Deformation measurements of 3D printed lattice-structured materials through image analysis

Measuring the deformation under loading conditions is a crucial part of any material characterization. Image analysis is a robust technology that determines the full-field deformation of a structure without interfering with its properties. These measurements are significantly challenging for lattice-structured materials due to the detailed geometries involved in the region of measurements. Furthermore, despite the advancements in Digital Image Correlation (DIC) techniques, there is a need for comprehensive performance analysis of different DIC software and alternative deformation measurement model development for complex geometric materials such as 3D-printed lattice-structured materials. Therefore, this research aims to investigate the deformation measurement of 3D-printed lattice-structured materials under compressive load using advanced image analysis techniques through validation and comparison of results. This study encompasses the performance analysis of a well-known commercial DIC software, an open-source DIC software, and a proposed Imaging Technique-based deformation analysis model for the full-field deformation measurement of 3D-printed lattice-structured materials. The results obtained from these techniques are compared with Finite Element simulations to validate their accuracy. The study also incorporates image segmentation for pre-processing images to improve the results. Five lattice types (Cubic, FCC, FCCZ, BCC and BCCZ) fabricated from PLA and TPU materials have been used to analyse their mechanical response under compressive loading. Results demonstrate that DIC analysis accurately portrays each material's unique deformation pattern. The commercial DIC software is efficient with a 7% deviation from the testing machine data for deformation in the Y direction, while the proposed Imaging Technique-based model shows a 6% deviation. In addition, the performance of the open-source DIC software improves after incorporating pre-processed images. This research also investigates the influence of several factors on the results, including speckle pattern on the surface, image resolution, background information, and illumination. This research establishes a unique dataset for lattice-structure deformation analysis and demonstrates the effectiveness of image-based measurement techniques for complex geometric materials. The findings highlight the potential of advanced image analysis techniques in improving the accuracy of deformation measurements and contribute to the development of more reliable and efficient DIC methods.