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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TinyTPC: A TEST STAND FOR LAr DOPING

TinyTPC is a small scale liquid-argon time projection chamber (LArTPC) that studies how photosensitive dopants can improve the energy resolution of low energy events in LArTPCs. Bench tests to resolve high voltage breakdown issues and to improve the low voltage system readout are described. Experimental data with a radioactive source of Th-228 for the calibration of the pixelated readout and the characterization of TinyTPC's energy resolution is explained. Provisional results from the addition of isobutylene (photosensitive dopant) and xenon (wavelength shifter) to liquid-argon (LAr) are also presented. Further steps to improve voltage system and enhance the data collection are discussed.

Rodriguez Thorne, Paloma↗
DOE OSTI2025

Achilles and GENIE Model Comparisons Between Quasi-Elastic Proton Exclusive Events in DUNE PRISM ND-LAr

In this study, we analyze simulated CCQE proton exclusive events in DUNE s ND-LAr using Achilles and GENIE Monte Carlo event generators. We generate events using muon neutrino exclusive flux files of DUNE s on-axis and 20m off-axis PRISM positions and compare various kinematics of proton exclusive events between the event generators. Events are further analyzed in categories according to the number of final-state protons. This study was motivated by QE s dominance in statistics for off-axis events over other channels in which off-axis events are very useful for characterizing DUNE s flux. Furthermore, our motivation for comparing results between generators is driven by off-axis QE neutrino spectra peaking below 1 GeV. In this region, many low-energy proton events are produced in which models have been shown to have disagreements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

TinyTPC: A Test Stand for LAr Doping

TinyTPC is a small scale liquid-argon time projection chamber (LArTPC) featuring a pixelated readout system (LArPix) designed to improve the detection of charged particles. To enhance energy measurements at MeV scales, TinyTPC will study the impact of isobutylene, a photosensitive dopant that converts light to charge, and xenon, a wavelength shifter. This presentation will detail TinyTPC's commissioning, operation, data collection methodologies, noise levels, and upcoming tests involving isobutylene, xenon, and radioactive sources.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

TinyTPC: A Test Stand for LAr Doping

LArTPCs are widely used in neutrino experiments at the GeV scale. They measure the charge and light produced by interactions between charged particles and argon atoms. While charge is collected efficiently, light is not. TinyTPC is a small scale LArTPC with a pixelated readout for R&D with photosensitive dopants, which convert light into charge. TinyTPC studies the effects of adding photosensitive dopants and xenon to liquid argon to enhance charge signals of events in the MeV scale.

Rodriguez Thorne, Paloma↗
DOE OSTI2025

Calorimetric Identification of Composite Nuclei in LAr

In neutrino-nucleus interactions, Final State Interactions (FSI) can cause nucleons to scatter or form heavier composite particles like deuterons and tritons. Observing these particles would provide direct evidence of FSI and help improve interaction models, which is essential for precise neutrino energy reconstruction in future experiments like DUNE. Our Goal: Develop an analysis to detect particles heavier than protons in ICARUS data to better constrain FSI models.

McCright, Hannah [Maryland U., College Park]↗
DOE OSTI2025

Commissioning of the trigger system for the ICARUS T600 LAr-TPC detector in SBN Program

The ICARUS experiment at Fermilab is the far detector of the Short Baseline Neutrino Program (SBN), aimed at studing the neutrino oscillation to find a fourth type of neutrino, called sterile neutrino. A key component for this detector is the trigger system, which aims to identify and isolate the physical interactions from the background events. In this framework my internship program was dedicated to the development of trigger logic and trigger inhibit mechanism in order to select the genuine neutrino interaction and to guarantee a correct functioning of the readout system. These two steps, that represent a part of the commissioning of the trigger system, were implemented with LabVIEW Software. The obtained results are a fundamental step towards a succesful activation of the detector in the next few months.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions

Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are particularly useful when a task is separable into distinct steps with a hierarchy of meaningful intermediate representations. In reliability-critical tasks, it is important to quantify the confidence of model inferences. However, chained models pose an additional challenge for uncertainty quantification, especially when input uncertainties need to be propagated. In such cases, a fully uncertainty-aware chain of models is required, where each step accepts a probability distribution over the input space, and produces a probability distribution over the output space. In this work, we present a case study for adapting a single model within an existing chain, designed for reconstruction within neutrino-Argon interactions, developed for neutrino oscillation experiments such as MicroBooNE, ICARUS, and the future DUNE experiment. We test the performance of an input uncertainty-enabled model against an uncertainty-blinded model using a method for generating synthetic noise. By comparing these two, we assess the increase in inference quality achieved by exposing models to upstream uncertainty estimates.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

Application of satellite data and LARS's data processing techniques to mapping vegetation of the Dismal Swamp

The feasibility of using digital satellite imagery and automatic data processing techniques as a means of mapping swamp forest vegetation was considered, using multispectral scanner data acquired by the LANDSAT-1 satellite. The site for this investigation was the Dismal Swamp, a 210,000 acre swamp forest located south of Suffolk, Va. on the Virginia-North Carolina border. Two basic classification strategies were employed. The initial classification utilized unsupervised techniques which produced a map of the swamp indicating the distribution of thirteen forest spectral classes. These classes were later combined into three informational categories: Atlantic white cedar (Chamaecyparis thyoides), Loblolly pine (Pinus taeda), and deciduous forest. The subsequent classification employed supervised techniques which mapped Atlantic white cedar, Loblolly pine, deciduous forest, water and agriculture within the study site. A classification accuracy of 82.5% was produced by unsupervised techniques compared with 89% accuracy using supervised techniques.

Messmore, J. A.↗
NASA NTRS1975

Use of LARS system for the quantitative determination of smoke plume lateral diffusion coefficients from ERTS images of Virginia

A technique for measuring smoke plume of large industrial sources observed by satellite using LARSYS is proposed. A Gaussian plume model is described, integrated in the vertical, and inverted to yield a form for the lateral diffusion coefficient, Ky. Given u, wind speed; y sub l, the horizontal distance of a line of constant brightness from the plume symmetry axis a distance x sub l, downstream from reference point at x=x sub 2, y=0, then K sub y = u ((y sub 1) to the 2nd power)/2 x sub 1 1n (x sub 2/x sub 1). The technique is applied to a plume from a power plant at Chester, Virginia, imaged August 31, 1973 by LANDSAT I. The plume bends slightly to the left 4.3 km from the source and estimates yield Ky of 28 sq m/sec near the source, and 19 sq m/sec beyond the bend. Maximum ground concentrations are estimated between 32 and 64 ug/cu m. Existing meteorological data would not explain such concentrations.

Blais, R. N.↗