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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Radio Afterglow Detection and AI-driven Response (RADAR): A Federated Framework for Gravitational-wave Event Follow-up

The landmark detection of both gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 has spurred efforts to streamline the follow-up of GW alerts in current and future observing runs of ground-based GW detectors. Within this context, the radio band of the EM spectrum presents unique challenges. Sensitive radio facilities capable of detecting the faint radio afterglow seen in GW170817, and with sufficient angular resolution, have small fields of view compared to typical GW localization areas. Additionally, theoretical models predict that the radio emission from binary neutron star mergers can evolve over weeks to years, necessitating long-term monitoring to probe the physics of the various postmerger ejecta components. These constraints, combined with limited radio observing resources, make the development of more coordinated follow-up strategies essential—especially as the next generation of GW detectors promises a dramatic increase in detection rates. Here, we present RADAR, a framework designed to address these challenges by promoting community-driven information sharing, federated data analysis, and system resilience, while integrating AI methods for both GW signal identification and radio data aggregation. We show that it is possible to preserve data rights while sharing models that can help design and/or update follow-up strategies. We demonstrate our approach through a case study of GW170817, and discuss future directions for refinement and broader application.

Gravitational waves↗
DOE OSTI2021

SANS quantification of bound water in water-soluble polymers across multiple concentration regimes

Contrast-variation small-angle neutron scattering (CV-SANS) is a widely used technique for quantifying hydration water in soft matter systems, but it is predominantly applied in the dilute regime or for systems with a well-defined structure factor. Here, CV-SANS was used to quantify the number of hydration water molecules associating with three water-soluble polymers with different critical solution temperatures and types of water–solute interactions in dilute, semidilute, and concentrated solution through the exploration of novel methods of data fitting and analysis. Multiple SANS fitting workflows with varying levels of model assumptions were evaluated and compared to give insight into SANS model selection. These fitting pathways ranged from general, model-free algorithms to more standard form and structure factor fitting. In addition, Monte Carlo bootstrapping was evaluated as a method to estimate parameter uncertainty through simulation of technical replicates. The most robust fitting workflow for dilute solutions was found to be form factor fitting without CV-SANS ( i.e. polymer in 100% D 2 O). For semidilute and concentrated solutions, while the model-free approach can be mathematically defined for CV-SANS data, the addition of a structure factor imposes physical constraints on the optimization problem, suggesting that the optimal fitting pathway should include appropriate form and structure factor models. The measured hydration numbers were consistent with the number of tightly bound water molecules associated with each monomer unit, and the concentration dependence of the hydration number was largely governed by the chemistry-specific interactions between water and polymer. Polymers with weaker water–polymer interactions ( i.e. those with fewer hydration water molecules) were found to have more bound water at higher concentrations than those with stronger water–polymer interactions due to the increase in the number of forced water–polymer contacts in the concentrated system. This SANS-based method to count hydration water molecules can be applied to polymers in any concentration regime, which will lead to improved understanding of water–polymer interactions and their impact on materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Wavelet Denoising of Radio Observations of Rotating Radio Transients (RRATs): Improved Timing Parameters for Eight RRATs

Rotating radio transients (RRATs) are sporadically emitting pulsars detectable only through searches for single pulses. While over 100 RRATs have been detected, only a small fraction (roughly 20%) have phase-connected timing solutions, which are critical for determining how they relate to other neutron star populations. Detecting more pulses in order to achieve solutions is key to understanding their physical nature. Astronomical signals collected by radio telescopes contain noise from many sources, making the detection of weak pulses difficult. Applying a denoising method to raw time series prior to performing a single-pulse search typically leads to a more accurate estimation of their times of arrival (TOAs). Taking into account some features of RRAT pulses and noise, we present a denoising method based on wavelet data analysis, an image-processing technique. Assuming that the spin period of an RRAT is known, we estimate the frequency spectrum components contributing to the composition of RRAT pulses. This allows us to suppress the noise, which contributes to other frequencies. We apply the wavelet denoising method including selective wavelet reconstruction and wavelet shrinkage to the de-dispersed time series of eight RRATs with existing timing solutions. The signal-to-noise ratio (S/N) of most pulses are improved after wavelet denoising. Compared to the conventional approach, we measure 12%–69% more TOAs for the eight RRATs. The new timing solutions for the eight RRATs show 16%–90% smaller estimation error of most parameters. Thus, we conclude that wavelet analysis is an effective tool for denoising RRATs signal.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Online Rapid Analysis of Laser Heterodyne Radiometer (LHR) Data Using the Planetary Spectrum Generator (PSG)

