Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “RF Waveform”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

RF signature detection for waveguide deformation

A radio frequency (RF) based waveguide health monitoring system is disclosed. The system employs an RF transmitter for launching a probe RF waveform into a waveguide. Reflections, etc., from the interior of the waveguide of the probe RF waveform create a signature RF waveform, with a health RF receiver receiving this resultant signature RF waveform. A health processing system analyzes the signature RF waveform, and when it detects a change indicative of a deformation of the waveguide, generates a warning signal. This change may be due to bends, flexes, vibrations (or changes in vibrations), or separations of the waveguide. The system may have low frequency, high frequency, or high frequency imaging modes. The system may employ a high-power probe RF waveform, thereby enabling a wireless charging system with power RF receivers located along the length of the waveguide providing additional functionality.

Curtis, Shane Keawe↗
DOE OSTI2023

Ammonia generation in Ns pulse and Ns pulse/RF discharges over a catalytic surface

Plasma-catalytic ammonia synthesis in a ns pulse discharge and a 'hybrid' ns pulse/RF discharge in plane-to-plane geometry is studied by Fourier Transform infrared absorption spectroscopy. The data are taken in a preheated H 2 –N 2 mixture, with and without Ni/γ-Al 2 O 3 or Co/γ-Al 2 O 3 catalyst placed in the discharge section. The measurement results are taken using two different approaches. The first is a 'single-stage' process, where a ns pulse discharge in the H 2 –N 2 mixture is sustained continuously. In this case, the ammonia yield increases slowly, over a period of tens of minutes. The second is a 'two-stage' process, where the catalyst is first activated by the ns pulse discharge sustained in pure nitrogen, and then the activated catalyst is exposed to the H 2 –N 2 flow, with or without the discharge. In this case, a strong overshoot of the NH 3 number density at the reactor exit is detected, by over a factor of two compared to the single-stage process. After the initial overshoot, the ammonia yield gradually decreases to the 'single stage' value (with the discharge on), or to near zero (with the discharge off). The results demonstrate that the ammonia yield in the plasma-catalytic reactor is controlled by the N atom accumulation on the catalyst surface, which reacts with H atoms thermally dissociated on the catalyst or generated in the plasma. The results also show that the plasma-catalytic ammonia yield is significantly higher compared to that in the ns pulse discharge without the catalyst. The accumulation of H atoms on the catalyst, with their subsequent reactions with N atoms generated in the plasma, is of relatively minor importance at the present conditions. An additional series of measurements was made with a sub-breakdown RF waveform overlapped with the ns pulse discharge train, to enhance the vibrational excitation of nitrogen. The ammonia yield measured with the RF waveform added is approximately 20% higher compared to that at the baseline ns pulse discharge conditions, both with and without the catalyst. This effect is weaker compared to that of the catalyst activation by N atoms. Additional data are necessary to isolate the possible effect of the vibrationally excited N 2 molecules on the ammonia synthesis in the plasma catalytic reactions.

surface reactions↗
DOE OSTI2018

Studies of CSR and Microbunching at Jefferson Laboratory ERLs

One attractive feature of energy recovery linacs (ERLs) is they are source limited. However as beam brightness increases so too do the effects of coherent synchrotron radiation (CSR) and the microbunching instability. The Low Energy Recirculator Facility at Jefferson Laboratory provides a test bed to characterize aspects of CSR's effect on the beam by measuring the energy extraction via CSR as a function of bunch compression. Data was recorded with acceleration occurring on the rising part of the RF waveform while the full compression point was moved along the backleg of the machine and the response of the beam measured. Acceleration was moved to the falling part of the RF waveform and the experiment repeated. Initial start-to-end simulations using a 1D CSR model show good agreement with measurements. The experiment motivated the design of a modified Continuous Electron Beam Accelerator Facility-style arc with control of CSR and the microbunching gain. Insights gained from that study informed designs for recirculation arcs in an ERL-driven electron cooler for Jefferson Laboratory's Electron Ion Collider. Progress on the design and outstanding challenges of the cooler are discussed.

