Search NASA⌕ Search

Engineering topics

Powers, Tom

Publications and source records attributed to Powers, Tom.

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An OVERVIEW of MICROPHONICS in CEBAF and CURRENT MODERATION TECHNIQUES

Superconducting RF (SRF) structures are susceptible to frequency detuning from external vibrations and modal mechanical resonances in the structure. These small disturbances, known as microphonics, require additional RF power in CW accelerating structures since the frequency is constantly shifting. In the Jefferson Lab CEBAF accelerator, time and frequency data of this frequency shift have been recorded for many years, allowing a retrospective analysis of different microphonics-mitigation techniques. Some of these techniques are specific to the design of each CEBAF cryomodule, for example implementing BNNT damping material on the cavity string. Other techniques are universal such as affixing vacuum lines and reinforcing waveguide structures.

Powers, Tom↗
DOE OSTI2022

A Method for In-Situ Q₀ Measurements of High-Quality SRF Resonators

Accelerator projects such as LCLS-II naturally require low-loss superconducting (SRF) cavities. Due to strong demand for improving intrinsic quality factor (Q₀), importance of accurate cavity characterization increases. We propose a method to measure Q₀ in situ for an SRF resonator installed in its cryogenic module and connected with a RF feed source via a fixed RF coupler. The method exploits measurements of a response for an SRF resonator fed by an amplitude-modulated signal. Such a signal can be synthesized as a beat-wave composed of two frequencies that are close to the resonant frequency. Analyzing the envelope of the reflected signal, one can find the difference in reflection for the chosen frequencies and use them to compute the intrinsic Q. We also develop the methodology to carry out measurements of Q₀ at the nominal cavity operating voltage. We verified our method in experiments with a room temperature copper resonator and with two SRF resonators including Fermilab’s 650 MHz cavity and JLab’s 1500 MHz cavity.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

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 origin. This information is subsequently utilized to identify failure trends and to implement corrective measures on the offending cavity. Manual inspection of large-scale, time-series data, generated by frequent system failures is tedious and time consuming, and thereby motivates the use of machine learning (ML) to automate the task. This study extends work on a previously developed system based on traditional ML methods (Tennant and Carpenter and Powers and Shabalina Solopova and Vidyaratne and Iftekharuddin, Phys. Rev. Accel. Beams, 2020, 23, 114601), and investigates the effectiveness of deep learning approaches. The transition to a DL model is driven by the goal of developing a system with sufficiently fast inference that it could be used to predict a fault event and take actionable information before the onset (on the order of a few hundred milliseconds). Because features are learned, rather than explicitly computed, DL offers a potential advantage over traditional ML. Specifically, two seminal DL architecture types are explored: deep recurrent neural networks (RNN) and deep convolutional neural networks (CNN). We provide a detailed analysis on the performance of individual models using an RF waveform dataset built from past operational runs of CEBAF. In particular, the performance of RNN models incorporating long short-term memory (LSTM) are analyzed along with the CNN performance. Furthermore, comparing these DL models with a state-of-the-art fault ML model shows that DL architectures obtain similar performance for cavity identification, do not perform quite as well for fault classification, but provide an advantage in inference speed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

ELECTRON COOLING USING A PULSED AND DITHERING BEAM FROM AN ELECTROSTATIC ELECTRON COOLER

Electron cooling continues to be an invaluable technique to reduce and maintain the emittance in hadron storage rings such as the EIC and EICC where stochastic cooling is inefficient and radiative cooling is negligible. Extending the energy range of electron coolers beyond what is feasible with the conventional, electrostatic approach necessitates the use of RF fields for acceleration and, thus, a bunched electron beam. To experimentally investigate how the relative time structure of the two beams affects the cooling properties, we have set up a pulsed-beam cooling device by adding a synchronized pulsing circuit to the conventional electron source of the CSRm cooler at Institute of Modern Physics. Using both constant and modulated synchronization between electron pulses and ion bunches, we have measured the effects of the electron bunch length and longitudinal ion focusing strength on the temporal evolution of the longitudinal and transverse ion beam profile and demonstrated the detrimental effect of timing jitter as predicted by space-charge theory and simulations. Our experiment suggests a need for further investigations of specific aspects of bunched cooling such as synchro-betatron coupling and phase dithering effects when using short electron bunches to cool longer ion bunches. However, given the comparatively long IBS lifetime of higher-energy proton storage rings like the EIC, slow dithering could potentially provide an option to save cost on the electron cooler linac.

Wang, Haipeng↗