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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 379 records · Page 21
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NASA NTRS2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consists of eighty-channel detector plane histograms that accumulate photon counts over time periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey dataset between 14 and 195 keV. Survey data comprises >90% of all BAT data by volume and allows for the tracking of long term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey dataset has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis python package , a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the python code and exemplify its usefulness and accuracy by analyzing survey data from the Crab Pulsar, NGC 2992, and a previously uncataloged MAXI Transient. The BatAnalysis package allows for ∼ 18 years of BAT survey to be used in a systematic way to study a large variety of astrophysical sources.

Tyler Parsotan↗
NASA NTRSDate not supplied

GPCP Version 3.2 Products and Results

The Global Precipitation Climatology Project (GPCP) products address the need for long-term precipitation products that emphasize homogeneity, following Climate Data Record (CDR) principles. The new-generation Version 3.2 provides key improvements over the operational Version 2.3 such as: finer spatial resolution of 0.5°x0.5°; wider geosynchronous infrared estimation (58°N-S) upgraded with the PERSIANN-CDR algorithm; upgraded retrievals from selected passive microwave sensors (GPROF algorithm) that calibrate the IR input; revised intercalibrations of TOVS and AIRS data (used at high latitudes); climatologies based on CloudSat, TRMM, and GPM to provide overall calibration by modern satellite estimates; the latest Global Precipitation Climatology Centre (GPCC) precipitation gauge analyses over land areas; regional modifications to the gauge undercatch correction; and IMERG half-hourly data input to the Daily V3.2 product. We will show sample analyses that demonstrate aspects of the Version 3.2 precipitation record, such as the global climatology, the time series for global land and ocean total precipitation and snowfall, and the time series of tropical land and ocean daily precipitation rate histograms. For selected analyses we will show improvements in both the Monthly and Daily products in Version 3.2 compared to the operational Version 2.3. In particular, the climatological zonal profile of precipitation in the Southern Ocean, extending south of 40°S, improves a suspected artifact in V2.3. Similarly, the Daily histograms over ocean in Version 3.2 lack the jump in the predecessor Version 1.3 Daily over ocean at the start of 2009, although a smaller jump is introduced in June 2014. The presentation will conclude with a prospectus for the future satellites/sensors and community datasets necessary to continue computation of a consistent CDR product on the one hand, while also potentially contributing to improvements in the historical record.

Global Precipitation Measurement↗
NASA NTRSDate not supplied

U.S. IMERG Status

The U.S. Science Team’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) product provides estimates of surface precipitation rate and related information on a global 0.1° half-hour grid. It is run three times at increasingly longer latency and higher information input to serve different communities. This presentation will briefly summarize the major upgrades included in Version 07. The Goddard Profiling (GPROF) algorithm (applied to passive microwave sensor data from the GPM virtual constellation) and the Combined Radar-Radiometer Algorithm (CORRA) that provide input to IMERG V07 are both improved, and the new Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR) algorithm is being applied to infrared data, which employs an additional, warmer infrared temperature threshold than the previous infrared scheme and a deep neural network. V07 has improved bias performance as a result of calibrations that now employ the entire swath widths of CORRA and GPROF GPM Microwave Imager precipitation estimates. As well, time continuity in precipitation features is improved as a result of changes to the Kalman filter that approximately preserve the local histogram of precipitation rates (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN), and that better account for differences in sensor performance. A long-standing bug in the geolocation that shifted grid values 0.1° to the east in the latitude band 70°N-S has been corrected. Other changes in V07 include a hierarchical selection among motion vector sources to address deficiencies in the precipitation propagation near orography, an update to the precipitation phase specification for improved consistency with current inputs, and a renewed effort to implement climatological gauge adjustment to the near-real-time Runs. Early evaluations of V07 IMERG show interesting behavior across the TRMM orbit boost that is highly relevant to the planned orbit boost for the GPM Core observatory.