Tennant, C.↗
DOE OSTI2018

Penetration of Ar and He RF-driven plasma jets into micrometer-sized capillary tubes

The penetration and propagation of cold atmospheric pressure plasmas into volumes having sub-millimeter to micrometer sizes with large aspect ratios is required for enabling an effective disinfection of the inside of catheter tubes, tooth cavities, skin pores and enhance plasma catalysis in porous catalysts. Here, we report on a study using a low voltage RF driven argon and helium plasma jets with the plasma generation outside a capillary tube with a large aspect ratio followed by its penetration and propagation inside the capillary. We present the experimental determination of the limitations on the penetration diameter, and the underpinning mechanisms of the plasma propagation and penetration process. Experimental results include time resolved imaging of plasma propagation and penetration in capillaries with different internal diameter and surface electric field measurements. We found that the time between the plasma jet in first contact with the capillary tube surface and the subsequent penetration into the capillary tube spans several RF cycles due to electric fields at the plasma-tube interface below 4 kV cm –1 . These low electric fields require Penning ionization and/or stepwise ionization and hence a buildup of the metastable and electron density is required to achieve a sufficiently large ionization rate near the capillary tube inlet to enable penetration and propagation. Furthermore, it is found that the propagation of the argon jet into the capillary occurs during the positive half cycle of the RF waveform and is very similar to the propagation of the jet in surrounding air.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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 OSTI2019

INL WTB Overview Capabilities Future v14_040419

INL Wireless Test Bed Mission Provide highly-regarded cellular, wireless and communications technical expertise, systems and environment to enable: Test & Demonstrate full scale wireless systems and equipment With and without controlled interference Terrestrial, Subterranean and Airborne Demonstrate new & emerging wireless technologies Develop and Train to Tactics, Techniques and Procedures (TTPs) for wireless systems In a real world environment and configurations at real frequencies and real power levels to make informed decision State-of-the-Art INL WTB Assets and Capabilities Instrumentation: RF waveform analyzers, generators Protocol analyzers Noise generators for controlled interference Established Services & Processes: Spectrum approval & monitoring Safety, Medical, Fire, Security (physical) Resource management - personnel, networks, configuration control Secure, IP protected multi-user facility Broadband data access – entire INL Range Hardware prototyping, scientific labs Visitor – US citizen & foreign national

2G↗
DOE OSTI2023

Multiple frequency electron cyclotron resonance thruster

An electron cyclotron resonance (ECR) thruster includes a magnetic field source configured to generate a magnetic field, a thruster body that defines a chamber, the thruster body being disposed relative to the magnetic field source such that the magnetic field is present in the chamber and such that a magnetic nozzle is established, an antenna configured to propagate radio frequency (RF) power within the chamber, and a waveform generator coupled to the antenna to generate an RF waveform for the RF power. The waveform generator is configured such that the RF waveform includes multiple frequencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Machine Learning Based Cavity Fault Classification and Prediction

We report on the development of machine learning models for classifying C100 superconducting radio frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through 5-passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level RF system configured such that a cavity fault triggers waveform recordings of 17 RF signals for each of the eight cavities in the cryomodule. Subject matter experts (SME) can analyze the collected time-series data, identify which of the eight cavities faulted first, and classify the type of fault. This information is used to find trends and strategically deploy mitigations to problematic cryomodules. However, manually labeling the data is laborious and time-consuming. By leveraging machine learning, near real-time – rather than post-mortem – identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the ML models during a recent physics run.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Effect of net direct current on the properties of radio frequency sheaths: simulation and cross-code comparison

In order to understand, predict and control ion cyclotron range of frequency (ICRF) interactions with tokamak scrape-off layer plasmas, computational tools which can model radio frequency (RF) sheaths are needed. In particular, models for the effective surface impedance and DC rectified sheath potentials may be coupled with full wave RF simulation codes to predict self-consistent wave fields near surfaces and the resulting power dissipation and plasma-material interactions from ion sputtering. In this study, previous work assuming zero net DC current flow through the sheath is generalized to allow the surface to collect net positive or negative current, as is often observed in experiments. The waveforms, DC potential and RF admittance are investigated by means of analytical theory, nonlinear fluid and particle-in-cell (PIC) codes. Cross-code comparisons provide detailed model verification and elucidate the roles of ion and electron kinetics. When the sheath draws negative (positive) DC current, the voltage rectification is reduced (increased) compared with the zero-current case, and the magnitude of both the real and imaginary parts of the admittance are increased (reduced). In conclusion, a previous four-input parametrization of the sheath rectification and admittance properties is generalized to include a fifth parameter describing the DC sheath current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

CEBAF C100 Fault Classification based on Time Domain RF Signals

The CEBAF 12 GeV upgrade project, which was completed and commissioned in 2014, included the construction and installation of 80 new 7-cell superconducting cavities that were configured in 10 cryomodules. In 2018, the software and hardware in the digital low level RF systems were configured such that a fault would trigger an acquisition process which records waveform records of 17 of the RF signals for each of the 8 cavities within the cryomodule for subsequent analysis. These waveforms are especially useful in C100 cryomodules as there is a 10% mechanical coupling between adjacent cavities. When one cavity has a fault and the gradient is reduced quickly, it will mechanically deform due relaxation of the Lorentz force effects. This deformation change causes perturbations in the adjacent cavities which, in turn, causes a cascade of cavity faults that are difficult to understand without the time domain data. This contribution will describe the types of faults encountered during operation and their signatures in the time domain data, as well as how is being used to modify the setup of the machine and implement improvements to the cryomodules.

