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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.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Characteristics of auroral electron acceleration regions observed by Atmosphere Explorer C

Satellite measurements of electron precipitation and ion drift velocities showed that electron acceleration regions (or inverted V's) in the 1200 to 1800 MLT quadrant exhibit the following systematic behavior: electron distribution functions in the accelerated region can be well described by Maxwellian primary electron beams accelerated through an electrostatic potential; the typical inverted V latitudinal structure is always observed in the accelerated regions, the electrostatic potential reaching a maximum and consequently decreasing to near zero over distances of 100 to 250 km; the Maxwellian temperature of the primary electron beam increases systematically with increasing electrostatic potential; rather weak acceleration regions, characterized by values of the electrostatic potential below 1 keV and values of the Maxwellian temperature between 100 and 350 eV, occur in the cusp and in the highest-latitude portion of the dusk side electron precipitation zone.

Burch, J. L.↗
DOE OSTI2021

2D Simulations of Diamagnetic Loop Calibrations

Diamagnetic loops can be used as a non-invasive method for measurements of beam size in electron beam accelerators that use solenoidal magnetic transport. A comprehensive theory for interpreting data from a diamagnetic loop relates the rms beam radius to the excluded flux measured by the loop and the beam current. Thus, primary calibration of the loop must relate the loop signal directly to the exclude d flux. We have simulated these calibrations with a 2D field solver in order to identify possible sources of uncertainty in our calibration technique.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Optimization of a buncher for High Energy H- Beam Transport [Slides]

Accelerators and beam transport systems typically contain numerous beamline devices, diagnostics, system study, and upgrade. Routinely TRACE, MADX and TRANSPORT codes are used for the beam envelope prediction and optimization. Unknown problems of accelerators and beam-transport are addressed based on R&D, such as LFB voltage variation effect study. A nominal diagnostic have used in non-traditional beam transport path to address scientific question (such as use of a BPM in the air). High energy beam operation is a methodical process and routine R&D is required to maintain high standards to deliver beam.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Polarized electron injector for positron production at CEBAF

As a part of the effort to expand the capabilities of CE-BAF 12 GeV (Continuous Electron Beam Accelerator Facility) at Jefferson Lab, the addition of a polarized positron source is considered. This capability would provide acceleration of high duty-cycle polarized posi-trons, with spin >60% polarization, through the same main CEBAF accelerator machine with appropriate mag-net field reversals and linac phasing to the four CEBAF experimental halls. To produce this positron beam, a high average current (3-10 mA) highly polarized electron beam with energy of 100 ? 150 MeV is required at the positron source target. The focus of this paper is the de-sign of that polarized electron beam injector. We will describe the production and delivery of a >3 mA highly polarized electron beam. We will discuss different aspects of the design, the photocathode gun, beam dynamics simulation results, spin manipulation, bunching and accelerating process and final electron beam parameters.

Kazimi, R.↗
NASA NTRS2016

Single-Event Effect Testing of the Linear Technology LTC6103HMS8#PBF Current Sense Amplifier

The LTC6103HMS8#PBF (henceforth abbreviated as LTC6103) current sense amplifier from Linear Technology was tested for both destructive and non-destructive single-event effects (SEE) using the heavy-ion cyclotron accelerator beam at Lawrence Berkeley National Laboratory (LBNL) Berkeley Accelerator Effects (BASE) facility. During testing, the input voltages and output currents were monitored to detect single event latch-up (SEL) and single-event transients (SETs).

single-event effects (SEE)↗
DOE OSTI2026

Transport of 12 GeV positron beams at Ce+BAF

Jefferson Lab (JLab) is developing a concept to upgrade the Continuous Electron Beam Accelerator Facility (CEBAF) to additionally deliver spin-polarized continuous-wave positron beams for its nuclear physics program users (Ce+BAF 12 GeV). The concept involves repurposing the Low Energy Recirculator Facility (LERF) at JLab as a dual injector, first producing 100-300 MeV spin-polarized electron beams which are subsequently used for the generation and formation of 123 MeV continuous-wave positron beams. The positron beams are transported to CEBAF and injected for acceleration up to 12 GeV, tailored to the requirements of its four experimental halls. Given the higher emittance of the secondary positron beams, the CEBAF optics are optimized for low dispersion and low beta functions to enhance transmission within the Ce+BAF acceptance limits and with an R56 to manage the positron beams bunch length and energy spread. Potential bottlenecks are being investigated through both optical modeling and measurements using an electron beam, as well as degraded electron beams, to map the 6d acceptance of CEBAF as it is today. This presentation shares preliminary results from multi-particle tracking simulations of the positron beam up to 12 GeV, including spatial, momentum, and spin characteristics, and explores the feasibility of delivering beams simultaneously to multiple experimental halls via extraction optics.

