A new Fourier-based large deformation Digital Volume Correlation Algorithm
Eyal Bar-Kochba (Brown University), Jennet Toyjanova (Brown University), Erik Andrews (), Kyung-Suk Kim (Brown University), Christian Franck (Brown University)
Eringen Medal Symposium in honor of G. Ravichandran
Tue 4:20 - 5:40
Salomon 001
In recent year digital volume correlation (DVC) algorithms have gained increased attention in experimental mechanics, biomechanics, and material science. DVC is used to measure three-dimensional deformation fields of a given material or tissue, by correlating intensity patterns within interrogation subvolumes. However, large-scale practical implementations of DVC algorithms have remained limited due to their inherent challenges in computational efficiency and calculation accuracy for large, non-linear deformations, such as indentation or penetration problems. To overcome these challenges, we developed and implemented a new Fourier-based large-deformation DVC formulation on graphics processing units (GPUs), which can be implemented on any personal computer and offers computational efficiency similar to parallel implementation on high performance clusters. The large-deformation algorithm employs a unique deformation-mapping scheme capable of capturing any general non-linear finite deformation behavior. This talk will present the mathematical basis and implementation details of our new method, and will highlight its suitability in detecting localized high magnitude strain fields using both simulated and experimental data.