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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
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 OSTI2022

Beam dynamics in independent phased cavities

Linear accelerators containing the sequence of independently phased cavities with constant geometrical velocity along each structure are widely used in practice. The chain of cavities with identical cell lengths is utilized within a certain beam velocity range, with subsequent transformation to the next chain with higher cavity velocity. Design and analysis of beam dynamics in this type of accelerator are usually performed using numerical simulations. A full theoretical description of particle acceleration in an array of independent phased cavities has not been developed. In the present paper, we provide an analytical treatment of beam dynamics in such linacs employing Hamiltonian formalism. We begin our analysis with an examination of beam dynamics in an equivalent traveling wave of a single cavity, propagating within accelerating section with constant phase velocity. We then consider beam dynamics in arrays of cavities, utilizing an effective traveling wave propagating along with the whole accelerator with the velocity of synchronous (reference) particle. The analysis concluded with the determination of the matched beam conditions. Finally, we present a beam dynamics study in 805 MHz Coupled Cavity Linac of the LANSCE accelerator facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

INITIAL STUDIES OF CAVITY FAULT PREDICTION AT JEFFERSON LABORATORY

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Vidyaratne, Lasitha↗
DOE OSTI2021

INITIAL STUDIES OF CAVITY FAULT PREDICTION AT JEFFERSON LABORATORY

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Vidyaratne, Lasitha↗
DOE OSTI2022

“Snowmass’21 Discussions on Future HEP Facilities in the US

The US particle physics community planning exercise (a.k.a. “Snowmass”) is organized every 7 to 9 years to provide a forum for discussions among the entire particle physics community to develop a scientific vision for the future of particle physics in the U.S. and its international partners. The Snowmass'21 Accelerator Frontier activities include discussions on high-energy hadron and lepton colliders, high-intensity beams for neutrino research and for “Physics Beyond Colliders”, accelerator technologies, science, education and outreach as well as the progress of core accelerator technologies, including RF, magnets, targets and sources. Here we summarize the Snowmass'21 discussions on future HEP accelerator facilities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Status of Error Correction Studies in Support of FFA@CEBAF

In pursuit of higher energy at the Continuous Electron Beam Accelerator Facility (CEBAF), the FFA@CEBAF energy upgrade study is considering the implementation of a novel technology to recirculate electron beam through the accelerating gradient of the machine more times. The technology in question is Fixed-Field Alternating-gradient (FFA) bending accelerator arcs: these arcs may replace the present highest energy electromagnetic (EM) arcs, and due to a much wider energy acceptance allow several more passes. The survey and beam error tolerance of the FFA arcs need to be well understood prior to commissioning, in addition to the limits of planned correction magnets and diagnostics. This work explores the current state of error tolerance and correction studies in FFA arcs at CEBAF.

Benesch, J.↗
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 OSTI2025

Persistent Current Simulation for CCT Testing Magnet Used in EIC

The Electron-Ion Collider (EIC), a powerful new facility to be built in the United States at the U.S. Department of Energy's Brookhaven National Laboratory in collaboration with Thomas Jefferson National Accelerator Facility, will explore the most fundamental building blocks of nearly all visible matter. Here, there are many different types of superconducting magnets near the interaction region (IR) of EIC. Due to space constraints and special lattice requirements, Tapered CCT (canted-cosine theta) magnets have been used for EIC. At beam injection, the magnetic field is only ~5.5% of the maximum operating field. Considerable field errors will be generated from persistent current in superconducting strands even using very fine filament for those superconductors. A tapered CCT demonstrator magnet has been built and tested successfully at BNL since July 2020 to evaluate the key technologies for future tapered CCT magnets. In October 2023, BNL team also measured the persistent current in this demonstrator magnet. To validate the persistent current simulation methods for CCT magnets in EIC, this paper used a full 3D Opera Model and measured magnetization data from superconducting strand for the simulation. Simulation results showed reasonable agreement with recent measurement results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Collider-quality electron bunches from an all-optical plasma photoinjector