GPM↗
NASA NTRS2023

Spacecraft Floating Potential Measurements for the Wind Spacecraft

Analysis of 8,804,545 electron velocity distribution functions, observed by the Wind spacecraft near 1 au between 2005 January 1 and 2022 January 1, was performed to determine the spacecraft floating potential, ∅ sc . Wind was designed to be electrostatically clean, which helps keep the magnitude of ∅ sc small (i.e., ∼5–9 eV for nearly all intervals) and the potential distribution more uniform. We observed spectral enhancements of ∅ sc at frequencies corresponding to the inverse synodic Carrington rotation period with at least three harmonics. The two-dimensional histogram of ∅ sc versus time also shows at least two strong peaks, with a potential third, much weaker peak. These peaks vary in time, with the intensity correlated with solar maximum. Thus, the spectral peaks and histogram peaks are likely due to macroscopic phenomena like coronal mass ejections (solar cycle dependence) and stream interaction regions (Carrington rotation dependence). The values of ∅ sc are summarized herein and the resulting data set is discussed.

Lynn B Wilson III↗
DOE OSTI2012

SystemConfidence

SystemConfidence is a benchmark developed at ORNL which can measure statistical variation in which the user can plot. The portions of the code which manage the collection of the histograms and computing statistics on the histograms were designed with the intent that we could use these functions in other codes.

Josh Lothian, Jeff Kuehn↗
DOE OSTI2016

Calculating Reuse Distance from Source Code

The efficient use of a system is of paramount importance in high-performance computing. Applications need to be engineered for future systems even before the architecture of such a system is clearly known. Static performance analysis that generates performance bounds is one way to approach the task of understanding application behavior. Performance bounds provide an upper limit on the performance of an application on a given architecture. Predicting cache hierarchy behavior and accesses to main memory is a requirement for accurate performance bounds. This work presents our static reuse distance algorithm to generate reuse distance histograms. We then use these histograms to predict cache miss rates. Experimental results for kernels studied show that the approach is accurate.

Cache memory↗
DOE OSTI2018

Method and apparatus for detecting dilute concentrations of radioactive xenon in samples of xenon extracted from the atmosphere

A method and apparatus for measuring the concentrations of radioxenon isotopes in a gaseous sample wherein the sample cell is surrounded by N sub-detectors that are sensitive to both electrons and to photons from radioxenon decays. Signal processing electronics are provided that can detect events within the sub-detectors, measure their energies, determine whether they arise from electrons or photons, and detect coincidences between events within the same or different sub-detectors. The energies of detected two or three event coincidences are recorded as points in associated two or three-dimensional histograms. Counts within regions of interest in the histograms are then used to compute estimates of the radioxenon isotope concentrations. The method achieves lower backgrounds and lower minimum detectable concentrations by using smaller detector crystals, eliminating interference between double and triple coincidence decay branches, and segregating double coincidences within the same sub-detector from those occurring between different sub-detectors.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Automatic Surface Defect Detection and Sizing for Superconducting Radio Frequency Cavities using Haar cascades

Serious albeit tiny surface defects can remain on the surface of superconducting radio frequency (SRF) cavities after polishing and cleaning. These defects reduce the efficiency of cavities and often limit the maximum attainable fields. We applied a Haar cascade artificial vision technique for automated identification, counting, and sizing of defects induced on niobium surface by Nb-H precipitates formed at cryogenic temperatures. The defects were counted and sized by a computer program and also counted and measured manually to estimate detection rate and accuracy of sizing. The overall detection rate was 53%, and the overall false positive rate was 29%. The technique that was used to automatically size the features was found to oversize the features, but oversize them consistently, resulting in a size histogram that represents the defect size distribution on the sample. After scaling the histogram data, the average defect area was found to be 90 square micrometers with the standard deviation of 70 square micrometers.

