In situ experiments and Digital Volume Correlation

General course information

Digital Volume Correlation (DVC) is a powerful experimental technique that computes 3D full-field displacement and strain maps from volumes images acquired during a deformation process of a material. DVC is the 3D extension of Digital Image Correlation (DIC) which was first described four decades ago. The emergence of DVC started early 2000s with the use of X-ray CT combined with in situ rigs to capture 3D morphological changes with time. Although the DVC algorithms are in spirit similar to DIC algorithms, DVC requires special attention and expertise from multiple fields (3D imaging, in situ testing, CT reconstruction, mechanics of materials, etc.) as the texture is not controlled (natural contrast brought by imaging) and the noise/CT artefacts are often dominating the accuracy/precision of the measurements. Adding the 4th dimension (3D + time) also means  that data processing and visualization are key to extract the mechanical information hidden inside the 4D datasets.

Organisation 

The training is organised in two parts: theory (0.5 day) and computer-based practical works (1.5 day) using the XDigitalVolumeCorrelation extension in the Thermo Scientific™ Amira-Avizo Software 3D where two solutions are implemented (a classic subset based approach and a more robust global approach). At the end of the second day, the users are invited to practise on their own dataset with the help of the trainers. The attendees are invited to bring their own laptop (an Avizo license will be provided for the training).

Who should attend?

Researchers working in the field of mechanics, physics, and materials science using 3D imaging techniques such as X-ray computed tomography who are interested to (i) compute 3D full-field displacements and strains for linking the microstructure to the mechanical/physical behaviour, (ii) use the DVC measured data to feed/validate finite element models. The attendees are requested to bring their own laptop to practise on the XDigitalVolumeCorrelation extension (free trial licence will be provided).

Learning outcomes

  • History of DVC

  •  Local and global approaches of DVC

  • DVC technical terms

  • Autocorrelation, subset/element size, sought displacement

  • Small strain and large strain formulation

  • How to approach a DVC problem 

  • How to generate a mesh for DVC

  • Practical works:

    • Learn about the texture​

    • Measure displacement and strain uncertainties

    • Methods for running a DVC analysis with rigid body motion: coarse registration, initial guess

    • DVC automation and post -DVC analysis of a time series 

    • Exploit the correlation residuals for damage investigation (cracks detection)

    • Exploit the correlation residuals to correct the time series by the displacement field

  • Extra demos:

    • Dialog between DVC and FE simulations

    • How to run a DVC analysis of large datasets