We present an approach for generating collider-quality electron bunches using a plasma photoinjector. The approach leverages recently developed techniques for the spatiotemporal control of laser pulses to produce a moving ionization front in a nonlinear plasma wave. The moving ionization front generates an electron bunch with a current profile that balances the longitudinal electric field of an electron beam-driven plasma wave, creating a uniform accelerating field across the bunch. Particle-in-cell (PIC) simulations of the ionization stage show the formation of an electron bunch with 220 pC charge and low emittance (ɛ 𝑥 = 171 nm rad, ɛ 𝑦 = 76 nm rad). Quasistatic PIC simulations of the acceleration stage show that the bunch is efficiently accelerated to 24 GeV over 2 m with a final energy spread of less than 1% and emittances of ɛ 𝑥 = 189 nm rad and ɛ 𝑦 = 80 nm rad. This high-quality electron bunch meets the requirements outlined by the Snowmass process for intermediate-energy colliders and compares favorably to the beam quality of proposed and existing accelerator facilities. The results establish the feasibility of plasma photoinjectors for future collider applications making a significant step toward the realization of high-luminosity, compact accelerators for particle physics research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Physics Design of Proton/Ion SRF Accelerators

Superconducting Radio Frequency (SRF) technology has become foundation of the modern high energy particle accelerators. The technology enables a higher accelerating field with minimal power dissipation and a stronger compact magnetic field. These advancements have broadened the operational horizon of the particle accelerators making a higher duty factor and Continuous Wave (CW) beam operations both feasible and economically viable. The intensity frontier research founded on generation of intense beam of exotic particles including but not limited to neutrinos, muons, kaons and neutrons as well as practical applications involving transmutation of nuclear reactor waste, rare isotopes generation, sub-critical nuclear power generation etc. could be accomplished efficiently only by using superconducting proton/ions particle accelerators. As a result, many newly constructed or under construction high energy accelerator facilities around the world such as Proton Improvement Plan-II (PIP-II) at Fermilab, FRIB at MSU, ESS at Sweden are utilizing SRF accelerators. This talk presents the design philosophy of SRF proton/ion particle accelerator, with a focus on optimizing its performance while addressing physics and operational challenges including the fault scenarios, machine availability and preservation of crucial beam parameters.

Saini, Arun↗
NASA NTRS1995

Energy measurement of electron beams by Compton scattering

A method has been proposed to utilize the well-known Compton scattering process as a tool to measure the centroid energy of a high energy electron beam at the 0.01% level. It is suggested to use the Compton scattering of an infrared laser off the electron beam, and then to measure the energy of the scattered gamma-rays very precisely using solid-state detectors. The technique proposed is applicable for electron beams with energies from 200 MeV to 16 GeV using presently available lasers. This technique was judged to be the most viable of all those proposed for beam energy measurements at the nearby Continuous Electron Beam Accelerator Facility (CEBAF). Plans for a prototype test of the technique are underway, where the main issues are the possible photon backgrounds associated with an electron accelerator and the electron and laser beam stabilities and diagnostics. The bulk of my ASEE summer research has been spent utilizing the expertise of the staff at the Aerospace Electronics Systems Division at LaRC to assist in the design of the test. Investigations were made regarding window and mirror transmission and radiation damage issues, remote movement of elements in ultra-high vacuum conditions, etc. The prototype test of the proposed laser backscattering method is planned for this December.

Keppel, Cynthia↗
DOE OSTI2024

Error and Correction Analysis for the FFA@CEBAF Energy Upgrade

An energy upgrade design for the Continuous Electron Beam Accelerator Facility (CEBAF) is under development, using fixed field alternating gradient (FFA) return arcs to recirculate electron beam up to an additional five times through the accelerating structures at CEBAF. A necessary component of any large accelerator is a beam steering and optical correction system. Small environmental changes and system errors can lower beam quality or even shut down the machine; and in pursuit of the scientific mission of JLab, high quality electron beams must be delivered to the experimental halls on a predictable schedule. Correction in the novel FFA arcs of the current upgrade design is complicated by several factors. These complexities inform the choice of correction algorithm structure and parameter values. A baseline algorithm in addition to diagnostic and correction hardware configuration is presented. The effect of this correction protocol is shown with respect to estimated errors, and several possible extensions of the algorithm are discussed. This work presents an important proof of concept for the FFA@CEBAF design effort, and provides a functional correction strategy which may be simply adjusted and optimized for future design changes.

