, such as the Pattern Induced Bias (PIB) and imprecision introduced through the strain calculation method. Future authors claiming improvements in 2D accuracy are encouraged to use these images for an unambiguous comparison.
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