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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 181 records · Page 10

A Mechanically Tuned Superconducting Main Injector Cavity

Radio Frequency (RF) superconductivity has been a mainstay of accelerator science for decades. However, its benefits have yet to be applied to proton synchrotrons with demanding tuning requirements. For example, the Main Injector (MI), Fermilab's high-energy proton synchrotron, currently utilizes 20+ ferrite-loaded cavities for a targeted 1.2 s acceleration cycle. Harnessing the extremely high gradients associated with superconductivity, the required number of cavities could be reduced by an order of magnitude, dramatically lowering operational power requirements even with cryogenic considerations. Additionally, the current plans for the Fermilab Accelerator Complex Evolution (ACE) initiative involve almost doubling the number of cavities in MI if the same designs are to be used, further highlighting the potential benefits of superconductivity. These advantages are attractive, but to date, no tunable superconducting cavity suitable for MI has been proposed due to the incompatibility of conventional broadband tuning methods with superconductivity. Here, we present a tunable superconducting cavity concept capable of record-breaking performance. Tuning will be accomplished by using high-speed linear actuators to vary the insertion depth of metallic plungers into the cavity volume. This tuning concept is theoretically viable with currently available technology and will be fully compatible with a superconducting cavity.

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Achievement in Beam Power Records for the NOvA Target System

We began upgrading the NOvA target system for 1-Mega Watt (1-MW) beam operation in 2017. Major challenges included maintaining the quality of neutrino beams with reliable instrumentation, reducing instantaneous beam heating on the target, increasing cooling power to handle the high-power beam, and controlling tritium water production rate. We finally achieved a one-hour beam power record of 1.018 MW in Summer 2024. This milestone demonstrates our capability to operate at 2+ MW beam power for the future Long Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE).

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Rapid Tuning of Synchrotron Surrogate Model at the Recycler Ring

The 8 GeV proton-storage Recycler Ring (RR) is essential for reaching megawatt beam intensity goals for the DUNE neutrino beam at Fermilab. Custom shims on each RR permanent magnet were designed to cancel manufacturing defects and bring magnetic fields to the design values. Remaining imperfections cause the observed tune variation vs energy to deviate from what is calculated using the design fields. Using the POUNDERS (“Practical Optimization Using No Derivatives for sums of Squares”) optimization method with Synergia in the loop, we demonstrate rapid convergence to a set of additive, higher-order multipole moments of these magnetic shims which reproduce that observed variation, and show that the convergence advantage grows with the parameter-space dimensionality.

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LBNF Internal Cryogenics Supports Design

This poster presents requirements, methodology, and results of the LBNF Internal Cryogenics External Supports conceptual design. Forces and flexibility analyses, membrane cryostat restrictions, and simplicity were all taken into consideration for the design.

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wa-hls4ml: A GNN Surrogate Model for hls4ml

Recent advancements in use of machine learning techniques on field-programmable gate arrays (FPGAs) have allowed for implementation of embedded neural networks with extremely low latency. This is invaluable for particle detectors at the Large Hadron Collider, where latency and used area must be strictly bounded. The hls4ml framework is a procedure for converting from trained machine learning model software, to a synthesis result that can be used on an FPGA. However, running the pipeline is a time-consuming procedure, and there is a strong risk of failure. In particular, it is possible that the model is unable to be converted into a synthesis result, or that the resource consumption of the model will exceed the resources of the target FPGA. To aid with this development, we introduce wa-hls4ml, a surrogate model which uses a graph neural network to emulate the structure of the source models. The goal is to estimate the chance of success and resource consumption of an arbitrary model when passed through the hls4ml procedure, without the time consumption of actually running the pipeline.

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Blueprints for Training Information Bottlenecks for Collider Analyses

Dimensionality reduction is a crucial aspect of data analysis in high energy physics, even if accompanied by information loss. Several methods, including histogram- and kernel-based analyses, are only computationally feasible for low-dimensional data. Furthermore, simulation models used in HEP can often only be validated for low-dimensional data. We provide several blueprints for using machine learning to create low-dimensional data representations (continuous event variables and discrete classification labels) for use in signal discovery and parameter estimation tasks. We also describe how to design the learned representation to facilitate a) searches with unknown model parameters and b) validation of simulation models in data control regions.