One of the biggest challenges in developing scientific instruments is not just the build and testing of an instrument, but the method for processing the data and producing a consistent, well characterized data product that can be confidently used by the public and scientific community. Raw data products are frequently an array of numbers that are a read-out of voltages. The challenge is to convert these arrays into meaningful information as well as remove noise and interferences. Because this can be a tedious and time-consuming, the goal is to automate the process so that data ca be processed rapidly and be available in real-time for event monitoring. Here we present a rapid analysis method for Laser Heterodyne Radiometer (LHR) data that can be used to analyze data taken from a range of LHR observation modes (column, limb, etc.). This online tool uses the versatile Planetary Spectrum Generator (PSG) and allows LHR users to quickly analyze their own data using a NASA Goddard Space Flight Center (GSFC) monitored capability to ensure quality and reproducibility in the data products. Background: Development of a miniaturized LHR (mini-LHR) as a ground instrument for measuring carbon dioxide (CO 2 ) and methane (CH 4 ) in the atmospheric column started in 2009 with the commercial availability of distributive feedback lasers (DFB) in wavelengths that could measure absorption of gases in the near-IR. As new DFB lasers, detectors and hardware emerged at different wavelengths, additional gases were added to the capability. The mini-LHR was adapted into an occultation-viewing CubeSat with Lawrence Livermore National Laboratory (LLNL) for observing CO 2 , CH 4 , and H 2 O in the limb and was launched in 2019. Other versions of the LHR technology have been designed for observation of water vapor in the lunar exosphere as well as observations of trace gases in planetary atmospheres and plumes from icy moons. The PSG is an online tool developed at GSFC that can be used for synthesizing Earth and planetary spectra (atmospheres and surfaces) over a broad range of wavelengths (0.1 μm to 100 mm) for any observatory, orbiter or lander. Spectra are simulated by combining several state-of-the-art radiative transfer models, spectroscopic databases, planetary databases, as well as modern-era retrospective analysis for research and applications, version 2 (MERRA-2) data set which provides meteorological inputs such as modeled surface pressure for calculating dry-air columns.

Emily Wilson↗
NASA NTRS1976

Tidal analysis of Met rocket wind data

A method of analyzing Met Rocket wind data is described. Modern tidal theory and specialized analytical techniques were used to resolve specific tidal modes and prevailing components in observed wind data. A representation of the wind which is continuous in both space and time was formulated. Such a representation allows direct comparison with theory, allows the derivation of other quantities such as temperature and pressure which in turn may be compared with observed values, and allows the formation of a wind model which extends over a broader range of space and time. Significant diurnal tidal modes with wavelengths of 10 and 7 km were present in the data and were resolved by the analytical technique.

Bedinger, J. F.↗
NASA NTRS1951

Analysis of Experimental Sea-level Transient Data and Analog Method of Obtaining Altitude Response for Turbine-propeller Engine with Relay-type Speed Control

Correlation has been established between transient engine and control data obtained experimentally and data obtained by simulating the engine and control with an analog computer. This correlation was established at sea-level conditions for a turbine-propeller engine with a relay-type speed control. The behavior of the controlled engine at altitudes of 20,000 and 35,000 feet was determined with an analog computer using the altitude pressure and temperature generalization factors to calculate the new engine constants for these altitudes. Because the engine response varies considerably at altitude some type of compensation appears desirable and four methods of compensation are discussed.

