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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 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2025

YeastWGD2025

Supplementary data for Discovery of additional ancient genome duplications in yeasts wgd_syn / - directory containing wgd syn output for all contiguous genomes [dataset] Tree - phylogeny [dataset]Duplications - duplication table from OrthoFinder output KOannotations - KEGG annotations used for enrichment analysis IPRannotations - InterPro annotations used for enrichment analysis DipodascalesOrthogroups - formatted orthogroup assignments for Dipodascales genes.fa and .gff3 files for each new genome assembly are also provided, those these are not required to replicate the analysis

Genomics↗

NASA NTRS1996

New observational facts about particle acceleration and transport during solar flares

Extensive hard X-ray (HXR)/gamma-ray (GR) observations of solar flares, performed during solar cycles 21 and 22 have led to important new discoveries. These data, combined with observations obtained in other parts of the electromagnetic spectrum (soft X-ray, Hard X-ray, optical, and radio) largley contributed to get a better understanding and to develop new ideas on particle acceleration and transport during solar flares. This review presents new observational facts relevant to hard X-ray/gamma-ray producing flares. Among these are the frequent presence of sub-second time structure in the hard X-ray emission, the variability in hard X-ray and radio spatial distributions during a flare and from flare to flare, the evidence for strong gamma-ray line emission from the Corona and the existence of extended phases of the gamma-ray emission lasting for several hours after the flare onset. This ensemble of observations indicates that particle acceleration takes place at different sites in a complex and dynamic magnetic field environment.

Trottel, G.↗

NASA NTRS2013

Fluid Vessel Quantity Using Non-invasive PZT Technology Flight Volume Measurements Under Zero G Analysis

The purpose of the project is to perform analysis of data using the Systems Engineering Educational Discovery (SEED) program data from 2011 and 2012 Fluid Vessel Quantity using Non-Invasive PZT Technology flight volume measurements under Zero G conditions (parabolic Plane flight data). Also experimental planning and lab work for future sub-orbital experiments to use the NASA PZT technology for fluid volume measurement. Along with conducting data analysis of flight data, I also did a variety of other tasks. I provided the lab with detailed technical drawings, experimented with 3d printers, made changes to the liquid nitrogen skid schematics, and learned how to weld. I also programmed microcontrollers to interact with various sensors and helped with other things going on around the lab.

Garofalo, Anthony A↗

NASA NTRS2013

Fluid Vessel Quantity using Non-Invasive PZT Technology Flight Volume Measurements Under Zero G Analysis

Garofalo, Anthony A.↗

NASA NTRS2013

Superorbital Periodic Modulation in Wind-Accretion High-Mass X-Ray Binaries from Swift Burst Alert Telescope Observations

We report the discovery using data from the Swift-Burst Alert Telescope (BAT) of superorbital modulation in the wind-accretion supergiant high-mass X-ray binaries 4U 1909+07 (= X 1908+075), IGR J16418−4532, and IGR J16479−4514. Together with already known superorbital periodicities in 2S 0114+650 and IGR J16493−4348, the systems exhibit a monotonic relationship between superorbital and orbital periods. These systems include both supergiant fast X-ray transients and classical supergiant systems, and have a range of inclination angles. This suggests an underlying physical mechanism which is connected to the orbital period. In addition to these sources with clear detections of superorbital periods, IGR J16393−4643 (= AX J16390.4−4642) is identified as a system that may have superorbital modulation due to the coincidence of low-amplitude peaks in power spectra derived from BAT, Rossi X-Ray Timing Explorer Proportional Counter Array, and International Gamma-Ray Astrophysics Laboratory light curves. 1E 1145.1−6141 may also be worthy of further attention due to the amount of low-frequency modulation of its light curve. However, we find that the presence of superorbital modulation is not a universal feature of wind-accretion supergiant X-ray binaries.

superorbital↗

NASA NTRS2014

Enhancement of Mutual Discovery, Search, and Access of Data for Users of NASA and GEOSS-Cataloged Data Systems