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Beam Design for Muon Catalyzed Fusion

Fusion holds great promise as a clean and abundant energy source. However, traditional thermonuclear fusion encounters significant challenges due to the extreme temperatures required to overcome the coulomb barrier for two nuclei to fuse. In contrast, muon-catalyzed fusion presents an alternative approach that can surmount this barrier at significantly lower temperatures. Muons, with properties resembling those of electrons but 200 times heavier, can effectively reduce the atomic orbital radius, enabling central nuclei to overcome the coulomb force through the strong force. By introducing muons into a mixture of deuterium and tritium (two hydrogen isotopes), fusion is facilitated, releasing a 3.5MeV alpha particle and a 14.1MeV neutron. In the majority of cases, the muon is liberated and can initiate further fusions. However, approximately 0.8% of the time, it adheres to the alpha particle and remains bound until it either decays or undergoes reactivation through collisio nal ionization. To maximize the number of fusions per muon, it is crucial to enhance the cycling rate and reactivation fraction. Theoretical predictions and experimental data both suggest that the sticking rate decreases with increasing density. However, there exists a discrepancy between experimental observations and theoretical estimations regarding the extent of this decrease. To address these disparities, this experiment aims to investigate the cycling rate and sticking fraction under higher temperatures and pressures than previously explored.

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ADRIANO2 Calorimeter Performance from 2022 Test Beams

A novel high-granularity dual-readout calorimetric technique was developed as part of the T1604 collaboration. The ADRIANO2 Calorimeter Prototype consists of a pair of optically isolated, small sized tiles made of scintillating plastic and lead glass. Čerenkov light from the lead glass are exploited to for high resolution timing measurements, while high granularity from scintillating plastic can be used to probe the spatial component of the particle shower. This setup works for excellent energy resolution and particle detection for REDTOP as it is crucial for a calorimeter to detect the decay products of eta/eta-prime mesons. Measurements were collected on ADRIANO2 between February to December 2022 to evaluate the detector performance at Fermilab’s Test Beam Facility. The key metrics extracted from my analysis are the detector’s efficiency for various tile configuration and light-yield which will then be used as parameters for an upgraded REDTOP monte-carlo simulation campaign. An in-depth analysis of ADRIANO2 performance are detailed in this presentation.

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Operational Experience of a Cryomodule Test Stand for LCLS-II Cryomodules

CMTS1 (cryomodule test stand 1) at Fermilab was built to test cryomodules built for the LCLS-II beamline at SLAC and is currently testing cryomodules for LCLS-II-HE, the high energy upgrade to LCLS-II. The first cryomodule test was in 2016 and to date over 30 cryomodules have been tested here. This talk will highlight operational experience of the vacuum systems including insulating, coupler, and a low particulate beamline vacuum system. It will focus on the problems that have come up over the years, their solutions, and mitigations put in place to prevent further issues.

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New Advances in Optical Stochastic Cooling

Recently, Optical Stochastic Cooling (OSC) became the first demonstrated method for ultra-high-bandwidth stochastic cooling. The initial experiments at Fermilab’s IOTA ring explored the essential physics of the method and demonstrated cooling, heating and manipulation of beams and single particles. Having been validated in practice, with continued development, OSC carries the potential for dramatic advances in the state-of-the-art performance and flexibility for beam cooling and control. The ongoing program at Fermilab is now focused on the development of an OSC system that includes high-gain optical amplification, which promises a two-order-of-magnitude increase in the strength of the OSC force. In this talk, we briefly review the results of the initial experimental campaign, describe the status of the conceptual and hardware designs for the amplified OSC system, report initial experimental results of our high-gain amplifier development, and explore near-term operational plans and use cases.

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RF Frontiers for Particle Physics, the US View

In this talk I provide an update on the RF research for future colliders in the U.S., through the prism of Snowmass and P5 report. During Snowmass, we considered various applications of RF technology to the proposed future colliders and other accelerator- and non-accelerator-based experiments. P5 narrowed down the choices of future machines. The colliders include circular and linear $e^+ e^-$ Higgs factories, and longer-term options such as muon and hadron high energy colliders. I will start with Snowmass and P5 recommendations. As it is impossible to cover all possible RF R&D topics, I will discuss only three critical topics relevant to future colliders: efficiency of RF power sources, cold normal conducting RF, and cavities for ionization channel of muon collider. Progress on SRF accelerating cavities for future colliders will be covered in a separate talk. The choice of topics reflects my preference and in some cases ignorance, which I think is inevitable when one tries to cover such a broad subject.

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Neutrino Beams & Fluxes

Overview of accelerator neutrino beams and neutrino fluxes. *Neutrinos & their sources • Accelerator Neutrino Beams • Beamline components • Neutrino flux • Why we care about flux uncertainties

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