If you are a component manufacturer dealing with cavitation peening and lack of volumetric data due to high speeds — this project developed a MHz rate tomoscopy prototype that provides 4D observation of processes reaching velocities up to ~km/s.
Ultra-Fast 4D X-Ray Imaging for High-Speed Industrial Process Analysis
Imagine trying to take a 3D photo of a bullet mid-flight, but the camera is too slow and only gives you a blur. This technology acts like a super-fast camera that takes multiple angles of an object at once instead of rotating it. It allows engineers to see inside solid materials during explosions or high-speed crashes in real-time.
What needed solving
Industries like aerospace and automotive cannot see inside opaque materials during ultra-fast processes, leaving them to rely on simulations and guesswork.
What was built
A prototype for MHz rate multi-projection X-ray imaging, including a portable sample setup for cavitation peening and specialized mechatronics and crystals.
Who needs this
Who can put this to work
If you are an equipment provider dealing with unpredictable laser-driven additive manufacturing dynamics — this project developed a high-brilliance X-ray imaging method that captures 3D frames at kHz or MHz rates to optimize production.
If you are a safety firm dealing with shock waves and fractures in opaque materials — this project developed a multi-projection X-ray system that visualizes fast phenomena with micron-scale resolutions.
Quick answers
What is the cost of implementing this technology?
Based on available project data, the EU contribution for development was EUR 3,154,350, but the commercial price per unit or service is not specified.
Can this be scaled for use in a standard factory?
Based on available project data, the system requires high-brilliance X-ray sources found at synchrotrons and X-ray free-electron laser sources, suggesting it is currently limited to specialized laboratory environments.
Who owns the IP and how is licensing handled?
The project is coordinated by DESY with a consortium of 9 partners; however, specific licensing terms or patent filings are not detailed in the provided data.
When will the technology be ready for industrial testing?
The prototype was installed in April, with follow-up commissioning scheduled for Autumn 2024.
How does this integrate with existing simulation software?
The project uses machine learning and modal data decomposition to analyze data, which can replace or validate current simulations and speculations regarding fast phenomena.
Who built it
The consortium is heavily research-oriented, consisting of 9 partners across 6 countries. With 5 universities and 2 research institutions, the academic weight is high, while industrial involvement is low at 11% (1 SME/Industry partner), indicating the project is currently focused on fundamental technical breakthroughs rather than immediate commercial productization.
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