ENGINES, CONTROL↗
DOE OSTI2015

Absolute photoneutron cross sections of Sm isotopes

Photoneutron cross sections for seven samarium isotopes, {sup 144}Sm, {sup 147}Sm, {sup 148}Sm, {sup 149}Sm, {sup 150}Sm, {sup 152}Sm and {sup 154}Sm, have been investigated near neutron emission threshold using quasimonochromatic laser-Compton scattering γ-rays produced at the synchrotron radiation facility NewSUBARU. The results are important for nuclear astrophysics calculations and also for probing γ-ray strength functions in the vicinity of neutron threshold. Here we describe the neutron detection system and we discuss the related data analysis and the necessary method improvements for adapting the current experimental method to the working parameters of the future Gamma Beam System of Extreme Light Infrastructure - Nuclear Physics facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1997

Method of calibrating an interferometer and reducing its systematic noise

Methods of operation and data analysis for an interferometer so as to eliminate the errors contributed by non-responsive or unstable pixels, interpixel gain variations that drift over time, and spurious noise that would otherwise degrade the operation of the interferometer are disclosed. The methods provide for either online or post-processing calibration. The methods apply prescribed reversible transformations that exploit the physical properties of interferograms obtained from said interferometer to derive a calibration reference signal for subsequent treatment of said interferograms for interpixel gain variations. A self-consistent approach for treating bad pixels is incorporated into the methods.

Hammer, Philip D.↗
NASA NTRS2004

Uncertainty-Based Approach for Dynamic Aerodynamic Data Acquisition and Analysis

Development of improved modeling methods to provide increased fidelity of flight predictions for aircraft motions during flight in flow regimes with large nonlinearities requires improvements in test techniques for measuring and characterizing wind tunnel data. This paper presents a method for providing a measure of data integrity for static and forced oscillation test techniques. Data integrity is particularly important when attempting to accurately model and predict flight of today s high performance aircraft which are operating in expanded flight envelopes, often maneuvering at high angular rates at high angles-of-attack, even above maximum lift. Current aerodynamic models are inadequate in predicting flight characteristics in the expanded envelope, such as rapid aircraft departures and other unusual motions. Present wind tunnel test methods do not factor changes of flow physics into data acquisition schemes, so in many cases data are obtained over more iterations than required, or insufficient data may be obtained to determine a valid estimate with statistical significance. Additionally, forced oscillation test techniques, one of the primary tools used to develop dynamic models, do not currently provide estimates of the uncertainty of the results during an oscillation cycle. A method to optimize the required number of forced oscillation cycles based on decay of uncertainty gradients and balance tolerances is also presented.

Heim, Eugene H. D.↗
DOE OSTI2015

Gravitational waves from rotating neutron stars: Current limits and prospects

Rotating neutron stars that emit continuous gravitational waves are among promising targets of the LIGO and Virgo detectors: sufficiently large non-axisymmetrie deformation w.r.t. the axis of rotation of a star generates a time-varying mass-quadrupole moment and henceforth gravitational wave emission. The departure from an axisymmetrie shape may be caused by the internal magnetic field and/or elastic stresses in the crust/core. If detected, it will provide novel insight into the presently obscured details of the interior neutron-star structure. This talk presents basic types of searches for such signals: from targeted searches from known pulsars to all-sky wide parameter searches for unknown objects. Selected methods used in the data analysis and to calculate the upper limits on the gravitational waves in the initial phase of LIGO and Virgo projects are briefly described. Observational results of LIGO and Virgo collaborations include “beating” the spin-down limit for the Crab and Vela pulsars [7, 11], search for a coherent signal from the direction of the Cas A supernova remnant [5], as well as the Galactic center [1], SN1987A and the Sco-X1 binary with the cross-correlation method [6], and the all-sky searches for signals of unknown position and frequency [2, 4, 8].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Production and discovery of neutron-rich isotopes by fragmentation of 198 Pt

Production cross sections were measured for fragments produced by an 85 MeV/u 198 Pt beam incident on a beryllium target. Event-by-event particle identification of A, Z, and q for the reaction products was performed by employing energy loss, time-of-flight, magnetic rigidity, and total kinetic energy measurements. Over 70 nuclei in the Hf-Pt region were identified, including three isotopes first observed in this work: 191,192 Hf and 189 Lu. Due to the existence of multiple charge states between H-like and C-like ions, a new analysis method was introduced, incorporating Monte Carlo calculations of charge state fractions for a given charge state of the projectile residue just after the reaction. For the first time, charge-state probability distribution functions after the reaction have been deduced from experimental data. Furthermore, this study provides insight into how to produce key nuclides near N = 126 and the ability of a fragmentation residue to retain electrons from the primary beam.

