The 3rd VOLDA Workshop will focus on advanced visualisation methodologies for fusion experiments and simulation, with AI and data-driven techniques as enabling components. The programme builds on practical experience from UKAEA, ITER, US laboratories and emerging digital engineering initiatives.
Advanced Visualisation for Fusion Experiments and Simulation
This topic explores scalable visualisation of experimental and simulation data across present and future fusion devices.
- Visualisation of large 3D plasma simulation datasets
- Integration of CAD, equilibrium reconstruction and diagnostic data
- Rendering sparse volumes, field-line structures and particle data
- Interactive exploration of magnetic topology and transport phenomena
- GPU-accelerated rendering pipelines
- Omniverse-based digital twin environments
- OpenUSD workflows for multi-disciplinary engineering integration
- Integration of ParaView/VTK outputs into immersive environments
- XR-based engineering visualisation and control-room applications
- Story-driven visual communication of complex plasma behaviour
Emphasis should be placed on performance, scalability, interoperability and real operational use.
Digital Twins and Engineering Integration
This topic focuses on the visual and structural integration of experiment, simulation and engineering systems.
- Tokamak digital twin frameworks
- Integration of structural, thermal and neutronics models
- Multi-physics visualisation pipelines
- Real-time data overlays on engineering models
- Cross-device digital twin comparison
- Digital engineering workflows supporting future programmes such as STEP and DEMO
- Collaborative visual environments for distributed teams
Contributions highlighting practical deployment challenges are particularly welcome.
Data-Driven Methods and AI-Enabled Workflows
AI and machine learning increasingly support visualisation, control and analysis in fusion environments.
- Surrogate models supporting near-real-time visual feedback
- Data-driven disruption prediction and visual analytics
- Physics-informed machine learning integrated into visual environments
- Automated feature detection within large diagnostic datasets
- Smart data retrieval based on physics events
- Integration of AI inference within digital twin environments
Submissions should focus on applied workflows and validated deployment rather than purely theoretical approaches.
Big Data Infrastructure and Scalable Pipelines
Modern fusion experiments generate large, complex datasets that require robust infrastructure.
- Scalable data pipelines linking HPC simulation and visual platforms
- Efficient storage and retrieval of high-resolution diagnostic data
- Containerised and reproducible visualisation workflows
- Multi-device data federation and benchmarking
- Secure cross-site collaboration frameworks
The 3rd VOLDA Workshop continues the tradition of focusing on practical experience, lessons learned and collaborative innovation in visualising offline and live fusion data.
