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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 NTRS2001

POLAR/CEPPAD Data Analysis

This final report provides a final report on a NASA sponsored project involving data reduction and scientific analysis related to the Comprehensive Energetic Particle Pitch Angle Distribution (CEPPAD) experiment of POLAR. Dr. D.N. Baker, the chief scientist, has focused primarily on the calibration of CEPPAD sensors and the interpretation of data from the sensors which has led to discoveries regarding storm-substorm relationships in the earth's magnetosphere. The report contains approximately 190 bibliographic references to the activities of Baker and others involved.

Baker, D. N.↗
NASA NTRS1973

Documentation of the data analysis system for the gamma ray monitor aboard OSO-H

The programming system is presented which was developed to prepare the data from the gamma ray monitor on OSO-7 for scientific analysis. The detector, data, and objectives are described in detail. Programs presented include; FEEDER, PASS-1, CAL1, CAL2, PASS-3, Van Allen Belt Predict Program, Computation Center Plot Routine, and Response Function Programs.

Croteau, S.↗
NASA NTRS1973

D-region blunt probe data analysis using hybrid computer techniques

The feasibility of performing data reduction techniques with a hybrid computer was studied. The data was obtained from the flight of a parachute born probe through the D-region of the ionosphere. A presentation of the theory of blunt probe operation is included with emphasis on the equations necessary to perform the analysis. This is followed by a discussion of computer program development. Included in this discussion is a comparison of computer and hand reduction results for the blunt probe launched on 31 January 1972. The comparison showed that it was both feasible and desirable to use the computer for data reduction. The results of computer data reduction performed on flight data acquired from five blunt probes are also presented.

Burkhard, W. J.↗
NASA NTRS2001

ISO Guest Observer Data Analysis and LWS Instrument Team Activities

The following is an interim annual report. Dr. Smith is currently on an extended TDY to the Istituto di Fisica dello Spazio Interplanetario (IFSI) at the Consilio Nazionale delle Richerche (CNR) in Rome, Italy, where he has been working on a related NASA grant in support of analysis of Infrared Space Observatory (ISO) data on star formation in Ultra Luminous Infrared Galaxies and our galaxy. Work emphasizes development of metal mesh grids for use in spacecraft, and the design and fabrication of test elements by the Naval Research Laboratory, Washington D.C. Work has progressed well, but slowly, on that program due to the departure of a key engineer. NASA has been advised of the delay, and granted a no-cost extension, whereby SAO has authorized a delay in the final report from NRL. Nevertheless NRL has continued to make progress. Two papers have been submitted to refereed journals related to this program, and a new design for mesh operating in the 20-40 micron region has been developed. Meetings continue through the summer on these items. A new technical scientist has been made a job offer and hopefully will be on board NRL shortly, although most of the present grant work is already completed. A more complete report, with copies of the submitted papers, designs, and other measures of progress, will be submitted to NASA in September when Dr. Smith returns from his current TDY.

Smith, Howard↗
NASA NTRS2012

Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis

MapReduce is an approach to high-performance analytics that may be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. We are particularly interested in the potential of MapReduce to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we are prototyping a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. Our initial focus has been on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. Preliminary results suggest this approach can improve efficiencies within data intensive analytic workflows.

Duffy, Daniel Q.↗
NASA NTRS2025

An Efficient GPU-Accelerated Multi-Source Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analysing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains Massive Black Hole Binaries, compact Galactic Binaries, and a parameterized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble MCMC sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or trans-dimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data. We recover posterior distributions for all 15 (6) of the injected MBHBs in the LDC2A training (hidden) dataset. We catalog ∼12000 Galactic Binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA global fit↗
NASA NTRSDate not supplied

SAGE III/ISS Rapid Data Analysis Through Dashboarding with Jupyter Notebooks

Spaceborne remote sensing observations of Earth’s atmosphere produce significant quantities of data over the life of each mission. In the case of the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) nearly four years of vertical profiles of atmospheric ozone, water vapor, and nitrogen dioxide concentrations as well as aerosol extinction coefficients have been released. The dichotomy of the desire for both long-term trends in the atmospheric state alongside the assessment of short-term impacts of major disruptive events such as volcanic eruptions and pyrocumulus injections requires agile tools to handle these cases in near real-time as new data are produced. The analysis landscape is further complicated by the desire to compare results between the numerous contemporary observations available for a given dataset. The SAGE III/ISS team has developed a suite of tools leveraging modern web-based frameworks allowing members to interact with a dashboard-style interface to load the data record, assess new profiles as they are generated and in ensemble, compare between species, and additionally add in measurements observed by other platforms as necessary. Leveraging a commonly packaged data format of NetCDF alongside the Python Jupyter Notebook framework, the data can be served to interested parties from an analysis server while still runnable on personal systems if required. This presentation illustrates the ecosystem developed by the SAGE III/ISS team, the applicability to measurements made by any limb-observing platform, and the benefit to transforming routine analyses into readily accessible dynamic plots. Frameworks currently exist at larger scales with projects such as GIOVANNI, and this illustration seeks to show that similar frameworks are accessible and possible within the local research environment while simultaneously unloading human processing cycles for more specialized analysis tasks.

