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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Characterization of the IOTA Proton Source

This project focuses on characterizing the IOTA proton source through changing the parameters of four various components of the Low Energy Beam Transport (LEBT). Because of an inecient lament, current was limited to 2 mA when 40 mA is ultimately desired. Through an investigation of the solenoids and trims of the LEBT, we sought more knowledge about the optimum settings for running the IOTA proton source.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Characterization of the IOTA Proton Source

This project focuses on characterizing the IOTA proton source through changing the parameters of four components of the Low Energy Beam Transport (LEBT). It is important to note that the filament used in testing was emission limited. Because of an inefficient filament, current was limited to 2mA when 40mA is ultimately desired. Through an investigation of the solenoids and trims of the LEBT, we sought more knowledge about the optimum settings for running the IOTA proton source.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Design and characterization of Ion sources for CHIP-TRAP

At Central Michigan University, we are developing a high-precision Penning trap mass spectrometer (CHIP-TRAP) for precise mass measurements with stable and long-lived isotopes. Ions will be produced using external ion sources and then transported to the Penning trap at low energy using electrostatic ion optics. Ion sources that will be utilized with CHIP-TRAP include a laser ablation ion source (LAS) that has already been commissioned, and a low current Penning ion trap (PIT) source that is currently being developed. The LAS enables ion production from solid targets via ablation and ionization with a high-powered laser pulse. The PIT source is a novel Penning ionization gauge (PIG) type source, consisting of a 0.55 T NdFeB ring magnet, cylindrical Penning trap, and low current thermal electron emitter that enables ion production via electron impact ionization of gaseous samples. For both ion sources, small bunches of ~100 – 1000 ions can be produced from a minimal sample of source material. Finally, the ion bunches are then transported along the CHIP-TRAP beamline, where time-of-flight mass filtering can be performed before they are captured in the CHIP-TRAP Penning traps.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

A novel, steerable, low-energy proton source for detector characterization

We report on the conversion of the Manitoba II mass spectrometer into a versatile low-energy proton beam facility. This infrastructure is adaptable to any detector-under-test (DUT), and has proven itself effective with the characterization of silicon detectors used in subatomic beyond-the-Standard-Model (BSM) searches, namely the Nab experiment. A pencil beam of mono-energetic protons can be produced in a range from 25 keV to 35 keV, achieving a beam current of ~1 x 10 -18 A. Electrostatic steering plates were constructed to direct the Gaussian-profile proton beam over a 117 mm diameter area-of-interest with full-width at half-maxima (FWHM) ranging from 0.6 mm to 1.26 mm. This work discusses the modifications and subsequent tests to confirm the beam specifications met the demands of the aforementioned detectors.

Fundamental neutron physics↗
DOE OSTI2018

Identification and Characterization of Dust Source Regions Across North Africa and the Middle East Using MISR Satellite Observations

Abstract Motivated by limitations in current satellite‐based dust source identification techniques, this study examines dust emissions and concentrations over North Africa and the Middle East during 2000–2016 by analyzing stereo and optical products from the Multiangle Imaging SpectroRadiometer instrument on the National Aeronautics and Space Administration polar‐orbiting Terra satellite. Based on the occurrence of fast‐moving, near‐surface dust plumes from the Multiangle Imaging SpectroRadiometer cloud motion vector product, dust sources in the study region are identified in geographical depressions, including the Bodélé Depression, which represents the leading source. The West African El Djouf desert generates substantial dust emissions, which are typically underestimated by aerosol loading‐based dust source identifications. In response to local vegetation cover anomalies, dust emissions and concentrations increased at 15% year −1 over the Middle East and decreased at 12% year −1 over the central Sahel during 2001–2013 but partly recovered toward their climatological means afterward.

Yu, Yan↗
DOE OSTI2016

First hydrogen operation of NIO1: Characterization of the source plasma by means of an optical emission spectroscopy diagnostic

NIO1 (Negative Ion Optimization 1) is a compact and flexible radio frequency H{sup −} ion source, developed by Consorzio RFX and INFN-LNL. The aim of the experimentation on NIO1 is the optimization of both the production of negative ions and their extraction and beam optics. In the initial phase of its commissioning, NIO1 was operated with nitrogen, but now the source is regularly operated also with hydrogen. To evaluate the source performances, an optical emission spectroscopy diagnostic was installed. The system includes a low resolution spectrometer in the spectral range of 300-850 nm and a high resolution (50 pm) one, to study, respectively, the atomic and the molecular emissions in the visible range. The spectroscopic data have been interpreted also by means of a collisional-radiative model developed at IPP Garching. Besides the diagnostic hardware and the data analysis methods, the paper presents the first plasma measurements across a transition to the full H mode, in a hydrogen discharge. The characteristic signatures of this transition in the plasma parameters are described, in particular, the sudden increase of the light emitted from the plasma above a certain power threshold.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Square Kilometre Array Science Data Challenge 1: analysis and results

ABSTRACT As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality data sets for testing and evaluating new techniques. In this paper, we present a description and results from the first such Science Data Challenge 1 (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560, 1400, and 9200 MHz) at three depths (8, 100, and 1000 h), SDC1 asked participants to apply source detection, characterization, and classification methods to simulated data. The challenge opened in 2018 November, with nine teams submitting results by the deadline of 2019 April. In this work, we analyse the results for eight of those teams, showcasing the variety of approaches that can be successfully used to find, characterize, and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.

