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International projects source: SICRIS

Recovering plasma-facing components temperatures in fusion devices from IR camera measurements

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Researchers (1)
no. Code Name and surname Research area Role Period No. of publications
1.  12725  PhD Leon Kos  Mechanical design  Head  2024  249 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  0782  University of Ljubljana, Faculty of Mechanical Engineering  Ljubljana  1627031  29,255 
Abstract
Infrared (IR) cameras are key diagnostics to monitor and control plasma-facing components (PFCs) in fusion devices. Nevertheless, the use of all-metallic PFCs with low and variable emissivity (ε ~ 0.1-0.5) makes it difficult to obtain a correct surface temperature measurement. The radiance collected by the IR camera includes both the thermal radiation emitted by the target and parasitic radiation coming from the target’s surroundings. Furthermore, target emissivity changes with the surface temperature and roughness. This causes significant errors in the surface temperature measurement that we need to address for achieving high power and safe plasma operation. Inaccurate interpretation of IR temperature measurement could endanger machine safety (temperature underestimation) or on the contrary, lead to unnecessary pulse interruptions that reduce the overall performance of the machine (temperature overestimation). The current approach is to convert the radiance collected by each pixel in an apparent using a physical relationship between emitted radiance and temperature (Planck’s law). Because a portion of the collected radiance is due to reflection on the target, a systematic error is made. This method is unable to recover the portion of reflected radiance and to deduce the correct temperature of the target using only the emitted radiance. The proposed technique in this project is to use a digital twin of the machine and to make in it assumptions on the temperatures of the different elements of the machine in order to simulate the images that would be measured under these supposed conditions. By comparing to the real image measured by the camera and using optimization techniques, the assumptions on the parameters can be updated until the simulated and measured images are close enough. It is then deduced that the assumptions made on the parameters of the digital twin are correct and that they correspond to the real temperatures in the machine.
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