Coxe, Alex [Old Dominion Univ., Norfolk, VA (Unite↗
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↗
NASA NTRS2003

Measurement of Charged Particle Interactions in Spacecraft and Planetary Habitat Shielding Materials

Accurate models of health risks to astronauts on long-duration missions outside the geomagnetosphere will require a full understanding of the radiation environment inside a spacecraft or planetary habitat. This in turn requires detailed knowledge of the flux of incident particles and their propagation through matter, including the nuclear interactions of heavy ions that are a part of the Galactic Cosmic Radiation (GCR). The most important ions are likely to be iron, silicon, oxygen, and carbon. Transport of heavy ions through complex shielding materials including self-shielding of tissue modifies the radiation field at points of interest (e.g., at the blood-forming organs). The incident flux is changed by two types of interactions: (1) ionization energy loss, which results in reduced particle velocity and higher LET (Linear Energy Transfer); and (2) nuclear interactions that fragment the incident nuclei into less massive ions. Ionization energy loss is well understood, nuclear interactions less so. Thus studies of nuclear fragmentation at GCR-like energies are needed to fill the large gaps that currently exist in the database. These can be done at only a few accelerator facilities where appropriate beams are available. Here we report results from experiments performed at the Brookhaven National Laboratory s Alternating Gradient Synchrotron (AGS) and the Heavy Ion Medical Accelerator in Chiba, Japan (HIMAC). Recent efforts have focused on extracting charge-changing and fragment production cross sections from silicon beams at 400, 600, and 1200 MeV/nucleon. Some energy dependence is observed in the fragment production cross sections, and as in other data sets the production of fragments with even charge numbers is enhanced relative to those with odd charge numbers. These data are compared to the NASA-LaRC model NUCFRG2. The charge-changing cross section data are compared to recent calculations using an improved model due to Tripathi, which accurately predicts the observed (slight) energy dependence. An additional set of data will be presented from an analysis of shielding material performance in the 1 GeV/nucleon iron beam at the AGS. A wide variety of candidate materials for spacecraft construction, as well as elemental targets, have been placed in this beam and their effects on transmitted dose and dose equivalent measured. The results support a prediction by J. Wilson et al. that hydrogen-loaded materials give the greatest dose reduction per unit mass.

Zeitlin, Cary J.↗
NASA NTRS2001

Recent measurements for hadrontherapy and space radiation: nuclear physics

The particles and energies commonly used for hadron therapy overlap the low end of the charge and energy range of greatest interest for space radiation applications, Z=1-26 and approximately 100-1000 MeV/nucleon. It has been known for some time that the nuclear interactions of the incident ions must be taken into account both in treatment planning and in understanding and addressing the effects of galactic cosmic ray ions on humans in space. Until relatively recently, most of the studies of nuclear fragmentation and transport in matter were driven by the interests of the nuclear physics and later, the hadron therapy communities. However, the experimental and theoretical methods and the accelerator facilities developed for use in heavy ion nuclear physics are directly applicable to radiotherapy and space radiation studies. I will briefly review relevant data taken recently at various accelerators, and discuss the implications of the measurements for radiotherapy, radiobiology and space radiation research.

NASA Discipline Radiation Health↗
DOE OSTI2024

Progress on the Autonomous Event Detection System For the Laser Particulate Counter

Field emission is one of the most important issues that limits the performance of the superconducting radio frequency (SRF) systems and leads to SRF cavity trips at the Continuous Electron Beam Accelerator Facility at Jefferson Lab. Studies have confirmed that particulates are the dominant source of field emitters and the particulates can be transported into a cavity from other parts of the accelerator. To monitor the transportation of the particulates, a prototype of a novel, non-invasive laser particulate counter (LPC) has been developed and tested. Experiments have been done to validate the capability of the LPC. We are developing autonomous event detection system to continuously monitor the readout from the LPC and to recognize real events generated by particulates from noises using machine learning model. In this report, we will present how the data are prepared and how the model is trained. We will also discuss the performance of the model.

Zhang, H.↗
DOE OSTI2026

Accelerator Complex Evolution at Fermilab

The largest hadron accelerator facility in the US is undergoing radical changes and the undertaking of new HEP-driven neutrino research. This talk will discuss the wide-ranging projects and impacts to the accelerator community taking place at FNAL.

Convery, M. [Fermilab]↗
DOE OSTI2022

Time- and Energy-Resolved Coupled Saturn Radiation Environments Simulations Using the Integrated Tiger Series (ITS) Code

Using a newly developed coupling of the ElectroMagnetic Plasma In Realistic Environments (EMPIRE) code with the Integrated Tiger Series (ITS) code, radiation environment calculations have been performed. The effort was completed as part of the Saturn Recapitalization (Recap) program that represents activities to upgrade and modernize the Saturn accelerator facility. The radiation environment calculations performed provide baseline results with current or planned hardware in the facility. As facility design changes are proposed and implemented as part of Saturn Recap, calculations of the radiation environment will be performed to understand how the changes impact the output of the Saturn accelerator.

43 PARTICLE ACCELERATORS↗