Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “accelerator physics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ANNIE: the Accelerator Neutrino Neutron Interaction Experiment

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a Gadolinium-loaded water Cherenkov detector placed in the Booster Neutrino Beam (BNB) at the Fermi National Accelerator Laboratory, USA. The primary physics goal of ANNIE is to perform neutrino cross-section measurements that will constrain systematic uncertainties in the next generation of long-baseline neutrino experiments. The first measurement will be the multiplicity of final-state neutrons from neutrino-nucleus interactions in water. Alongside these measurements, ANNIE has achieved the first ever deployments of two novel detector technologies in a neutrino beam: Large Area Picosecond Photodetectors (LAPPDs) and Water-based Liquid Scintillator (WbLS). LAPPDs are micro-channel-plate-based devices that provide timing resolution of ~100 picoseconds and sub-centimeter spatial resolution. WbLS combines the low attenuation and Cherenkov production of pure water with the high light-yield and low detection threshold of liquid scintillator. This talk will discuss the status of ANNIE's physics and R&D measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Beam results for the new super-conducting booster at Jefferson Lab

The performance results of a new super-conducting booster for the CEBAF injector at Jefferson Lab, could be of interest for other similar electron injectors. A recent addition of this new booster has provided us the ability to achieve a more adiabatic acceleration and therefore an improvement to the beam dynamics and beam brightness. It has also simplified the design and operation of the section of the injector responsible for accelerating the electron beam from a few hundred keV to several MeV (typically 6.7 MeV). The addition of the new booster was part of an upgrade to the CEBAF injector to improve the beam quality for future physics experiments with high sensitivity to beam quality. The booster consists of two cavities: a 2-cell cavity followed by a 7-cell cavity. This combination allows for a wide range of input electron beam energies, from 130 keV to more than 300 keV. In fact, during the last year, the booster was successfully operated with 140,180, and 200 keV input beam energies as the electron gun was being upgraded. This paper describes the new booster, presents beam optics data results from different beam studies, commissioning, and the physics quality beam operation.

Accelerator Physics↗
DOE OSTI2020

Model uncertainty in accelerator application simulations

Monte-Carlo nuclear reaction and transport codes are widely used to devise accelerator-based nuclear physics experiments; at the same time, many experiments are performed to validate the Monte-Carlo codes, which can be used for the design of full-scale nuclear power applications or the design of new benchmark experiments. Dedicated model benchmark studies investigate a broad range of nuclear reactions and quantities. Examples of these include isotope formation or secondary particle fluxes that result from the interactions of GeV-range hadrons with monoisotopic targets, which can be used to assess the respective systematic uncertainty of models. Such benchmark studies, as well as many nuclear application experiments and simulations carried out by various groups over the last few decades, enable us to draw methodological lessons. In this work, model uncertainty determined based on available experimental data allow us to identify the effects of practitioner expertise as well as the design of codes (user access to micro-scale parameters) on the range of uncertainties. We found that in cases when simulations are performed by code developers or users that are very experienced in performing simulations, the model to experiment quantity ratios generally agree with the limits determined by dedicated benchmark studies. In other cases, the ratios generally tend to be either smaller (underestimation of model error) or larger (overestimation of model error). A plausible explanation of the aforementioned effects is suggested.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Hydrodynamic modeling of plasma channel systems for laser plasma accelerators

Structured plasma channels are an essential technology for driving high-gradient, plasma-based acceleration and control of electron and positron beams for advanced concepts accelerators. Laser and gas technologies can permit the generation of long plasma columns known as hydrodynamic, optically-field-ionized (HOFI) channels, which feature low on-axis densities and steep walls. By carefully selecting the background gas and laser properties, one can generate narrow, tunable plasma channels for guiding high intensity laser pulses. Here, we present on the development of simulations of HOFI channels using the FLASH code, a publicly available radiation hydrodynamics code. We explore sensitivities of the channel evolution to laser profile, intensity, and background gas conditions, and identify relevant scalings with laser intensity through a range of practical channel delays.

