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Experimental study demonstrates real-time computer-vision control of jet-breakup pebble fabrication, suggesting enhanced scalability of breeding blankets for fusion reactors.
To meet the stringent dimensional tolerances required for lithium-enriched ceramic granules, the Karlsruhe Institute of Technology (KIT) has devised the KALOS (KArlsruhe Lithium OrthoSilicate) technique, in which a steady molten jet is deliberately destabilised by an adjustable excitation frequency. Lithium-enriched ceramic granules are a cornerstone for the tritium-breeding blankets that will be employed in future fusion power plants, and their quality hinges on precise control of the jet-breakup process. In this work we present a novel high-speed camera-based measurement and control platform that automatically monitors and regulates pebble production. Image-processing algorithms extract droplet size, position, and inter-droplet distance distributions in real time. For this purpose, both classical image-processing methods and deep neural networks are investigated. Experimental results demonstrate that the system delivers accurate measurements and reliably adjusts the driving frequency to maintain target pebble dimensions. Thus, the proposed computer-vision system enables closed-loop control of the KALOS process, paving the way for robust, large-scale ceramic pebble fabrication.
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Vogelbacher et al. (2026) studied this question.
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