Accelerator Physics↗
DOE OSTI2024

MEMS RF accelerators for nuclear energy and advanced manufacturing

Energetic ions are widely used to develop radiation hard structural materials and fuels for advanced nuclear energy. Ion beams are also used to generate neutrons for nuclear materials testing, as well as in a series of high impact, high value adding manufacturing processes (ranging from doping of semiconductors to hardening of materials against wear and to increase bio-compatibility of materials). But to date, high power beams of high energy ions are simply too expensive because they are delivered from large single beam accelerators. We have recently demonstrated that MEMS technology enables massively parallel, low cost batch fabrication of ion beams. We propose to scale intense ion accelerators based on MEMS (micro-electro mechanical systems) to high beam power (>10 kW). With our approach, hundreds to thousands of ion beamlets will be densely packed on silicon wafers. Ions are injected and accelerated across gaps formed in stacks of wafers, leading to uniquely high current densities for intense ion accelerators with variable kinetic energy (0.1 to 10 MeV) and variable ion species. Our team brings together experts in high power ion accelerators from Lawrence Berkeley National Laboratory and leading experts in MEMS technology from Cornell University. We will deliver a disruptive technology of low cost, flexible and massively scalable ion accelerators that will enable the rapid development of radiation hard nuclear materials for advanced nuclear energy and enable new applications in manufacturing.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators

Abstract Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-objective optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithms (GAs), have been leveraged for many optimization problems, however, they do not apply to complex control problems by design. This paper demonstrates the power of differentiability for solving MOO problems in particle accelerators using a deep differentiable reinforcement learning (DDRL) algorithm. We compare the DDRL algorithm with model-free reinforcement learning (MFRL), GA, and Bayesian optimization (BO) for simultaneous optimization of heat load and trip rates in the continuous electron beam accelerator facility. The underlying problem enforces strict constraints on both individual states and actions as well as cumulative (global) constraints on energy requirements of the beam. Using historical accelerator data, we develop a physics-based surrogate model which is differentiable and allows for back-propagation of gradients. The results are evaluated in the form of a Pareto-front with two objectives. We show that the DDRL outperforms MFRL, BO, and GA on high dimensional problems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

An Electron-Beam Ion-Neutralization Diagnostic for the Scorpius Radiography Accelerator

Electron beam spilling onto the beam pipe can produce positive ions that are accelerated inward into the beam body by its space charge. These ions partially neutralize the space charge, thereby causing the beam to be mismatched to the magnetic fields used for transport. A diagnostic of neutralization effects has been used on present accelerators, and in this note the feasibility of its use on a future accelerator is assessed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

