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At least 487 records · Page 27

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DOE OSTI2021

Advances in secondary ion mass spectrometry for N-doped niobium

Accurate secondary ion mass spectroscopy measurement of nitrogen in niobium relies on the use of closely equivalent standards, made by ion implantation, to convert nitrogen signal intensity to nitrogen content by determination of relative sensitivity factors (RSFs). Accurate RSF values for ppm-range nitrogen contents are increasingly critical, as more precision is sought in processes for next-generation superconducting radiofrequency (SRF) accelerator cavities. Furthermore, factors influencing RSF value measurements were investigated with the aim of reliably attaining better than 10% accuracy in nitrogen concentrations at various depths into the bulk. This has been accomplished for materials typical of SRF cavities at the cost of increased attention to all aspects.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Analysis of furnace contamination on superconducting radio frequency niobium using secondary-ion mass spectrometry

Detection of surface contamination on niobium materials used in superconducting radio frequency (SRF) applications is difficult due to quantitative sensitivity and near-atomic depth resolution needed. Inspection of samples known to have experienced surface contamination was found to have inconsistent nitride coverage after high-temperature nitrogen gas exposure (“doping”). Here we compare contaminating species found on samples treated in several different vacuum furnaces, both “exposed” directly in the chamber and “protected” by containment shielding from evaporative sources with “furnace caps.” Typically, furnace caps are used to impede contamination from reaching the interior surface of cavities during the high-temperature vacuum bake that immediately precedes exposure to nitrogen gas. Although, to date, little is known about the effectiveness of these caps, SIMS results showed that they were effective in limiting contamination arising from the furnace environment. Inspection of sample surfaces by SEM showed a lack of nitrides present on contaminated specimens. TEM with energy dispersive spectroscopy performed on these samples revealed that a carbon-rich layer now existed, indicating that a relatively high contaminant load prevents the nucleation and growth of surface nitrides, while thus inhibiting interstitial nitrogen uptake. Except in extreme cases, subsequent removal of the top several micrometers of the surface via electropolishing appears to effectively eliminate any strong influence on the subsequent SRF cavity performance. With the absence of furnace cleaning, carbon contamination was found to be nearly 10× higher for protected nitrogen-doped and electropolished samples, with minimal metallic contamination detected for both processes. SIMS analysis was also performed to compare the cleanliness of samples fully prepared by such nitrogen “doping” with those prepared by a related process, involving the dissolution of niobium surface oxide and diffusion of oxygen into the surface. This oxygen doping or alloying process offers attractive advantages.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Deep-learning-based domain adaptation for cavity fault prediction at Jefferson Laboratory

Superconducting radio-frequency (SRF) cavities are the core components of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab, providing high-power electron beams for nuclear physics experiments. The facility comprises 418 SRF cavities, and any fault in these cavities can lead to interruptions in the electron beam supply. Cavity faults are the leading cause of beam trips in CEBAF. Predicting and mitigating those faults before onset can help maintain normal operation. Existing models face challenges in distinguishing between normal and fault signals when changes occur in the underlying time-series data, from changes in control software, operational parameters, or the environment. This work proposes a deep learning domain adaptation model that leverages transfer learning to address fault prediction challenges by improving accuracy. The model is trained and fine-tuned using a dataset collected for faulty and normal operation using a data acquisition system in CEBAF. Our deep learning-based domain adaptation model achieves a prediction accuracy of 89.61% of the fault and normal signals. The developed model effectively predicts normal running signals compared to the baseline approach without domain adaptation. This capacity is essential for the fault prediction task in the CEBAF because of heavily imbalanced data containing vast amounts of normal signals. The model performs well for predicting faults several hundred milliseconds before the fault onset compared to other models where no adaptation is applied. Incorporating deep learning-based domain adaptation techniques will significantly improve the fault prediction performance.

