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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory

Abstract Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗
DOE OSTI2024

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗
DOE OSTI2024

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗
DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗
NASA NTRS2004

Small Mercury Ion Clock for On-board Spacecraft Navigation

I.Small Ion Clock Approach and Heritage: a) No lasers, uwave cavities, cryogenics, atomic beams, etc. b) Ions are electrically shuttled between separate optical and microwave traps. II. Each trap is optimized for its task: quadrupole for optical state selection; multi-pole for microwave clock. a) Very good stability shown in USNO. Timescale running "open loop." III. "Open loop" operation means no self-measurements of frequency offsets: (Zeeman, ion temperature,... etc.) a) Fewer parts and procedures, produces stable output continuously. IV. Ion clock is not so sensitive to temperature fluctuations a) Measured u:nshielded temperature coefficient of few 10(exp -15) per C. b) No bulky temperature isolation needed.

Prestage, John D.↗
NASA NTRS1997

Low-leakage and low-instability labyrinth seal

Improved labyrinth seal designs are disclosed. The present invention relates to labyrinth seal systems with selected sealing surfaces and seal geometry to optimize flow deflection and produce maximum turbulent action. Optimum seal performance is generally accomplished by providing sealing surfaces and fluid cavities formed to dissipate fluid energy as a function of the geometry of the sealing surfaces along with the position and size of the fluid cavities formed between members of the labyrinth seal system. Improved convex surfaces, annular flow reversal grooves, flow deflection blocks and rough, machined surfaces cooperate to enhance the performance of the labyrinth seal systems. For some labyrinth seal systems a mid-cavity throttle and either rigid teeth or flexible spring teeth may be included.

Rhode, David L.↗
DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗
DOE OSTI2025

Near-Term Application Engineering Challenges in Emerging Superconducting Qudit Processors

We review the prospects to build quantum processors based on superconducting transmons and radiofrequency cavities for testing applications in the NISQ era. We identify engineering opportunities and challenges for implementation of algorithms in simulation, combinatorial optimization, and quantum machine learning in qudit-based quantum computers.

Venturelli, Davide [RIACS, Mtn. View] (ORCID:00000↗
NASA NTRS1975

Waveguide CO2 laser gain: Dependence on gas kinetic and discharge properties

Using a simple rate equation approach the gas kinetic and discharge properties of waveguide CO2 lasers were examined. The dependence was calculated of the population inversion and laser small signal gain on gas pressure, gas mixture, pumping rate (discharge current), tube bore diameter, and wall temperature. At higher pressures the gain is optimized by using more helium rich mixtures and smaller bore diameters. The dependence of laser tunability on the gas kinetic properties and cavity losses was determined, it was found that for loss cavities the laser tunability may substantially exceed the molecular fullwidth at half maximum. The more helium rich gas mixtures give greater tunability when cavity losses are small and less tunability when cavity losses are large. The role of the various gases in the waveguide CO2 laser is the same as that in conventional devices, by contrast with conventional lasers, the waveguide laser transition is homogeneously broadened. The dependence of gain on gas pressure and other kinetic and discharge properties differs substantially from that predicted by scaling results from conventional low pressure lasers.

Cohen, S. C.↗
NASA NTRS2014

Enabling Technologies for Entrepreneurial Opportunities in 3D printing of SmallSats

A consortium of innovative experts in additive manufacturing (AM) comprising Northrup Grumman Technical Services, University of Texas at El Paso (UTEP), Configurable Space Microsystems Innovations & Applications Center (COSMIAC), NASA Glenn Research Center (GRC), and Youngstown State University, have made significant breakthroughs in the goal of creating the first complete 3D printed small satellite. Since AM machines are relatively inexpensive, this should lead to many entrepreneurial opportunities for the small satellite community. Our technology advancements are focused on the challenges of embedding key components within the structure of the article. We have demonstrated, using advanced fused deposition modeling techniques, complex geometric shapes which optimize the spacecraft design. The UTEP Keck Center has developed a method that interrupts the printing process to insert components into specific cavities, resulting in a spacecraft that has minimal internal space allocated for what traditionally were functional purposes. This allows us to increase experiment and instrument capability by provided added volume in a confined small satellite space. Leveraging initial progress made on a NASA contract, the team investigated the potential of new materials that exploit the AM process, producing candidate compositions that exceed the capabilities of traditional materials. These "new materials" being produced and tested include some that have improved radiation shielding, increased permeability, enhanced thermal properties, better conductive properties, and increased structural performance. The team also investigated materials that were previously not possible to be made. Our testing included standard mechanical tests such as vibration, tensile, thermal cycling, and impact resistance as well as radiation and electromagnetic tests. The initial results of these products and their performance will be presented and compared with standard properties. The new materials with the highest probability to disrupt the future of small satellite systems by driving down costs will be highlighted, in conjunction with the electronic embedding process.