Eremeev, Grigory V.↗
DOE OSTI2019

Time-Resolved PIV Measurements of Flow Field at Diffuser Exit Downstream of a Rotating Detonation Combustor

Time-resolved particle image velocimetry at 30 kHz is applied to the exhaust flow field of a RDC system configured with a diffuser geometry and a converging-diverging (CD) nozzle. The RDC is operated with methane fuel and oxygen-enriched air, motivated by power generation applications. The measured flow-field is discretized into axial and non-axial velocity components. Results are shown to characterize the flow-field across a cord length at the exit plane. Instantaneous contours of the two velocity components, and 1D histograms of velocity components, and 2D histograms of total velocity and tilt angle are shown at multiple locations in the flow. Repeatability of the data is evaluated by comparing tests conducted at similar flow rates. Results are presented for a baseline test case, and test cases showing the effect of reactant higher flow rate and CD nozzle geometry. Finally, the results are compared to a previous RDC study without the diffuser to compare the effectiveness of the diffuser and CD nozzle designs in mitigating the flow periodicity at the combustor exit.

03 NATURAL GAS↗
DOE OSTI2022

Estimating β eff from static, late-time Feynman neutron noise measurements

The effective delayed neutron fraction, β eff , is a kinematic parameter describing the contribution of delayed neutrons to the effective multiplication factor, $\kappa$ eff , and is of great interest to the nuclear criticality safety community and beyond. In fact, $\kappa$ eff presently must be inferred (as opposed to directly measured) since variables like β eff must be obtained from simulation, reference tables, or a dynamic or pulsed measurement where the assembly of fissile material is perturbed and not in steady state. Several recent works have proposed neutron noise techniques to estimate β eff from static measurements (such as benchmark experiments). This work experimentally investigates an approach based on looking at late-time (up to thousands of seconds) correlated neutrons in Feynman histograms. This work utilizes measurements of weapons grade plutonium and highly enriched uranium to construct late-time Feynman histograms and investigate a proposed methodology of estimating β eff from a fit of the distribution. Data is shown from both He-3 detectors and an organic scintillator array. This work is preliminary in nature, demonstrating some experimental feasibility and proposing improvements for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Spherical Kernel Density Estimators For Monte Carlo Radiation Transport Problems

Recently, there has been interest in creating alternatives to histograms (mesh tallies) for estimating spatially-distributed quantities such as scalar flux and reaction rate densities. Kernel Density Estimators (KDEs) are non-parametric estimators that obtain estimates of the underlying distribution at user-defined points without having to specify an underlying mesh, and the uncertainty at those points is independent of the number of tally points used in the simulation. This has led to the investigation of KDEs as an attractive potential alternative to histogram tallies in Monte Carlo radiation transport simulations for reactor physics problems and shielding applications. A KDE was recently created specifically for cylindrical geometries that is capable of producing smooth and accurate estimates of flux and reaction rate densities in reactor physics problems. This work extends the cylindrical KDE and cylindrical Mean Free Path (MFP) KDE to spherical geometries and verifies the spherical KDE on bare and reflected critical benchmark problems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Estimation of uncertainties for subcritical benchmark measurements - 14387

Subcritical measurements are used for many applications including nonproliferation, treaty verification, in-situ monitoring for criticality, and reactor subcriticality monitoring. Most analysis methods involve correlated neutron detection, based upon the property that fission events can create multiple neutrons that are born at nearly the same time (on a scale of 10{sup -13} or 10{sup -14} seconds). Many different time-correlated methods have been used since the 1950's and are still widely utilized today. This particular work describes an uncertainty analysis of measured data using the Hage-Cifarelli formalism of the Feynman Variance-to-Mean method. The Feynman Variance-to-Mean method was introduced by Feynman et al. in 1956 and is based upon the differences between the detector count data and the data that would be expected from measurements taken from a Poissonian source. The Hage-Cifarelli formalism relates moments of the Feynman histograms to several parameters of a system: leakage multiplication (M{sub L}), spontaneous fission rate (F{sub S}), (α,n) neutron emission rate (S{sub α}), detector efficiency (ε), and the moments of the number of neutrons emitted per fission (ν). The first part of the uncertainty method described in this work will show how to determine uncertainties of the first (R{sub 1}) and second (R{sub 2}) reduced factorial moments of the Feynman histograms. The second part of the method will describe how to determine the uncertainties in the other parameters given uncertainties in the reduced factorial moments; in particular, this work will focus on determining the uncertainties in M{sub L} and F{sub S}. This work will utilize measured data from a recent benchmark evaluation with a 4.5 kg sphere of α-phase plutonium to validate the uncertainty analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗
DOE OSTI2020

