Shape Function-Based Strain Determination in DIC for Solids and Lattice Structures

Background: Additive Manufacturing offers the opportunity to build lattice structures with benefits in manufacturing efficiency and weight. For the determination of the fatigue properties of lattice structures, it lacks a method to determine the deformation under mechanic stress.

Objective: A digital image correlation (DIC) algorithm was implemented. The algorithm determines strains within a subset in an uncommon way by physically interpreting the subset shape function and does not need neighboring subsets, therefore.

Method: With a monochrome background this shape function-based strain determination is able to determine the deformation of a whole lattice unit cell, even if the background is visible in sectors of the subset. The implementation is validated by comparing the results in quasi-static tests on bulk material specimens to the results tactile sensors and a conventional DIC program. Then the deformation of lattice unit cells in fatigue tests is evaluated.

Results: The shape function-based strain determination performs well in quasi-static tests even for large deformations. The deformation of lattice unit cells is determined successfully, whereby conventional DIC algorithms can be challenged if the lattice’s strut diameter becomes close to the image resolution. The determined strains are appropriate for lifetime prediction and fractures can be detected.

Conclusion: The shape function-based strain determination is a suitable tool for determination of large local strains as well as strains in lattice structures, which do partially not cover the background in the whole region of interest due to periodic empty spaces between the lattice struts. For determination of strain fields, conventional DIC algorithms will still be more efficient in this state of development.