An ongoing NASA-funded Data Rods (time series) project has demonstrated the removal of a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series) for selected variables of the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) and other NASA data sets. Data rods are pre-generated or generated on-the-fly (OTF), leveraging the NASA Simple Subset Wizard (SSW), a gateway to NASA data centers. Data rods Web services are accessible through the CUAHSI Hydrologic Information System (HIS) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) but are not easily discoverable by users of other non-NASA data systems. An ongoing GEOSS Water Services project aims to develop a distributed, global registry of water data, map, and modeling services cataloged using the standards and procedures of the Open Geospatial Consortium and the World Meteorological Organization. Preliminary work has shown GEOSS can be leveraged to help provide access to data rods. A new NASA-funded project is extending this early work.

data access↗

NASA NTRS2014

Timing and Flux Evolution of the Galactic Center Magnetar SGR J1745-2900

We present the X-ray timing and spectral evolution of the Galactic Center magnetar SGR J1745-2900 (SGR*) for the first 4 months post-discovery using data obtained with the Nuclear Spectroscopic Telescope Array (NuSTAR) and Swift observatories. Our timing analysis reveals a large increase in the magnetar spin-down rate by a factor of 2.6 plus or minus 0.07 over our data span. We further show that the change in spin evolution was likely coincident with a bright X-ray burst observed in 2013 June by Swift, and if so, there was no accompanying discontinuity in the frequency. We find that the source 3 to 10 kiloelectronvolt flux has declined monotonically by a factor of approximately 2 over an 80-day period post-outburst accompanied by an approximately 20 percent decrease in the source's blackbody temperature, although there is evidence for both flux and kiloteslas having leveled off. We argue that the torque variations are likely to be magnetospheric in nature and will dominate over any dynamical signatures of orbital motion around Sgr A*.

Stars: magnetic field↗

NASA NTRS2019

NASA Earthdata Knowledge Base

Prototype work for connecting together the main elements of Earth Observation knowledge and context in a way that is: machine-readable, human-usable and curatable. Using the latest in graph technologies and cloud managed services.

earth data↗

NASA NTRSDate not supplied

Creating a knowledge graph to connect scientific publications and datasets for improving discovery of GES DISC’s data and services

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes to the public hundreds of Earth Science data collections. These collections are used in research, resulting in thousands of scientific papers published each year. As new users come to GES DISC for the data, it is important for them to understand how these data were used in the prior research. For this we are creating the Knowledge Graph that connects research paper citation and the data collection metadata. The relationships created in the graph have potential for the Web applications that utilize this information to directly connect the paper research to the GES DISC datasets and services. We will demonstrate these relationships using the Web application prototype.

Nathaniel Ross Crosby↗

NASA NTRSDate not supplied

NASA’s Unsteady Pressure-Sensitive Paint Research and Operational Capability Developments

To address challenges in the field of unsteady aerodynamics, NASA has developed a new state-of-the-art capability called Unsteady Pressure-Sensitive Paint (uPSP). It has been developed as an operational surface-pressure measurement capability for deployment in NASA’s AETC ground test facilities. Offering unprecedented spatiotemporal resolution, uPSP is an extremely powerful tool for investigating unsteady separated flows. To accelerate scientific discovery, uPSP data is to be processed and distributed as rapidly as it is acquired. Several demonstrations of the technology collected valuable data that has been used to develop data products, a robust processing pipeline, and other computational capabilities. A collection of papers documents the most recent research and development work on the uPSP technology and capability. This paper summarizes the current state of this effort at NASA.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

The Science Discovery Engine: An Open Science Success Story

NASA is committed to building an inclusive open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI is made up of a number of activities including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to the wealth of NASA’s open science data and information. In this presentation, we will present our collaborative work to date to build the SDE and our vision for empowering open source science in the future.

