Description
Non-destructive testing (NDT) plays an essential role in the analysis, visualization, and optimization of complex component and heterogeneous material systems (e.g., fiber composites). It is thus the key for discovering new materials and for producing novel highly integrated and lightweight components in a cost-effective way. Thes high-tech materials and components are needed in a wide range of sectors such as health care, leisure, automotive, or aeronautics and rely on detailed inspections. The required data for respective analyses are generated using imaging techniques such as X-ray computed tomography (XCT) and provide 2D images, volumetric models and derived quantitative data in high-dimensional data spaces. For XCT we call such ensembles of data “rich XCT data”. Such rich XCT data can rarely or only to a limited extent be analyzed on desktop monitors using standard 2D visualization techniques alone. With the emergence of Immersive Analytics, especially Virtual Reality (VR), new interaction and visualization techniques have been introduced, which offer an enhanced understanding of highly complex internal structures.
Tasks
In this project, we want to investigate immersive interaction and visualization techniques and advance our prototype (see also image) with techniques that enable an exploration of the primary XCT data as well as secondary data extracted from XCT scans together with domain specialists. The developed methods should help domain experts in the analysis of such fiber-reinforced polymers (FRPs) materials, which can consist of several hundreds of thousands of objects (i.e., fibers and pores), each having more than twenty different extracted features (i.e., length, diameter, …). The developed techniques will integrated as a module in our software open_iA and made available open source for the scientific community.
Requirements
- Interest and knowledge in (immersive) visualization
- Experience of VR concepts is advantageous
- Good programming skills in C++, Qt, VTK
- Creativity and enthusiasm.