Bonaldi, A.↗
DOE OSTI2024

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at s N N = 5.02 TeV

Two-particle Bose–Einstein momentum correlation functions are studied for charged-hadron pairs in lead-lead collisions at a center-of-mass energy per nucleon pair of s NN = 5.02 TeV . The data sample, containing 4.27 × 10 9 minimum bias events corresponding to an integrated luminosity of 0.607 nb − 1 , was collected by the CMS experiment in 2018. The experimental results are discussed in terms of a Lévy-type source distribution. The parameters of this distribution are extracted as functions of particle pair average transverse mass and collision centrality. These parameters include the Lévy index or shape parameter α , the Lévy scale parameter R , and the correlation strength parameter λ . The source shape, characterized by α , is found to be neither Cauchy nor Gaussian, implying the need for a full Lévy analysis. Similarly to what was previously found for systems characterized by Gaussian source radii, a hydrodynamical scaling is observed for the Lévy R parameter. The λ parameter is studied in terms of the core-halo model. ©2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Metrics and Methods for Radiation Detection Algorithm Characterization for Nuclear/Radiological Source Search

This report presents a series of recommendations for data to train and evaluate radiation detection algorithms and performance metrics to evaluate these algorithms. These recommendations were formed through a community consensus approach through the Detection Radiation Algorithms Group (DRAG), a multi-institution collaboration spanning eight Department of Energy laboratories and John Hopkins Applied Physics Laboratory. This report includes recommendations on background data variability, and metrics to quantify variability, sources and shielding configurations to include in data collection campaigns and detector response variability. In addition, this report describes several anomaly detection and identification algorithms and recommends metrics to report their performance. Finally, this report ends with a discussion on machine learning algorithms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Accelerating fissile material detection with a neutron source

A system discriminating fissile material from nonfissile material wherein a digital data acquisition unit collects data at high rate, and processes large volumes of data directly to count neutrons from the unknown source and detect excess grouped neutrons to identify fission. The system includes a Poisson neutron generator for in-beam interrogation of a possible fissile neutron source and inducing neutron emission therefrom, and a DC power supply that exhibits electrical ripple of less than one part per million. A neutron count histogram and Poisson count distribution are overlaid to provide a visual indication of the difference in correlation of natural and induced emitted neutrons from the radiation source to characterize the neutron source as fissile material or non-fissile material.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Accelerating fissile material detection with a neutron source

A method of discriminating fissile material from non-fissile material with a digital data acquisition system that collects data at high rate, and processes large volumes of data directly to count neutrons from the unknown source and detect excess grouped neutrons to identify fission. The system includes a Poisson neutron generator for in-beam interrogation of a possible fissile neutron source and inducing neutron emission therefrom, and a DC power supply that exhibits electrical ripple of less than one part per million. A neutron count histogram and Poisson count distribution are overlaid to provide a visual indication of the difference in correlation of natural and induced emitted neutrons from the radiation source to characterize the neutron source as fissile material or non-fissile material.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

An Open-Source Framework for Characterizing Urban Energy Models: Integrating Top-Down and Bottom-Up Methods to Predict Residential Buildings Characteristics: Preprint

Bottom-up urban energy models are crucial for understanding current energy use patterns and informing design strategies. However, accurately characterizing these models to represent different communities remains a challenge due to the extensive data needed for simulating existing energy use behavior. This data includes information related to human activities and building characteristics, all of which correlate with socioeconomic factors. To overcome this challenge, we developed an automated framework that utilizes both top-down and bottom-up data, to predict unknown building and occupant characteristics that are needed for more accurate and equitable modeling and analytics. Our framework, integrated into the URBANopt district energy modeling platform, uses statistical data models from ResStock. URBANopt models co-located buildings and neighborhoods. At this scale there are data gaps in building characteristic data, such as materials, insulation, occupancy, income, and energy usage of the buildings. To address this data gap, we use ResStock data, representative at the census tract scale, and develop machine-learning and deeplearning techniques to disaggregate it to individual buildings. By mapping unique occupant, building and economic properties to URBANopt energy models, we gain detailed insights into the variability of building energy use across different neighborhoods. This insight helps deploy technologies for co-located buildings and supports targeted upgrades for communities with unique economic and demographic characteristics, ensuring energy equity. Accurate characterization of energy models allows us to develop equitable strategies tailored to diverse neighborhoods, whether underserved or affluent. Our automated framework streamlines energy modeling and provides a reliable tool for building energy characterization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