Rahman, Md Monibor [Old Dominion Univ., Norfolk, V↗

DOE OSTI2025

Monte Carlo simulation analysis for radiation damage on Glidcop Al-15 caused by 17-20 MeV/u heavy ions

The Facility for Rare Isotope Beams (FRIB) SRF linear heavy-ion accelerator is designed to accelerate all ions up to uranium to a maximum beam power of 400 kW. Several beam intercepting devices (BIDs) are essential to the successful operation of the accelerator, including a low power charge selector (LPCS) made of copper containing 0.15% precipitated aluminum oxide by weight called Glidcop Al-15. As FRIB ramps up the primary beam power beyond the current 20 kW level, the charge selector must withstand higher radiation damage rates, typically measured in displacements per atom (dpa). Significant beam induced radiation damage including significant deformation, like swelling, blistering, and cracking has been observed on a recently removed LPCS. We also observed physical features up to about 5.5 mm wide and appear to be deeper than the projected range of any ions. This paper presents the results of Monte Carlo simulations carried out using the Particle and Heavy Ion Transport code System (PHITS), quantifying the total damage dose and ion concentration, etc. Simulating an accurate irradiation history is essential to determining the scope of post irradiation examination (PIE) work.

Fletcher, Ethan [Michigan State U.]↗

DOE OSTI2021

Superconducting Radio-frequency Cavity Fault Classification Using Machine Learning at Jefferson Laboratory

We report on the development of machine learning models for classifying C100 superconducting radiofrequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. Of the 418 SRF cavities in CEBAF, 96 are designed with a digital low-level RF system configured such that a cavity fault triggers recordings of RF signals for each of eight cavities in the cryomodule. Subject matter experts analyze the collected time-series data and 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 postmortem - identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the machine learning models during a recent physics run. We also discuss efforts for further insights into fault types through unsupervised learning techniques and present preliminary work on cavity and fault prediction using data collected prior to a failure event.

Tennant, C. D.↗

DOE OSTI2021

An 8 GeV Linac as the Booster Replacement in the Fermilab Power Upgrade

Increasing the Main Injector (MI) beam power above ~1.2 MW requires replacement of the 8 GeV Booster by a higher intensity alternative. Previously, rapid-cycling synchrotron (RCS) and Linac solutions were considered for this purpose. In this paper, we consider the Linac version that produces 8 GeV H⁻ beam for injection into the Recycler Ring (RR) or Main Injector (MI). The Linac takes ~1 GeV beam from the PIP-II Linac and accelerates it to ~2 GeV in a cw SRF linac, followed by a ~2-8 GeV pulsed linac using 1300 MHz cryomodules. The linac components incorporate recent improvements in SRF technology. The linac configuration and beam dynamics requirements are presented. Injection options are discussed. Research needed to implement the Booster replacement is described.

Neuffer, David V.↗

DOE OSTI2021

Study of Conduction-Cooled Superconducting Quadrupole Magnets Combined with Dipole Correctors for the ILC Main Linac

A superconducting rf (SRF) cryomodule for International Linear Collider(ILC) Main Linac equips focus/steering magnets. The magnets are "superferric" magnets with four superconducting (SC) race track coils conductively cooled from the cryomodule LHe supply pipe. The quadrupole field gradient and dipole field are 40 T/m and 0.1 T, respectively. The magnet length and iron-pole radius are 1 m and 0.045 m, respectively. It is known that dark current is generated at SRF cavities and accelerated through the following linac string. The dark current reaches and heats the SC magnets. It is estimated that the power deposition in the magnet may reach more than a few watts and temperature of the SC coils may locally reach to critical temperature of NbTi. It is important to make the magnet not reach quench with sufficient conduction cooling. We aim to realize the SC magnet which can stably operate under such condition. We plan to develop test coils made of three types of SC materials, NbTi, Nb₃Sn, and MgB₂ and study thermal characteristics and stability . We will develop a short model magnet, based on the test coil results. Here, we will present the magnet design study and the R&D plan.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

PRELIMINARY RESULTS OF MAGNETIC AND TEMPERATURE MAP SYSTEM FOR 3 GHz SUPERCONDUCTING RADIO FREQUENCY CAVITIES

Superconducting radio frequency (SRF) cavities are fundamental building blocks of modern particle accelerators. A surface resistance in the tens of nanoOhm range is achieved when cooling these cavities to liquid helium temperature, ~2 - 4 K. One of the leading sources of residual losses in SRF cavities is trapped magnetic flux. Flux trapping mechanism depends on different surface preparations and cool-down conditions. We have designed, developed and commissioned a combined magnetic and temperature mapping system using anisotropic magneto-resistance sensors and carbon resistors, respectively, to study the flux trap mechanism in 3 GHz single-cell niobium cavities. In this contribution, we will describe the experimental apparatus and present preliminary test results.

