Accuracy of stress measurement by Laue microdiffraction (Laue-DIC method): The influence of image noise, calibration errors and spot number

Laue microdiffraction, available at several synchrotron radiation facilities, is well suited for measuring the intragranular stress field in deformed materials thanks to the achievable submicrometer beam size. The traditional method for extracting elastic strain (and hence stress) and lattice orientation from a microdiffraction image relies on fitting each Laue spot with an analytical function to estimate the peak position on the detector screen. The method is thus limited to spots exhibiting ellipsoidal shapes, thereby impeding the study of specimens plastically deformed. To overcome this difficulty, the so-called Laue-DIC method introduces digital image correlation (DIC) for the evaluation of the relative positions of spots, which can thus be of any shape. This paper is dedicated to evaluating the accuracy of this Laue-DIC method. First, a simple image noise model is established and verified on the data acquired at beamline BM32 of the European Synchrotron Radiation Facility. Then, the effect of image noise on errors on spot displacement measured by DIC is evaluated by Monte Carlo simulation. Finally, the combined effect of the image noise, calibration errors and the number of Laue spots used for data treatment is investigated. Results in terms of the uncertainty of stress measurement are provided, and various error regimes are identified.The treatment of Laue microdiffraction images for stress analysis in deformed specimens can be improved by using digital image correlation techniques, thereby resulting in the so-called Laue microdiffraction (Laue-DIC) method. This method has demonstrated better performance than traditional methods in previous studies. In this work, two sources of errors affecting the accuracy of Laue-DIC, i.e. image noise and calibration errors, are identified, and their collective effect along with the influence of the number of spots recorded are assessed by Monte Carlo simulation.