High precision 5 MeV Mott polarimeter

We report on the design and performance of a Mott polarimeter optimized for a nominal 5-MeV electron beam from the Continuous Electron Beam Accelerator Facility (CEBAF) injector. The rf time structure of this beam allows the use of time of flight in the scattered electron detection, making it possible to cleanly isolate those detected electrons that originate from the scattering foil, and resulting in measured scattering asymmetries which are exceptionally stable over a broad range of beam conditions, beam currents, and foil thicknesses. In two separate series of measurements from two different photocathode electron sources, we have measured the Mott scattering asymmetries produced by an approximately 86% transversely polarized electron beam incident on ten gold foils with nominal thicknesses between 50 and 1000 nm. The statistical uncertainty of the measured asymmetry from each foil is below 0.25%. Within this statistical precision, the measured asymmetry was unaffected by ±1-mm shifts in the beam position on the target foil, and by beam current changes and dead-time effects over a wide range of beam currents. The overall uncertainty of our beam polarization measurement, arising from the uncertainty in the value of the scattering asymmetry at zero foil thickness as determined from our fits to the measured asymmetries versus scattering foil thicknesses, the estimated systematic effects, and the (dominant) uncertainty from the calculation of the theoretical Sherman function, is 0.61%. A simulation of the polarimeter using geant4 has confirmed that double scattering in the target foil is the sole source of the dependence of the measured asymmetry on foil thickness, and gives a result for the asymmetry versus foil thickness in good agreement with both our measurements and a simple calculation. Future measurements at different beam energies and with target foils of different atomic numbers will seek to bound uncertainties from small effects such as radiative corrections to the calculation of the polarimeter analyzing power. A simultaneous high-precision measurement of the beam polarization with a different polarimeter, AESOP (Accurate Electron Spin Optical Polarimeter), under development at the University of Nebraska, clearly possible at the CEBAF accelerator, will allow a high-precision comparison of our measured asymmetries with theoretical calculations of the Mott analyzing power. Finally, the improved precision of the current Mott polarimeter along with similar improvements to other Jefferson Lab polarimeters warrants another precision comparison of all of these polarimeters when measuring a beam of the same polarization.

Grames, J. M. (ORCID:0000000193908752)↗
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

SRF cavity instability detection with machine learning at CEBAF

During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detectfast transient instabilities during these trip events. These challenges make the identification of an unstable cavity out of the hundreds installed at CEBAF a difficult and time-consuming task. To tackle these issues, a fast data acquisition system (DAQ) for the legacy SRF cavities has been developed, which records the sample at 5 kHz. An unsupervised learning framework has been developed to identify anomalous SRF cavity behavior. We will discuss the present status of the DAQ system and our framework, along with recent successes in detecting anomalous cavity behavior. Overall, our method offers a practical solution for identifying unstable SRF cavities, contributing to increased beam availability and machine reliability.

Accelerator Physics↗
DOE OSTI2024

Neutrino Program at Fermilab -- Enhancing proton beam power and accelerator infrastructure

The upcoming long baseline neutrino experiments aim to enhance proton beam power to multi-MW scale and utilize large-scale detectors to address the challenge of limited event statistics. The DUNE experiment at LBNF will test the three neutrino flavor paradigm and directly search for CP violation by studying oscillation signatures in the high intensity $\nu_{\mu}$ (anti-$\nu_{\mu}$) beam to $\nu_{e}$ (anti-$\nu_{e}$) measured over a long baseline. Higher beam power and improved accelerator up-time will enhance neutrino flux for the neutrino program by increasing the number of protons on target. LBNF/DUNE, as well as PIP-II upgrade and Accelerator Complex Evolution (ACE) plan, play a vital role in this effort. The scientific potential of ACE plan extends beyond neutrino physics, encompassing endeavors such as the Muon Collider, Charged Lepton Flavor Violation (CLFV), Dark Sectors, and exploration of neutrinos beyond DUNE.\par In the era of higher-power accelerator operation , research in target materials and beam instrumentation is crucial for optimizing design modifications. This abstract discusses Fermilab ACE, the science opportunities it provides, and how Fermilab is pushing the limits of proton beam power and accelerator infrastructure. By tackling neutrino beam challenges and exploring research and development ideas, we are advancing our understanding of fundamental particles and their interactions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗
DOE OSTI2021

HIGH VOLTAGE DESIGN AND EVALUATION OF WIEN FILTERS FOR THE CEBAF 200 keV INJECTOR UPGRADE

High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require highly spin-polarization electron beams, produced from strained super-lattice GaAs photocathodes, activated to negative electron affinity in a photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector defines the orientation of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming MOLLER experiment requires increasing the electron beam energy to 200 keV, to reduce unwanted helicity correlated intensity and position systematics and provide precise control of the polarization orientation. Our contribution describes design, fabrication and testing of the high voltage system to upgrade the Wien spin rotator to be compatible with the 200 keV beam. This required Solidworks modeling, CST and Opera electro- and magnetostatic simulations, upgrading HV vacuum feedthroughs, and assembly techniques for improving electrode alignment. The electric and magnetic fields required by the Wien condition and the successful HV characterization under vacuum conditions are also presented.