Powers, T.↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
DOE OSTI2025

High-power test of a C-band linear accelerating structure with an RFSoC-based LLRF system

Normal conducting linear particle accelerators consist of multiple rf stations with accelerating structure cavities. Low-level rf (LLRF) systems are employed to set the phase and amplitude of the field in the accelerating structure and to compensate for the pulse-to-pulse fluctuation of the rf field in the accelerating structures with a feedback loop. The LLRF systems are typically implemented with analog rf mixers, heterodyne-based architectures, and discrete data converters. There are multiple rf signals from each of the rf stations, so the number of rf channels required increases rapidly with multiple rf stations. With a large number of rf channels, the footprint, component cost, and system complexity of the LLRF hardware will increase significantly. To meet the design goals of being compact and affordable for future accelerators, we have designed the next-generation LLRF (NG-LLRF) with a higher integration level based on RFSoC technology. The NG-LLRF system samples rf signals directly and performs rf mixing digitally. Further, the NG-LLRF has been characterized in loopback mode to evaluate the performance of the system and has also been tested with a standing-wave accelerating structure, a prototype for the Cool Copper Collider (C 3 ) with a peak rf power level up to 16.45 MW. The loopback test demonstrated amplitude fluctuation below 0.15% and phase fluctuation below 0.15°, which are considerably better than the requirements of C 3 . The rf signals from the different stages of the accelerating structure at different power levels are measured by the NG-LLRF, which will be critical references for the control algorithm designs. The NG-LLRF also offers flexibility in waveform modulation, so we have used rf pulses with various modulation schemes, which could be useful for controlling some of the rf stations in accelerators. In this paper, the high-power test results at different stages of the test setup will be summarized, analyzed, and discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

2020 Review of Axis 2 rf

An intense relativistic electron beam can produce radiofrequency (rf) radiation in many ways. The DARHT II linear induction accelerator produces a 17 MeV, 1.65 kA beam. The dominant sources of rf at DARHT-II and the methods used to suppress this rf are well documented. This note will examine the observed rf over the past six years and its impact on the beam. The recorded waveforms for each hydro starting with 4011 from 10/29/14 are examined to identify the presence of rf. The hydros are chosen because they represent the optimal accelerator performance at any given time rather than tuning or beam studies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Bi-triaxial photoconductive switch module

Methods, systems, and devices describe bi-triaxial photoconductive switch modules that that eliminate the need for external DC blocking capacitors, while providing a highly compact structure that can produce bipolar output waveforms conducive to feeding to radio-frequency (RF) devices, such as antennas. Some implementations of the disclosed bi-triaxial photoconductive switch modules utilize unified cast-in-place capacitors that can be designed with an appropriate geometry, volume and orientation to provide desired energy storage capacity while eliminating or reducing parasitics.

42 ENGINEERING↗
DOE OSTI2025

Two-frequency RF fields induced multipactor in coaxial transmission lines

This study presents a comprehensive investigation of two-surface multipactor discharge in coaxial transmission lines under two-frequency radio frequency (RF) excitation using one-dimensional Monte Carlo simulations validated against three-dimensional particle-in-cell simulations and experimental data. The results show that introducing a second carrier mode can suppress multipactor by reshaping and shrinking the susceptibility region, with the extent and location of suppression strongly dependent on the device's aspect ratio and the relative phase of the second carrier mode. Distinct suppression patterns are observed across different fd regimes, while in some cases, susceptibility expansion also occurs under two-frequency operation. A key outcome is the identification and delineation of pure and mixed multipactor modes in coaxial geometry, where analytical mode boundaries are not readily available. Unlike planar geometries, pure-mode regions in coaxial systems overlap with mixed-mode domains, complicating mode identification. Additionally, image charge forces are found to have negligible influence on susceptibility thresholds but strongly affect electron growth rates. These findings offer valuable insights into the use of waveform engineering for controlling multipactor in high-power RF systems.

43 PARTICLE ACCELERATORS↗