Accelerators↗
DOE OSTI2024

Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations

One of the most promising applications of machine learning in computational physics is to accelerate the solution of partial differential equations (PDEs). The key objective of machine-learning-based PDE solvers is to output a sufficiently accurate solution faster than standard numerical methods, which are used as a baseline comparison. Here, we first perform a systematic review of the ML-for-PDE-solving literature. Out of all of the articles that report using ML to solve a fluid-related PDE and claim to outperform a standard numerical method, we determine that 79% (60/76) make a comparison with a weak baseline. Second, we find evidence that reporting biases are widespread, especially outcome reporting and publication biases. We conclude that ML-for-PDE-solving research is overoptimistic: weak baselines lead to overly positive results, while reporting biases lead to under-reporting of negative results. To a large extent, these issues seem to be caused by factors similar to those of past reproducibility crises: researcher degrees of freedom and a bias towards positive results. We call for bottom-up cultural changes to minimize biased reporting as well as top-down structural reforms to reduce perverse incentives for doing so.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The miniJPAS survey: White dwarf science with 56 optical filters

We analyze the white dwarf population in miniJPAS, the first square degree observed with 56 medium-band, 145 Å in width optical filters by the Javalambre Physics of the accelerating Universe Astrophysical Survey (J-PAS), to provide a data-based forecast for the white dwarf science with low-resolution ($R$ ~ 50) photo-spectra. We define the sample of the bluest point-like sources in miniJPAS with $r$ < 21.5 mag, a point-like probability larger than 0.5, ($u$ - $r$)< 0.80 mag, and ($g$ - $i$)< 0.25 mag. This sample comprises 33 sources with spectroscopic information: 11 white dwarfs and 22 quasi-stellar objects (QSOs). We estimate the effective temperature ($T$ eff ), the surface gravity, and the composition of the white dwarf population by a Bayesian fitting to the observed photo-spectra. The miniJPAS data are sensitive to the Balmer series and the presence of polluting metals. Our results, combined with those from the Javalambre Photometric Local Universe Survey (J-PLUS) which has a lower spectral resolution but has already observed thousands of white dwarfs, suggest that J-PAS photometry would permit – down to $r$ ~ 21.5 mag and at least for sources with 7000 < $T$ eff < 22 000 K – both the classification of the observed white dwarfs into H-dominated and He-dominated with 99% confidence and the detection of calcium absorption for equivalent widths larger than 15 Å. The effective temperature is estimated with a 2% uncertainty, which is close to the 1% from spectroscopy. A precise estimation of the surface gravity depends on the available parallax information. In addition, the white dwarf population at $T$ eff > 7000 K can be segregated from the bluest extragalactic QSOs, providing a clean sample based on optical photometry alone. The J-PAS low-resolution photo-spectra would produce precise effective temperatures and atmospheric compositions for white dwarfs, complementing the data from Gaia. J-PAS will also detect and characterize new white dwarfs beyond the Gaia magnitude limit, providing faint candidates for spectroscopic follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Unconventional ideas for ionization cooling of muons

Small muon beams increase the luminosity of a muon collider. Reducing the momentum and position spreads of muons reduces emittance and leads to small, cool beams. Ionization cooling has been observed at the Muon Ionization Cooling Experiment. 6D emittance reduction by a factor of 100, 000 has been achieved in simulation. Another factor of 5 in cooling would meet the basic requirements of a high luminosity muon collider. In this paper we compare, for the first time, the amount of RF needed in a cooling channel to previous linacs. Here, we also outline three methods aimed to help achieve a final factor of 5 in 6D cooling.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Advanced assessment of beam-induced background at a muon collider

Renewed international interest in muon colliders motivates the continued investigation of the impacts of beam-induced background on detector performance. This continues the effort initiated by the Muon Accelerator Program and carried out until 2017. The beam-induced background from muon decays directly impacts detector performance and must be mitigated by optimizing the overall machine design, with particular attention paid to the machine detector interface region. In order to produce beam-induced background events and to study their characteristics in coordination with the collider optimization, a flexible simulation approach is needed. To achieve this goal we have chosen to utilize the combination of LineBuilder and Monte Carlo FLUKA codes. We report the results of beam-induced background studies with these tools obtained for a 1.5 TeV center of mass energy collider configuration. Good agreement with previous simulations using the MARS15 code demonstrates that our choice of tools meet the accuracy and performance requirements to perform future optimization studies on muon collider designs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

The PAU Survey: narrow-band photometric redshifts using Gaussian processes

Here, we study the performance of the hybrid template machine learning photometric redshift (photo- z ) algorithm delight , which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the 40 PAUS narrow bands with six broad-band fluxes ( uBVriz ) in the Cosmic Evolution Survey (COSMOS) field using three different methods, including a new method that utilizes the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. delight achieves a photo- z 68th percentile error of σ 68 = 0.0081(1 + z ) without any quality cut for galaxies with i auto < 22.5 as compared to 0.0089(1 + z ) and 0.0202(1 + z ) for the bpz and annz 2 codes, respectively. delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than bpz and annz 2. Common photo- z outliers of delight and bcnz 2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrow-band fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of bcnz 2 and delight , allowing us to achieve a photo- z quality of σ 68 < 0.0035(1 + z ) at a magnitude of i auto < 22.5 while keeping 50 per cent objects of the galaxy sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The miniJPAS survey quasar selection – II. Machine learning classification with photometric measurements and uncertainties

