Finite element model updating (FEMU) is an advanced inverse parameter identification method capable of identifying multiple parameters in a material model through one or a few well-designed material tests. The method has become more mature thanks to the widespread use of full-field measurement techniques, such as digital image correlation. Proper application of FEMU requires extensive expertise. This paper offers a review of FEMU and a guide to practice. It also presents FEMU-DIC, an open-source software package. We conclude by discussing the challenges and opportunities in this field with the intent of inspiring future research.

Background: The association of advanced digital image correlation (DIC) and numerical simulation has been widely used for inverse parameter identification. Objective: It is attractive to develop an accurate DIC method sharing the common features with numerical simulation, which can lead to better synergy between experiments and simulations. Methods: A new meshfree digital image correlation (MF-DIC) using element free Galerkin method (EFGM) is proposed for deformation measurement. The EFGM is a classical meshfree method in numerical studies, and it is directly used to construct the shape function in MF-DIC from a set of scattered nodes for image matching. The MF-DIC is principally different from the classical local DIC and global DIC since it does not rely on the concept of a subset or an element. Results: In MF-DIC, the $${C}^{1}$$C 1 -continuous displacement for every point is constructed based on a group of scattered nodes in a small support domain surrounding it. The continuous strain map can then be directly derived from the displacement, instead of using an additional smoothing technique as required in classical local DIC or post-processing used in global DIC. A performance assessment based on the Metrological Efficiency Indicator (MEI), as defined in DIC Challenge 2.0, shows that the proposed MF-DIC yields an excellent balance between spatial resolution and measurement resolution for both displacement and strain measurements. Conclusions: Given that the proposed MF-DIC shares common features with the classical meshfree method in computational mechanics, it paves the way for an enhanced synergy between experiments and simulations required for robust inverse parameter identification methods.

We propose an easy-to-implement and automatic telecentric camera calibration method. The proposed method adopts a virtual planar target, which is actively transformed and displayed on a fixed liquid crystal display screen, for calibrating telecentric cameras. Compared with regular methods that require human interaction to move physical planar targets, the proposed method offers the merits of simple and automatic calibration implementation, since it eliminates the needs of manufacturing and manually moving a physical calibration target. For validation, a single-camera telecentric pseudo-stereo vision system was calibrated using the proposed method. The calibrated telecentric stereo vision system was further used for three-dimensional reconstruction of both planar and complex surfaces. Experimental results demonstrate the proposed calibration method can be used for accurate telecentric stereo vision measurement.