Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems
18th International Conference on Accelerator and Large Experimental Physics Control Systems, Shanghai, China, 14-22 October 2021
Field emission control, mitigation, and reduction is critical for reliable operation of high gradient superconducting radio-frequency (SRF) accelerators. With the SRF cavities at high gradients, the field emission of electrons from cavity walls can occur and will impact the operational gradient, radiological environment via activated components, and reliability of CEBAF’s two linacs. A new effort has started to minimize field emission in the CEBAF linacs by re-distributing cavity gradients. To measure radiation levels, newly designed neutron and gamma radiation dose rate monitors have been installed in both linacs. Artificial intelligence (AI) techniques will be used to identify cavities with high levels of field emission based on control system data such as radiation levels, cryogenic readbacks, and vacuum loads. The gradients on the most offending cavities will be reduced and compensated for by increasing the gradients on least offensive cavities. Training data will be collected during this year’s operational program and initial implementation of AI models will be deployed. Preliminary results and future plans are presented.
Original Publication Citation
Carpenter, A., Degtiarenko, P., Suleiman, R., Tennant, C., Turner, D. L., Vidyaratne, L., Iftekharuddin, K., & Rahman Md, M. (2021). Using AI for management of field emission in SRF linacs. In K. Furukawa, Y. Yan, Y. Leng, & Z. Chen (Eds.), Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems. (pp. 970-974). JACoW Publishing. https://doi.org/10.18429/JACoW-ICALEPCS2021-THPV043
Carpenter, A.; Degtiarenko, P.; Suleiman, R.; Tennant, C.; Turner, D.; Vidyaratne, L. S.; Iftekharuddin, Khan; and Rahman, Md. Monibor, "Using AI for Management of Field Emission in SRF Linacs" (2021). Electrical & Computer Engineering Faculty Publications. 317.