Communications↗
NASA NTRS1989

Development of a high power microwave thruster, with a magnetic nozzle, for space applications

This paper describes the current development of a high-power microwave electrothermal thruster (MET) concept at the NASA Lewis Research Center. Such a thruster would be employed in space for applications such as orbit raining, orbit maneuvering, station change, and possibly trans-lunar or trans-planetary propulsion of spacecraft. The MET concept employs low frequency continuous wave (CW) microwave power to create and continuously pump energy into a flowing propellant gas at relative high pressure via a plasma discharge. The propellant is heated to very high bulk temperatures while passing through the plasma discharge region and then is expanded through a throat-nozzle assembly to produce thrust, as in a conventional rocket engine. Apparatus, which is described, is being assembled at NASA Lewis to test the MET concept to CW power levels of 30 kW at a frequency of 915 MHz. The microwave energy is applied in a resonant cavity applicator and is absorbed by a plasma discharge in the flowing propellant. The ignited plasma acts as a lossy load, and with optimal tuning, energy absorption efficiencies over 95 percent (based on the applied microwave power) are expected. Nitrogen, helium, and hydrogen will be tested as propellants in the MET, at discharge chamber pressures to 10 atm.

Power, John L.↗
NASA NTRS1997

Computational Modeling in Structural Materials Processing

High temperature materials such as silicon carbide, a variety of nitrides, and ceramic matrix composites find use in aerospace, automotive, machine tool industries and in high speed civil transport applications. Chemical vapor deposition (CVD) is widely used in processing such structural materials. Variations of CVD include deposition on substrates, coating of fibers, inside cavities and on complex objects, and infiltration within preforms called chemical vapor infiltration (CVI). Our current knowledge of the process mechanisms, ability to optimize processes, and scale-up for large scale manufacturing is limited. In this regard, computational modeling of the processes is valuable since a validated model can be used as a design tool. The effort is similar to traditional chemically reacting flow modeling with emphasis on multicomponent diffusion, thermal diffusion, large sets of homogeneous reactions, and surface chemistry. In the case of CVI, models for pore infiltration are needed. In the present talk, examples of SiC nitride, and Boron deposition from the author's past work will be used to illustrate the utility of computational process modeling.

Meyyappan, Meyya↗
NASA NTRS2011

NASA Tech Briefs, July 2011

Topics covered include: 1) Collaborative Clustering for Sensor Networks; 2) Teleoperated Marsupial Mobile Sensor Platform Pair for Telepresence Insertion Into Challenging Structures; 3) Automated Verification of Spatial Resolution in Remotely Sensed Imagery; 4) Electrical Connector Mechanical Seating Sensor; 5) In Situ Aerosol Detector; 6) Multi-Parameter Aerosol Scattering Sensor; 7) MOSFET Switching Circuit Protects Shape Memory Alloy Actuators; 8) Optimized FPGA Implementation of Multi-Rate FIR Filters Through Thread Decomposition; 9) Circuit for Communication Over Power Lines; 10) High-Efficiency Ka-Band Waveguide Two-Way Asymmetric Power Combiner; 11) 10-100 Gbps Offload NIC for WAN, NLR, and Grid Computing; 12) Pulsed Laser System to Simulate Effects of Cosmic Rays in Semiconductor Devices; 13) Flight Planning in the Cloud; 14) MPS Editor; 15) Object-Oriented Multi Disciplinary Design, Analysis, and Optimization Tool; 16) Cryogenic-Compatible Winchester Connector Mount and Retaining System for Composite Tubes; 17) Development of Position-Sensitive Magnetic Calorimeters for X-Ray Astronomy; 18) Planar Rotary Piezoelectric Motor Using Ultrasonic Horns; 19) Self-Rupturing Hermetic Valve; 20) Explosive Bolt Dual-Initiated from One Side; 21) Dampers for Stationary Labyrinth Seals; 22) Two-Arm Flexible Thermal Strap; 23) Carbon Dioxide Removal via Passive Thermal Approaches; 24) Polymer Electrolyte-Based Ambient Temperature Oxygen Microsensors for Environmental Monitoring; 25) Pressure Shell Approach to Integrated Environmental Protection; 26) Image Quality Indicator for Infrared Inspections; 27) Micro-Slit Collimators for X-Ray/Gamma-Ray Imaging; 28) Scatterometer-Calibrated Stability Verification Method; 29) Test Port for Fiber-Optic-Coupled Laser Altimeter; 30) Phase Retrieval System for Assessing Diamond Turning and Optical Surface Defects; 31) Laser Oscillator Incorporating a Wedged Polarization Rotator and a Porro Prism as Cavity Mirror; 32) Generic, Extensible, Configurable Push-Pull Framework for Large-Scale Science Missions; 33) Dynamic Loads Generation for Multi-Point Vibration Excitation Problems; 34) Optimal Control via Self-Generated Stochasticity; 35) Space-Time Localization of Plasma Turbulence Using Multiple Spacecraft Radio Links; 36) Surface Contact Model for Comets and Asteroids; 37) Dust Mitigation Vehicle; 38) Optical Coating Performance for Heat Reflectors of the JWST-ISIM Electronic Component; 39) SpaceCube Demonstration Platform; 40) Aperture Mask for Unambiguous Parity Determination in Long Wavelength Imagers; 41) Spaceflight Ka-Band High-Rate Radiation-Hard Modulator; 42) Enabling Disabled Persons to Gain Access to Digital Media; 43) Cytometer on a Chip; 44) Principles, Techniques, and Applications of Tissue Microfluidics; and 45) Two-Stage Winch for Kites and Tethered Balloons or Blimps.