Kaylin Bugbee↗

NASA NTRSDate not supplied

NASA’s Unsteady Pressure-Sensitive Paint Research and Operational Capability Developments

To address challenges in the field of unsteady aerodynamics, NASA has developed a new stateof-the-art capability called Unsteady Pressure-Sensitive Paint (uPSP). It has been developed as an operational surface-pressure measurement capability for deployment in NASA’s AETC ground test facilities. Offering unprecedented spatiotemporal resolution, uPSP is an extremely powerful tool for investigating unsteady separated flows. To accelerate scientific discovery, uPSP data is to be processed and distributed as rapidly as it is acquired. Several demonstrations of the technology collected valuable data that has been used to develop data products, a robust processing pipeline, and other computational capabilities. A collection of papers documents the most recent research and development work on the uPSP technology and capability. This paper summarizes the current state of this effort at NASA.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

SBIR Space Weather R2O2R Technology Development and Commercial Applications

The Small Business Innovation Research (SBIR) Program provides U.S. small businesses of 500 or fewer employees with the opportunity for early-stage funding for research and development. Through NASA's Science Mission Directorate, the SBIR subtopic S14.01 Space Weather Research-to-Operations-to-Research (R2O2R) Technology Development and Commercial Applications supports high-priority space weather needs as outlined in the National Space Weather Strategy and Action Plan (NSWSAP). There are four focus areas for which solutions are sought; these will be discussed (in no priority order): 1) space-weather forecasting technologies, techniques, and applications, 2) commercial and decision-making applications for space weather technologies, 3) space weather advanced data-driven discovery techniques, and 4) space-weather instrumentation.

Space weather↗

DOE OSTI2025

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]↗

DOE OSTI2021

Causal Evaluations for Identifying Differences between Observations and Earth System Models

We use a nascent data-driven causal discovery method to find and compare causal relationships in observed data and climate model output. We consider ten different features in the Arctic climate collected from public databases on observational and Energy Exascale Earth System Model (E3SM) data. In identifying and analyzing the resulting causal networks, we make meaningful comparisons between observed and climate model interdependencies. This work demonstrates our ability to apply the PCMCI causal discovery algorithm to Arctic climate data, that there are noticeable similarities between observed and simulated Arctic climate dynamics, and that further work is needed to identify specific areas for improvement to better align models with natural observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

An Integrated Indexing and Search Service for Distributed File Systems

Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure–property relationships. For many properties of interest in materials discovery, the challenging nature and high cost of data generation has resulted in a data landscape that is both scarcely populated and of dubious quality. Data-driven techniques starting to overcome these limitations include the use of consensus across functionals in density functional theory, the development of new functionals or accelerated electronic structure theories, and the detection of where computationally demanding methods are most necessary. When properties cannot be reliably simulated, large experimental data sets can be used to train ML models. In the absence of manual curation, increasingly sophisticated natural language processing and automated image analysis are making it possible to learn structure–property relationships from the literature. Finally, models trained on these data sets will improve as they incorporate community feedback.

36 MATERIALS SCIENCE↗

DOE OSTI2022

First all-flavor search for transient neutrino emission using 3-years of IceCube DeepCore data

Since the discovery of a flux of high-energy astrophysical neutrinos, searches for their origins have focused primarily at TeV-PeV energies. Compared to sub-TeV searches, high-energy searches benefit from an increase in the neutrino cross section, improved angular resolution on the neutrino direction, and a reduced background from atmospheric neutrinos and muons. However, the focus on high energy does not preclude the existence of sub-TeV neutrino emission where IceCube retains sensitivity. Here we present the first all-flavor search from IceCube for transient emission of low-energy neutrinos, focusing on the energy region of 5.6-100 GeV using three years of data obtained with the IceCube-DeepCore detector. We find no evidence of transient neutrino emission in the data, thus leading to a constraint on the volumetric rate of astrophysical transient sources in the range of ~ 705-2301 Gpc -3 yr -1 for sources following a subphotospheric energy spectrum with a mean energy of 100 GeV and a bolometric energy of 1 052 erg.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