Parajuli, I. P.↗

DOE OSTI2022

MAGNETIC FIELD MAPPING OF 1.3 GHz SUPERCONDUCTING RADIO FREQUENCY NIOBIUM CAVITIES

Niobium is the material of choice to build superconducting radio frequency (SRF) cavities, which are fundamental building blocks of modern particle accelerators. These cavities require a cryogenic cool-down to ~2 - 4 K for optimum performance minimizing RF losses on the inner cavity surface. However, temperature-independent residual losses in SRF cavities cannot be prevented entirely. One of the significant contributor to residual losses is trapped magnetic flux. The flux trapping mechanism depends on different factors, such as surface preparations and cool-down conditions. We have developed a diagnostic magnetic field scanning system (MFSS) using Hall probes and anisotropic magneto-resistance sensors to study the spatial distribution of trapped flux in 1.3 GHz single-cell cavities. The first result from this newly commissioned system revealed that the trapped flux on the cavity surface might redistribute with increasing RF power. The MFSS was also able to capture significant magnetic field enhancement at specific cavity locations after a quench.

Parajuli, I. P.↗

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

PARTICULATE STUDY OF NEG PUMPS IRRADIATED IN THE CEBAF TUNNEL

Non-evaporable getter (NEG) pumps are being used to maintain ultra-high vacuum in the beamline of superconducting radio-frequency (SRF) accelerators, such as the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. Because of the sensitivity of the performance of SRF cavities to particulate contamination, it is important to evaluate the integrity of the NEG material after exposure to high radiation during beam operation. The particulate from two NEG pumps based on ZAO® getter alloy was measured with a particle counter in a clean-room. The pumps were assembled onto a hermetically sealed setup which was placed in the CEBAF tunnel. The setup was exposed to 24 h beam operation for ~ 230 days. The total gamma-rays dose measured on the test setup was ~ 1.6 Mrad. The total neutron dose measured at ~ 75 cm of the test setup was ~ 11 krad. The particulate count from the two pumps was measured again in the clean-room after irradiation. Whereas an increase of particulate counts was measured, compared to before irradiation, subsequent measurements indicate the absence of systematically loose particulate. The pumping speed of one of the irradiated pumps was also measured to be consistent with that of a non-irradiated one, corroborating the absence of significant damage to the ZAO® NEG material due to irradiation.

Ciovati, G. [Thomas Jefferson National Accelerator↗

DOE OSTI2026

Status of 22 GeV CEBAF Upgrade Using FFA Arcs

Jefferson Lab is exploring an upgrade to extend CEBAF’s energy to ~22 GeV within the existing tunnel by incorporating Fixed-Field Alternating-Gradient (FFA) arcs. In this scheme, the two lowest-energy electromagnetic arcs are removed, the remaining arcs are reassigned to lower energies, and a new pair of high-energy FFA arcs enables six additional recirculations using the existing SRF linacs. The non-scaling FFA lattice employs Halbach-derived permanent magnets with provisions for dipole, quadrupole, and higher-order components, offering large momentum acceptance and reduced operating cost. Implementing this concept requires updated linac optics, modifications to the remaining arcs, and a redesigned electromagnetic switchyard. Ongoing beam-dynamics studies address synchrotron-radiation–induced energy loss and emittance growth, along with strategies for their mitigation.

Ogur, S. [Thomas Jefferson National Accelerator Fa↗

DOE OSTI2022

Evaluation of Single-Cell Cavities Made of Forged Ingot Niobium at Jefferson Lab

Currently, fine grain niobium (Nb) (grain size ~ 50 um) and large grain Nb (grain size of a few cm) are being used for the fabrication of superconducting radio frequency (SRF) cavities. Medium grain forged ingot with grain size of a few hundred um may be beneficial for cost-effectiveness as well as providing better performance for future SRF-based accelerators. Forged ingot Nb with medium grain size is a novel production method to obtain Nb discs used for the fabrication of superconducting radio frequency cavities. We have fabricated two 1.5 GHz single cell cavities made from forged Nb ingot with a residual resistivity ratio of ~100. The cavities were chemically and mechanically polished and heat-treated in the temperature range of 650-1000 C before the rf test. One of the cavities reached an accelerating gradient of 34 MV/m with a quality factor Q > 1e10, while the second cavity was limited at 14 MV/m, likely due to a weld defect at the equator.