Palacios-Serrano, G.↗
DOE OSTI2021

Electrostatic Design and Characterization of a 200 keV Photogun and Wien Spin Rotator

High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require high spin-polarization electron beams produced from strained super-lattice GaAs photocathodes activated to negative electron affinity in a high voltage photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector provides precise control of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming Moller experiment requires increasing the electron beam energy to 200 keV, resulting in better transmission through injector apertures and improved photocathode lifetime. In addition, the energy increase is expected to reduce unwanted helicity correlated intensity and position systematics. These requirements led to the design of a shielding electrode described in this work, which minimizes the electric field at the triple-point junction and linearizes the potential along the insulator, thus reducing the risk of field emission induced insulator arcing. The Wien spin rotator design was modified for increasing the electric field from 1.6 to 2.7 MV/m and the magnetic field from 9.1 to 13 mT. The upgrades required detailed modeling in Solidworks, electrostatic simulations using CST, beam dynamics using GPT, device implementation, and in situ high voltage characterization of the world?s first 200 keV polarized photoelectron gun and compatible Wien filter spin rotator.

Palacios-Serrano, Gabriel↗
NASA NTRS1990

Vehicle charging effects during electron beam emission from the CHARGE-2 experiment

The CHARGE-2 sounding rocket payload has measured the transient and steady-state charging of a spacecraft in LEO during the emission of a low-power electron beam. The electron beam successfully escaped the emitting spacecraft above 240 km, rather than being degraded by the spacecraft's potentials. These potentials were limited to about half of the 1-kV beam accelerating potential at all latitudes, suggesting that the electron beam was able to escape at altitudes down to 160 km. Electrons created from beam-plasma interactions become increasingly important in the return current below 240 km, and increased with decreasing altitude.

Myers, Neil B.↗
DOE OSTI2020

Jefferson Laboratory C100 Superconducting Radio-Frequency Cavity Fault Data, 2020

The dataset was created to train machine learning models for the task of identifying the (1) cavity and (2) fault type from C100-type cryomodules at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), thereby replacing the time-consuming efforts of a subject matter expert. Superconducting radio-frequency (SRF) cavity trips represent a significant source of accelerator downtime. Real-time – rather than post-mortem – identification of the offending cavity and classification of the fault type would give control room operators valuable feedback for corrective action planning. The anticipated benefit is increased beam-on-target time for users and provides performance metrics that can be used to improve future cavity designs. A series of 17 RF signals are recorded for each of the 8 cavities in a C100 cryomodule every time a cavity trips. These time-series signals are written to file using a specially designed data acquisition system. The dataset represents fault events recorded during Continuous Electron Beam Accelerator Facility (CEBAF) beam operations between January 18, 2019 and March 9, 2020. The following filtering steps were applied to collected data; (1) only 4 of the 17 signals per cavity are retained (GMES, GASK, CRFP, DETA2) (2) only events with data from each of the eight cavities in the cryomodule are kept, (3) only events that were sampled at 5 kHz were kept, (4) events from cryomodule 0L04 were neglected, (5) events occurring between February 4, 3PM and February 5, 12PM were neglected. As a result of preprocessing, the dataset is comprised of 2,375 unique events. The full dataset is comprised of three files: features.csv, cavity_labels.csv, fault_labels.csv. Each instance in faults.csv includes a timestamp (“date_time”), a label for the cryomodule which experienced the trip (“zone_label”), and 192 features (“feature_1”, “feature_2”... “feature_192”). The features correspond to 6 autoregressive features for each of 4 signals per cavity for each of the 8 cavities (6 × 4 signals/cavity × 8 cavities/cryomodule = 192). To deal with the large variation of signal amplitudes, time-series standardization via the z-score (standard score) function was applied prior to computing the features. For each instance, there is an associated label for the (1) cavity which faulted first (cavity_labels.csv) and (2) the type of fault that caused the trip (fault_labels.csv). The cavity identification can take values of [0, 1, 2, 3, 4, 5, 6, 7, 8] and the fault type can take values of [‘Microphonics’, ‘Quench_100ms’, ‘Controls_Fault’, ‘E_Quench’, ‘Quench_3ms’, ‘Single_Cav_Turn_Off’ , ‘Heat_Riser_Choke’, ‘Multi_Cav_Turn_Off’].

43 PARTICLE ACCELERATORS↗