Fabien introduces innovative approach to Digital Volume Correlation
Revolutionising Material Analysis: Sub-Volume Adaptive Meshing in Global Digital Volume Correlation
Materials science is an exciting and constantly evolving study of the properties and behaviour of different materials. Digital Volume Correlation (DVC) is a crucial technique in this field, enabling researchers to accurately track changes and analyse complex structural deformations. By capturing digital images at different stages of deformation, DVC can be used to study the deformation of 3D structures on both small and large scales.
However, when it comes to performing DVC, two approaches emerge: local and global. The local approach divides a 3D image into smaller sub-volumes, independently calculating displacement parameters for each. On the other hand, the global approach computes a shared set of parameters for the entire image. While the global approach yields more accurate results due to continuous displacement interpolation, it faces hardware limitations. The sheer computational power required to manage the entire reference and deformed 3D images during optimisation becomes a barrier.
Dr Fabien Leonard, University of Manchester at Harwell Data Analysis Manager, recently introduced an innovative approach to DVC known as sub-volume adaptive meshing. This revolutionary approach involves partitioning larger volumes into smaller parts that can be processed separately before being combined to provide a comprehensive result. The sub-volume adaptive meshing method has overcome the hardware limitations of previous techniques, enabling more accurate results to be obtained on larger volumes.
The process of sub-volume adaptive meshing involves dividing a large volume into smaller, more manageable sub-volumes. These sub-volumes can then be processed separately, each undergoing its own meshing process. The meshing process involves dividing the sub-volume into smaller elements or tetrahedra, which can be analysed separately. Once the global DVC process is completed on each individual subvolume, the individual results are merged back together to provide a comprehensive output that accurately tracks changes and analyses complex structural deformations.
One of the primary benefits of sub-volume adaptive meshing is its ability to provide accurate and reliable data on the deformation of 3D structures. By partitioning larger volumes into smaller sub-volumes and processing them separately, researchers can obtain more accurate results on larger volumes without the hardware limitations that were previously encountered. This innovation has gained immense popularity among researchers in materials science, who constantly strive to improve their understanding of the properties and behaviour of different materials.
A test was completed on a graphite sample to see how it holds up under pressure. The area being looked at exceeded the computation limitations. The use of sub-volume adaptive meshing overcame the hardware limitations where global DVC is required over large volumes, and meshing density can be user-defined to fit the expected damage location within the sample.
In conclusion, the sub-volume adaptive meshing technique has revolutionised the field of materials science, providing researchers with a more accurate and reliable method for studying the deformation of 3D structures. This technique has overcome the hardware limitations of previous methods, enabling researchers to obtain more precise results on larger volumes. As the field of materials science continues to evolve, it is likely that we will see further innovations such as this, which will help to deepen our understanding of the properties and behaviour of different materials.
This work was supported by the EPSRC project “Reducing Risk through Uncertainty Quantification for Past, Present and Future Generations of Nuclear Power Plants” (EP/R012423/1).
To explore the findings further read the paper (PDF file) or access the presentation.