190 ≤ A ≤ 219↗
DOE OSTI2025

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Performance Risk Model Validation with Operationally Relevant Tasks

Human Research Program aims to develop methods to support astronauts’ health and productivity during spaceflight. The Crew Health and Performance Probabilistic Risk Assessment (CHP-PRA) team uses powerful computational methods to predict mission risk in both domains: medical and performance. Here, we show how CHP-PRA uses the Performance Risk Model (PRisM) to quantify the performance risk and show an application of the model on operationally relevant tasks. There are various metrics adopted across performance researchers that PRisM can accommodate. For data analysis, interpretation, and integration, we use a method of unifying data from multiple sources by converting each to a single metric. We consult subject matter experts prior to integrating the converted data into PRisM. The method we use is inspired by the Cooper-Harper rating scale [1]. Using this unified metric, we can easily combine data from various tests and lab groups. We explain our conversion method in detail and show how it pertains to the process of testing and validation of PRisM on operational tasks. We conducted an initial validation in collaboration with the Behavioral Health and Performance (BHP) lab. We test PRisM using data on their operationally relevant task ROBoT-r, a track-and-capture task for grappling incoming resupply vehicles [2]. Several other labs at NASA Johnson Space Center worked together to design 7 Functional Task Tests (FTTs) in pursuit of simulating the tasks required after landing on a planetary surface and after return to Earth [3]. Here we use the results from both ROBoT-r and the 7 FTTs and compare their experiment data to PRisM’s computational output to demonstrate how PRisM can support operations by predicting crew performance on future missions.

performance modeling↗
NASA NTRS1989

Improved method of analyzing hot-wire measurements in supersonic turbulence

The present analysis method for hot-wire data in supersonic turbulence takes sound field effects into account and yields greater accuracy in its treatment of flow variable fluctuations than existing methods despite requiring only a moderately accurate estimate of static pressure fluctuations. The method demonstrates the way in which neglecting pressure fluctuations will affect hot-wire data analysis, as well as indicating the probable direction the errors will take.

Logan, Pamela↗
NASA NTRS2006

Design Parameters Influencing Reliability of CCGA Assembly: A Sensitivity Analysis

Area Array microelectronic packages with small pitch and large I/O counts are now widely used in microelectronics packaging. The impact of various package design and materials/process parameters on reliability has been studied through extensive literature review. Reliability of Ceramic Column Grid Array (CCGA) package assemblies has been evaluated using JPL thermal cycle test results (-50(deg)/75(deg)C, -55(deg)/100(deg)C, and -55(deg)/125(deg)C), as well as those reported by other investigators. A sensitivity analysis has been performed using the literature da to study the impact of design parameters and global/local stress conditions on assembly reliability. The applicability of various life-prediction models for CCGA design has been investigated by comparing model's predictions with the experimental thermal cycling data. Finite Element Method (FEM) analysis has been conducted to assess the state of the stress/strain in CCGA assembly under different thermal cycling, and to explain the different failure modes and locations observed in JPL test assemblies.

reliability↗
DOE OSTI2018

Results from the Atacama B-mode Search (ABS) experiment

We report the Atacama B-mode Search is an experiment designed to measure the cosmic microwave background polarization at large angular scales (0ℓ>4). It observes at 145 GHz from a site at 5,190 m elevation in northern Chile. The noise equivalent polarization temperature, or NEQ, is 41 μK√s. One of the unique features of ABS is its use of a rapidly rotating ambient-temperature half-wave plate (HWP) {as the first optical element}. {The HWP spins} at 2.55 Hz to modulate the incident polarized signal at frequencies above where instrument white noise dominates over atmospheric fluctuations and other sources of low-frequency noise. We report here on the analysis of data from a 2,400 deg 2 region of sky. We perform a blind analysis to reduce potential bias. After unblinding, we find agreement with the Planck TE and EE measurements on the same region of sky, {with a derived calibration factor of 00.89 ± 0.1}. We marginally detect polarized dust emission {(at 3.2 σ for EE and 2.2 σ for BB)} and give an upper limit on the tensor-to-scalar ratio of r<2.3 (95% confidence level) with the equivalent of 100 on-sky days of observation. Finally, we also present a new measurement of the polarization of Tau A and introduce new methods for calibration and data analysis associated with HWP-based observations.

79 ASTRONOMY AND ASTROPHYSICS↗