Dhakal, P.↗

DOE OSTI2022

ERL-Based Compact X-Ray FEL

We propose to develop an energy-recovery-linac (ERL)-based X-ray free-electron laser (XFEL). Taking advantage of the demonstrated high-efficiency energy recovery of the beam power in the ERL, the proposed concept offers the following benefits: i) recirculating the electron beam through high-gradient superconducting RF (SRF) cavities shortens the linac, ii) energy recovery in the SRF linac saves the klystron power and reduces the beam dump power, iii) the high average beam power produces a high average photon brightness. In addition, such a concept has the capability of delivering optimized high-brightness CW X-ray FEL performance at different energies with simultaneous multipole sources. In this paper, we will present the preliminary results on the study of feasibility, optics design and parameter optimization of such a device.

Lin, Fanglei↗

DOE OSTI2022

Real-Time Cavity Fault Prediction in CEBAF Using Deep Learning

Data-driven prediction of future faults is a major research area for many industrial applications. In this work, we present a new procedure of real-time fault prediction for superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF) using deep learning. CEBAF has been afflicted by frequent downtime caused by SRF cavity faults. We perform fault prediction using pre-fault RF signals from C100-type cryomodules. Using the pre-fault signal information, the new algorithm predicts the type of cavity fault before the actual onset. The early prediction may enable potential mitigation strategies to prevent the fault. In our work, we apply a two-stage fault prediction pipeline. In the first stage, a model distinguishes between faulty and normal signals using a U-Net deep learning architecture. In the second stage of the network, signals flagged as faulty by the first model are classified into one of seven fault types based on learned signatures in the data. Initial results show that our model can successfully predict most fault types 200 ms before onset. We will discuss reasons for poor model performance on specific fault types.

Rahman, M.↗

DOE OSTI2022

Compact, High-Power Superconducting Electron Linear Accelerators for MW Industrial Applications

Fermilab has developed a novel concept for an industrial electron linac using Nb₃Sn coating technology and conduction cooling. We will show the range of multi-cavity linac designs targeted toward various applications. We will also discuss technology development status with results on conduction cooling of SRF cavities based on cryocoolers, which removes the need for liquid Helium, thus making SRF technology accessible to industrial applications. These conduction-cooled linacs can generate electron beam energies up to 10 MeV in continuous-wave operation and can reach higher power (>=1 MW) by combing several modules. Compact and light enough to mount on mobile platforms, our machine is anticipated to enable new in-situ environmental remediation applications such as waste-water treatment for urban areas, X-ray medical device sterilization, and innovative pavement applications. We also show cost-economics and key R&D areas that much be addressed for a practical machine.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Impedance and wakefield studies of the EIC RCS 591 MHz five-cell cavity

The Electron-Ion Collider (EIC) is a next-generation accelerator complex designed to enable high-luminosity collisions between highly polarized electrons and light ions (e.g., He-3). A central component of its Electron Injection System (EIS) is the Rapid Cycling Synchrotron (RCS), which accelerates a single 28 nC electron bunch from 750 MeV to 5, 10, or 18 GeV using an array of 591 MHz five-cell superconducting RF (SRF) cavities—eight at the current design stage. To ensure stable acceleration of high-charge bunches, we conducted detailed impedance and wakefield studies of the SRF cavity structure using both frequency- and time-domain methods. Wakefield solvers (ECHO3D, ECHO1D, CST), eigenmode analysis, and multi-particle tracking with ELEGANT were employed to evaluate longitudinal and transverse impedance effects and to determine instability thresholds. These studies provide critical input for the cavity design and operating parameters required to preserve beam quality and stability in the RCS.

Accelerator Physics↗

DOE OSTI2026

Design of a shipping fixture for a compact cryomodule hermetic assembly

In support of the development of a conduction-cooled 915MHz superconducting radio frequency (SRF) cryomodule, this study highlights the design of a shipping fixture for transporting the hermetic assembly 4500 km from Jefferson Lab to General Atomics in San Diego, California. The hermetic assembly consists of a 2-cell 915 MHz SRF cavity, a coaxial fundamental power coupler and warm-to-cold transition beam tubes. The two-part shipping assembly consists of an inner frame, providing direct mounting of the components, and an outer frame mounted to the ground transport vehicle. The inner frame is then connected to the outer frame by way of wire-rope isolators. Accelerometer data from ground transportation of previous projects at Jefferson Lab provides the baseline for the expected frequency and magnitude of vibrational and shock events during transit. Modal analyses were carried out in ANSYS on the inner frame assembly and critical components to identify an appropriate wire-rope isolator configuration such that peak loads are mitigated and the incurred frequencies do not correspond with the fundamental modes of the structures.

Accelerator Physics↗