Computing Potential of the Mean Force Profiles for Ion Permeation Through Channelrhodopsin Chimera, C1C2

Umbrella sampling, coupled with a weighted histogram analysis method (US-WHAM), can be used to construct potentials of mean force (PMFs) for studying the complex ion permeation pathways of membrane transport proteins. Despite the widespread use of US-WHAM, obtaining a physically meaningful PMF can be challenging. Here, we provide a protocol to resolve that issue. Then, we apply that protocol to compute a meaningful PMF for sodium ion permeation through channelrhodopsin chimera, C1C2, for illustration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A unified approach to evaluating precipitation frequency estimates with uncertainty quantification: Application to Florida and California watersheds

Although a variety of climate datasets are now available, including observational and model products, there remains a pressing need for the development of a unified, automated and application-focused approach for evaluating and comparing climate extremes within and across these datasets. Precipitation frequency (PF) es- timates for extreme precipitation events are useful decision-relevant quantities among water managers. Our objective and quantitative framework for computing PF estimates of any duration uses known techniques in a novel combination. Our framework consists of three steps: (1) use of a regionalization-based statistical method for precipitation frequency estimation at observed sites; this involves hierarchical clustering (here we used Ward’s method) for delineating homogeneous regions, and regional frequency analysis using L-moments; (2) use of kriging for spatial mapping because of its advantages over other conventional interpolation methods; (3) use of z-scores accounts for estimation uncertainties when comparing PF estimates between datasets. The 24-h PF estimates in the Kissimmee-Southern Florida watershed (flat topography) and the Sacramento-San Joaquin watershed (complex topography) demonstrate the applicability of this approach in regions of any geographical complexity. Our results are shown to be reasonably calibrated using the probability integral transform (PIT) histogram of the best fitted distribution. Our results are compared with that of the NOAA Atlas 14 reports and show that for most of the stations the two estimates are statistically indistinguishable; and, the confidence intervals of our estimates are narrower than those of the NOAA estimates. Our approach is applicable to a variety of datasets and provides a baseline for assessing performance of climate models in historical simulations – a necessary first step towards analyzing future projections.

58 GEOSCIENCES↗
DOE OSTI2017

Transformations based on continuous piecewise-affine velocity fields

Here, we propose novel finite-dimensional spaces of well-behaved Rn → Rn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization over monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Conductance Steamflow relationship

These histograms represent our calibration of conductance of a volcanic geothermal field (with a clay cap) and the observed steam flow rates. See the following paper for further description: Trainor-Guitton, Hoversten,Nordquist, Intani, Value of information analysis using geothermal field data: accounting for multiple interpretations & determining new drilling locations. SEG Abstracts 2015.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

When to use rsync

We have endeavored to show, using a series of data transfer results obtained from two testbeds, when to use the popular data copying tool rsync and related tools. Tests have been conducted in local area network (LAN) and wide area network (WAN) environments. We conclude that for files in a certain size range and network latency ≦ 10 ms round trip time (RTT), rsync is still useful for data moving tasks in the category 4 of the U.S. DOE Technical Report “Data Movement Categories”. For more demanding data movement requirements, tools of different classes are suggested. Sample histograms from two DOE user facilities are provided to further support our conclusions.

97 MATHEMATICS AND COMPUTING↗