Global digital volume correlation of large volumes: a sub-volume adaptive meshing approach

Abstract

While global Digital Volume Correlation (DVC) yields more accurate results compared to local DVC, its main drawback remains the computational power needed to store and update the entire reference and deformed volumes during the optimisation process. This effectively prevents the use of global DVC for large volumes, with the exact size limit depending on the accessible RAM of the workstation or server running the DVC algorithm. This paper presents a development made at the University of Manchester at Harwell to perform a global DVC on X-ray Computed Tomography (XCT) volumes larger than the capabilities of a given computer hardware. The method relies on dividing the large meshed volume into smaller overlapping volumes, and corresponding meshes, that can be handled successively by the computer hardware to perform global DVC. Then, the nodes in the overlapping regions are assessed and the resulting sub-volumes global DVC results are merged into a single output result file covering the entire XCT volume. Overall, this sub-volume adaptive meshing approach is a solution to overcomes hardware limitations in cases where global DVC is required over large volumes and meshing density can be user-defined to fit the expected damage location within the sample.