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2022

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Articles 61 - 64 of 64

Full-Text Articles in Physics

Grand Challenges In Low Temperature Plasmas, Xinpei Lu, Peter J. Bruggeman, Stephan Reuter, George Naidis, Annemie Bogaerts, Mounir Laroussi, Michael Keidar, Eric Robert, Jean-Michel Pouvesle, Dawei Liu, Kostya (Ken) Ostrikov Jan 2022

Grand Challenges In Low Temperature Plasmas, Xinpei Lu, Peter J. Bruggeman, Stephan Reuter, George Naidis, Annemie Bogaerts, Mounir Laroussi, Michael Keidar, Eric Robert, Jean-Michel Pouvesle, Dawei Liu, Kostya (Ken) Ostrikov

Electrical & Computer Engineering Faculty Publications

Low temperature plasmas (LTPs) enable to create a highly reactive environment at near ambient temperatures due to the energetic electrons with typical kinetic energies in the range of 1 to 10 eV (1 eV = 11600K), which are being used in applications ranging from plasma etching of electronic chips and additive manufacturing to plasma-assisted combustion. LTPs are at the core of many advanced technologies. Without LTPs, many of the conveniences of modern society would simply not exist. New applications of LTPs are continuously being proposed. Researchers are facing many grand challenges before these new applications can be translated to practice. …


Real-Time Cavity Fault Prediction In Cebaf Using Deep Learning, Md. M. Rahman, K. Iftekharuddin, A. Carptenter, T. Mcguckin, C. Tennant, L. Vidyaratne, Sandra Biedron (Ed.), Evgenya Simakov (Ed.), Stephen Milton (Ed.), Petr M. Anisimov (Ed.), Volker R.W. Schaa (Ed.) Jan 2022

Real-Time Cavity Fault Prediction In Cebaf Using Deep Learning, Md. M. Rahman, K. Iftekharuddin, A. Carptenter, T. Mcguckin, C. Tennant, L. Vidyaratne, Sandra Biedron (Ed.), Evgenya Simakov (Ed.), Stephen Milton (Ed.), Petr M. Anisimov (Ed.), Volker R.W. Schaa (Ed.)

Electrical & Computer Engineering Faculty Publications

Data-driven prediction of future faults is a major research area for many industrial applications. In this work, we present a new procedure of real-time fault prediction for superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF) using deep learning. CEBAF has been afflicted by frequent downtime caused by SRF cavity faults. We perform fault prediction using pre-fault RF signals from C100-type cryomodules. Using the pre-fault signal information, the new algorithm predicts the type of cavity fault before the actual onset. The early prediction may enable potential mitigation strategies to prevent the fault. In our work, we apply …


Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina Jan 2022

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina

Electrical & Computer Engineering Faculty Publications

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of …


Nb₃Sn Coating Of A 2.6 Ghz Srf Cavity By Sputter Deposition Technique, M. S. Shakel, Wei Cao, H. Elsayed-Ali, G. V. Eremeev, U. Pudasaini, A. M. Valente-Feliciano Jan 2022

Nb₃Sn Coating Of A 2.6 Ghz Srf Cavity By Sputter Deposition Technique, M. S. Shakel, Wei Cao, H. Elsayed-Ali, G. V. Eremeev, U. Pudasaini, A. M. Valente-Feliciano

Electrical & Computer Engineering Faculty Publications

Nb₃Sn is of interest as a coating for SRF cavities due to its higher transition temperature Tc ~18.3 K and superheating field Hsh ~400 mT, both are twice that of Nb. Nb₃Sn coated cavities can achieve high-quality factors at 4 K and can replace the bulk Nb cavities operated at 2 K. A cylindrical magnetron sputtering system was built, commissioned, and used to deposit Nb₃Sn on the inner surface of a 2.6 GHz single-cell Nb cavity. With two identical cylindrical magnetrons, this system can coat a cavity with high symmetry and uniform thickness. Using Nb-Sn multilayer sequential sputtering followed by …