Astrophysical surveys rely heavily on the classification of sources as stars, galaxies, or quasars from multiband photometry. Surveys in narrow-band filters allow for greater discriminatory power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of a larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a machine learning-based method that employs convolutional neural networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering ∼1 deg 2 of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established machine learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars, and unresolved galaxies. Our results are a proof of concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Status and Challenges in the MQXFB Nb 3 Sn Quadrupoles for the HL-LHC

The inner triplet (or low-β) quadrupole magnets are among the components to be upgraded in LHC interaction regions for the HL-LHC project. The new quadrupole magnets, called MQXF, are based on Nb 3 Sn superconducting magnet technology, with a conductor peak field of 11.3 T. CERN is in charge of the fabrication of the MQXFB variant, the longest Nb 3 Sn accelerator magnets designed and manufactured up to now, with a magnetic length of 7.2 m. Two magnets, MQXFBP3 and MQXFB02, reached the HL-LHC project requirements. However, they still exhibited a limitation at 4.5 K with a phenomenology similar to the one observed on the first two prototypes. After improvements on the cold mass (longitudinal welding) and magnet assembly (elimination of overstress on the conductor during loading) procedures, a series of modifications were implemented in MQXFB03 at the level of the coil fabrication to address and/or reduce weaknesses in the coils. The magnet was tested and was the first to achieve performance requirements at both 1.9 K and 4.5 K, with no signs of conductor limitation at 4.5 K. MQXFB is now in the series production phase, with around 2/3 of the coils completed and half of the magnets assembled. We provide in this paper an overview of the MQXFB program, with a summary of the main recent achievements and an overall status of the fabrication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Architecture for Quantum Time-dependent Circuits (ArQTIC) v1.0

ArQTiC is a domain-specific full-stack software package built for the dynamic simulations of materials on quantum computers. Its main contributions include providing a software library for high-level programming of such simulations on quantum computers, and providing post-processing capabilities that allow users to more efficiently analyze results from the quantum computer. Paired with the power to optimize and execute quantum circuits, ArQTiC opens the field of dynamic materials simulations on quantum computers to a broader community of scientists from a wider range of domain sciences, paving the way for accelerated progress towards physical quantum supremacy.

Bassman, Lindsay↗
DOE OSTI2021

Deep reinforcement learning for dynamic control of fuel injection timing in multi-pulse compression ignition engines

Conventional compression-ignition (CI) engines have long offered high thermal efficiencies and torque across a wide range of loads, but often require extensive exhaust gas treatment that decreases efficiency to meet ever-increasing emissions regulations. One strategy to decrease emissions is to split the fuel injection into a series of smaller injections. In this paper, we explore a new way of discovering optimal control strategies for the next generation of CI engines using deep reinforcement learning (DRL). We outline a DRL procedure to maximize the weighted reward of engine work while minimizing end-of-cycle NO x emissions. Through the procedure outlined in this paper, we show that the DRL agent is able to reduce NO x emissions threefold while only decreasing network by 2%. We demonstrate the use of transfer learning (TL) across hierarchies of physical models to accelerate the learning process, making this approach feasible for a range of control problems within this space. This paper presents a framework and demonstration for using DRL to design control systems in technology areas such as multi-pulse engine control where a hierarchy of models combined with multi-objective rewards are used for optimal operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

RPI LINAC refurbishment and upgrade project

The Electron Linear Accelerator at Rensselaer Polytechnic Institute (RPI) was constructed in the late 1950s and started operation in 1961 [1]. The facility was designed and used primarily for measurements of Nuclear Data (ND) with emphasis on the resonance energy region. As such it was designed to produce short pulses of neutrons (5-5000 ns) and equipped with detection stations at different neutron flight path distances from the source (15 m-250 m). When the LINAC started operation it was one of the most powerful accelerators in the world for high energy-resolution measurements in the resonance region. The original LINAC with some upgrades is still in operation but no longer provides world class capabilities for measurements with short pulses. In 2011 discussions between the RPI ND group, Naval Reactors, and the Nuclear Criticality Safety Program about the future of the LINAC concluded that maintaining the capability to perform world-class nuclear data measurements at RPI was desirable. To that end, it was decided to refurbish the facility and upgrade the accelerator capabilities to enable high accuracy measurement in the resonance region with narrow neutron pulse and high electron beam power. Located at a major US technical university, this project provides a needed US nuclear data capability for both research and education, and also includes external users and industrial applications.

43 PARTICLE ACCELERATORS↗