Dashboarding↗
NASA NTRS1992

ICE/ISEE plasma wave data analysis

The interval reported on, from Jan. 1990 to Dec. 1991, has been one of continued processing and archiving of ICE plasma wave (pw) data and transition from analysis of ISEE 3 and ICE cometary data to ICE data taken along its cruise trajectory, where coronal mass ejections are the focus of attention. We have continued to examine with great interest the last year of ISEE 3's precomet phase, when it spent considerable time far downwind from Earth, recording conditions upstream, downstream, and across the very weak, distant flank bow shock. Among other motivations was the apparent similarity of some shock and post shock structures to the signatures of the bow wave surrounding comet Giacobini-Zinner, whose ICE-phase data was revisited. While pursuing detailed, second-order scientific inquiries still pending from the late ISEE 3 recordings, we have also sought to position ourselves for study of CME's by instituting a data processing format new to the ISEE 3/ICE pw detector. Processed detector output has always been summarized and archived in 24-hour segments, with all pw channels individually plotted and stacked one above the next down in frequency, with each channel calibrated separately to keep all data patterns equally visible in the plots, regardless of gross differences in energy content at the various frequencies. Since CME's, with their preceding and following solar wind plasmas, can take more than one day to pass by the spacecraft, a more condensed synoptic view of the pw data is required to identify, let alone assess, CME characteristics than has been afforded by the traditional routines. This requirement is addressed in a major new processing initiative in the past two years. Besides our own ongoing and fresh investigations, we have cooperated, within our resources, with studies conducted extramurally by distant colleagues irrespective of the phase of the ISEE 3/ICE mission under scrutiny. The remainder of this report summarizes our processing activities, our investigations, both internal and cooperative, our scientific results, and our publication activity.

Greenstadt, E. W.↗
NASA NTRS1998

SOHO Ultraviolet Coronagraph Spectrometer (UVCS) Mission Operations and Data Analysis

The scientific goal of UVCS is to obtain detailed empirical descriptions of the extended solar corona as it evolves from a period of minimum activity to maximum and to use these descriptions to identify and understand the physical processes responsible for coronal heating, solar wind acceleration, coronal mass ejections (CME's), and the phenomena that establish the plasma properties of the solar wind as measured by the CELIAS/SOHO experiment. We must observe a wide range of conditions (e.g., heating rate, impulsive mass ejections, magnetic field opening) in order to choose among competing theoretical explanations of the observed coronal structures and dynamics. During the first year of scientific observations (1 April 1996 through 31 March 1997), the LTVCS made the first extensive ultraviolet spectroscopic observations above the base of the solar corona. Those observations revealed extremely high most probable speeds along the line of sight for O(5+) in polar coronal holes above 2 solar radii from sun center and smaller such speeds for H(0) and protons. Doppler dimming and pumping diagnostics indicated that O(5+) and H(0) I reached supersonic outflow velocities within 2 solar radii. The observations appeared to be consistent with O95+) heating and direct momentum transfer by high frequency MHD waves through ion cyclotron resonance. Equatorial streamers were found to appear much different when observed in O VI, Fe XII and Mg X than when observed in H I Lyman-alpha or visible light. This led G. Noci to suggest that the elemental abundance of O, Fe, and Mg are lower in the dark center region of the O VI streamer image than it is in the brighter outer legs of the streamer. The O VI line ratio indicated a much smaller outflow speed in streamers than in the surrounding coronal holes. Spectroscopic observations of CME's in June and December 1996 showed large Doppler shifts indicating macroscopic flows of up to 200 km/s transverse to the apparent motion of the CME. The December event displayed factor of 500 intensity increases in H I Lyman lines and bright emissions in cool ion lines like C III 977 A indicating that the origin of some of the gas was a prominence. UVCS also observed two comets, several stars and interplanetary hydrogen. In the current reporting period, the initial results were published and detailed analyses including self consistent empirical models were developed. The research results were reported, published or submitted/accepted for publication. New observations were made to uncover additional information about the surprising results of the first year and other new observations revealed more surprises. A UVCS Tutorial was developed to familiarize potential users of UVCS data with the data products, analysis techniques and coronal models needed to analyze the data.

Kohl, John L.↗
NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗
NASA NTRS2025

Efficient GPU-Accelerated MultiSource Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational-wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analyzing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains massive black hole binaries, compact galactic binaries, and a parametrized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble Markov Chain Monte Carlo (MCMC) sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or transdimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data.We recover posterior distributions for all 15 (6) of the injected massive black hole binaries (MBHB) in the LDC2A training (hidden) dataset. We catalog ∼12000 galactic binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA↗