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NTT and ITER to collaborate on early anomaly prediction
Global technology solutions provider NTT Corporation (Japan) and the ITER Organization are planning joint experiments on predicting anomalies in ITER plant facilities. The early detection of anomalies and failures can reduce equipment downtime and increase the efficiency of the ITER Tokamak's operational phases.
NTT's artificial-intelligence (AI) powered anomaly prediction technology "DeAnoS" (for Deep Anomaly Surveillance) will be used to understand the normal status of selected ITER plant equipment, to detect faults, and to predict anomalies. The ITER Organization has already provided some operational data from the cooling water system to set up this ambitious collaboration, and will scale up with data from other equipment in the years ahead.
These experiments result from a Cooperation Agreement signed with NTT in 2020.
At the Korea Institute of Fusion Energy (KFE), the KSTAR tokamak recommenced operations in December after a major upgrade to replace the…
KSTAR aims for longer plasmas
At the Korea Institute of Fusion Energy (KFE), the KSTAR tokamak recommenced operations in December after a major upgrade to replace the device's carbon divertor with a tungsten divertor.
According to an article on the KFE website, the original carbon divertors could take a thermal load of 5MW/m², whereas the tungsten divertor can take 10MW/m². The upgrade is critical to the goal of sustaining a 100-million-degree plasma for 300 seconds by 2026. Data from the operational campaign will be directly relevant to ITER, which will operate a tungsten divertor under similar plasma conditions in terms of shape and structure.
This testing campaign will continue through February 2024. Read more about the plans in this article in English on the KFE website, or in Korean in the Chosun Biz.