Source record↗
DOE OSTI2025

Investigating Low Loss Substrates for Improved Qubit Coherence Times

Superconducting qubits are sensitive to dielectric losses from substrates, making the identification, optimization, and preparation of low-loss materials essential for enhancing qubit coherence times. In this work, we utilize Nb superconducting radio-frequency (SRF) cavities as a high-precision measurement tool to study the dielectric loss tangent of substrates with parts-per-billion sensitivity. This technique enables temperature- and field-resolved measurements, providing deep insights into the behavior of candidate materials such as sapphire and silicon. We explore the impact of substrate preparation techniques, examining how surface treatments and cleaning protocols influence dielectric loss. These studies highlight both the microscopic origins of loss in these substrates and the critical role of preparation methods, helping to identify key materials and processes that minimize dielectric loss, crucial for improving qubit performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2005

Implanted Silicon Resistor Layers for Efficient Terahertz Absorption

Broadband absorption structures are an essential component of large format bolometer arrays for imaging GHz and THz radiation. We have measured electrical and optical properties of implanted silicon resistor layers designed to be suitable for these absorbers. Implanted resistors offer a low-film-stress, buried absorber that is robust to longterm aging, temperature, and subsequent metals processing. Such an absorber layer is readily integrated with superconducting integrated circuits and standard micromachining as demonstrated by the SCUBA II array built by ROE/NIST (1). We present a complete characterization of these layers, demonstrating frequency regimes in which different recipes will be suitable for absorbers. Single layer thin film coatings have been demonstrated as effective absorbers at certain wavelengths including semimetal (2,3), thin metal (4), and patterned metal films (5,6). Astronomical instrument examples include the SHARC II instrument is imaging the submillimeter band using passivated Bi semimetal films and the HAWC instrument for SOFIA, which employs ultrathin metal films to span 1-3 THz. Patterned metal films on spiderweb bolometers have also been proposed for broadband detection. In each case, the absorber structure matches the impedance of free space for optimal absorption in the detector configuration (typically 157 Ohms per square for high absorption with a single or 377 Ohms per square in a resonant cavity or quarter wave backshort). Resonant structures with -20% bandwidth coupled to bolometers are also under development; stacks of such structures may take advantage of instruments imaging over a wide band. Each technique may enable effective absorbers in imagers. However, thin films tend to age, degrade or change during further processing, can be difficult to reproduce, and often exhibit an intrinsic granularity that creates complicated frequency dependence at THz frequencies. Thick metal films are more robust but the requirement for patterning can limit their absorption at THz frequencies and their heat capacity can be high. patterned absorber structures that offer low heat capacity, absence of aging, and uniform, predictable behavior at THz frequencies. We have correlated DC electrical and THz optical measurements of a series of implanted layers and studied their frequency dependence of optical absorption from .3 to 10 THz at cryogenic temperatures. We have modeled the optical response to determine the suitability of the implanted silicon resistor as a function of resistance in the range 10 Ohms/sq to 300 Ohms/sq.

Chervenak, J. A.↗
NASA NTRS1990

Structural damping optimization via non-obstructive particle damping technique

A passive vibration damping technique that is referred to as 'Non-Obstructive Particle Damping (NOPD)' is presented. The NOPD technique consists of making small diameter holes (or cavities) at appropriate locations inside vibrating structures and filling these holes to appropriate levels with particles which yield the maximum damping effectiveness for the desired mode (or modes). Powders, spherical shaped, metallic, non-metallic or liquid particles (or mixtures) with different densities, viscosities and adhesive or cohesive characteristics can be used.

Panossian, Hagop V.↗
NASA NTRS1986

Parallel electric fields in extragalactic jets - Double layers and anomalous resistivity in symbiotic relationships

After examining the properties of Coulomb-collision resistivity, anomalous (collective) resistivity, and double layers, a hybrid anomalous-resistivity/double-layer model is introduced. In this model, beam-driven waves on both sides of a double layer provide electrostatic plasma-wave turbulence that greatly reduces the mobility of charged particles. These regions then act to hold open a density cavity within which the double layer resides. In the double layer, electrical energy is dissipated with 100 percent efficiency into high-energy particles, creating conditions optimal for the collective emission of polarized radio waves.

Borovsky, J. E.↗