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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

ATD-1 Avionics Phase 2: Post-Flight Data Analysis Report

This report aims to satisfy Air Traffic Management Technology Demonstration - 1 (ATD-1) Statement of Work (SOW) 3.6.19 and serves as the delivery mechanism for the analysis described in Annex C of the Flight Test Plan. The report describes the data collected and derived as well as the analysis methodology and associated results extracted from the data set collected during the ATD-1 Flight Test. All analyses described in the SOW were performed and are covered in this report except for the analysis of Final Approach Speed and its effect on performance. This analysis was de-prioritized and, at the time of this report, is not considered feasible in the schedule and costs remaining.

Scharl, Julien↗
NASA NTRS1973

Research needs in ocean color data analysis

The success of the effort to extract several subsurface oceanographic parameters from remotely sensed ocean color data will depend to a great extent upon the existence of adequate theoretical models relating the desired oceanographic parameters to the upwelling radiances to be observed. In order to guide the development of these models, and to check their accuracies, a considerable amount of experimental work must be performed. The theoretical and experimental work needed to develop techniques for the quantitative analysis of satellite ocean color data is described.

Mccluney, W. R.↗
NASA NTRS1977

A study of Stormsat interactive data analysis facility

Stormsat, a third generation geosynchronous satellite intended for the investigation and forecasting of severe local storms, tropical cyclones and other mesoscale phenomena, could be launched as early as 1982. The paper outlines the interactive data processing and analysis functions which must be performed and presents a possible configuration capable of achieving the demonstration forecast objectives. Important features of the data processing system include (1) interactive extraction of wind, temperature and moisture profiles, cloud structure and precipitation from Stormsat data, and (2) numerical and statistical modeling necessary to provide demonstration forecasts.

Hasler, A. F.↗
NASA NTRS2006

Quasi Real Time Data Analysis for Air Quality Monitoring with an Electronic Nose

Cabin Air Quality Monitoring: A) Functions; 1) Incident monitor for targeted contaminants exceeding targeted concentrations. Identify and quantify. 2) Monitor for presence of compounds associated with fires or overheating electronics. 3) Monitor clean-up process. B) Characteristics; 1) Low mass, low power device. 2) Requires little crew time for maintenance and calibration. 3) Detects, identifies and quantifies selected chemical species at or below 24 hour SMAC.

data analysis↗
NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗
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]↗
NASA NTRS1972

OGO-6 data analysis

A general summary is presented of the results of the data reduction effort for the OGO-6 neutral atmosphere composition experiment.

Taeusch, D. R.↗
NASA NTRS1997

Data Analysis Results From the GOLD Experiments

Analyses of uplink and downlink data from recent free-space optical communications experiments carried out between Table Mountain Facility (near Pasadena, CA) and the Japanese ETS-VI satellite are presented.

Free-space↗
NASA NTRS2007

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗
NASA NTRS1985

Dynamics-A explorer RIMS data analysis

Activities of the RIMS instrument during the extended mission are planned. The modes of operation for RIMS to achieve the science requirements utilizing the new and exciting information on the composition and dynamics of the low energy (0-50eV) ions in the Earth's ionosphere and magnetosphere are determined. The specific science problems and the required RIMS operational modes needed to acquire the desired data are identified. The analysis was performed on the RIMS data to achieve the science results and this new information was used in determining RIMS operations during the latter part of the mission. Necessary sensitivity tests of RIMS operating modes and instrument performance was suggested. The inflight results was compared with theoretical models.

Banks, P. M.↗
NASA NTRS1993

DataHub--Knowledge-Based Science Data Management for Exploratory Data Analysis

It is our belief that new modes of research and new tools will be required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed. The fundamental innovation required is the integration of three automation technologies, videlicet knowledge-based expert systems, science visualization and science data management. This integration is based on a concept caled the DataHub, which we describe here.

DataHub↗
NASA NTRS2014

Data Analysis & Statistical Methods for Command File Errors

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Correlation Analysis↗
NASA NTRS1998

Polar Hydra Data Analysis

The science activities are: 1) Hydra is still operating successfully on orbit. 2) A large amount of analysis and discovery has occurred with the Hydra ground data processing this past year. 3) Full interdetector calibration has been implemented and documented. This intercalibration was necessitated by the incorrect installation of bias resistors in the pre-acceleration stage to the electron channeltrons. This had the effect of making the counting efficiency for electrons energy dependent as well as channeltron specific. The nature of the error had no impact on the ion detection efficiency since they have a different bias arrangement. This intercalibration is so effective, that the electron and ion moment densities are routinely produced with a level of agreement better than 20%. 4) The data processing routinely removes glint in the sensors and produces public energy time spectrograms on the web overnight. 6) Routine, but more intensive computer processing codes are operational that determine for electrons and ions, the density, the flow vector, the pressure tensor and the heat flux by numerical integration. These codes use the magnetic field to sustain the quality of their output. To gain access to this high quality magnetic field within our data stream we have monitored Russell's web page for zero levels and timing files (since his data acquisition is not telemetry synchronous) and have a local reconstruction of B for our use. We have also detected a routine anomaly in the magnetometer data stream that we have documented to Chris Russell and developed an editing algorithm to intercept these "hits" and remove them from the geophysical analysis.

Scudder, J. D.↗
NASA NTRS1976

Data analysis report on ATS-F COMSAT millimeter wave propagation experiment, part 1

The 13/18 GHz COMSAT Propagation Experiment (CPE) was performed to measure attenuation caused by hydrometeors along slant paths from transmitting terminals on the ground to the ATS-6 satellite. The effectiveness of site diversity in overcoming this impairment was also studied. Problems encountered in assembling a valid data base of rain induced attenuation data for statistical analysis are considered. The procedures used to obtain the various statistics are then outlined. The graphs and tables of statistical data for the 15 dual frequency (13 and 18 GHz) site diversity locations are discussed. Cumulative rain rate statistics for the Fayetteville and Boston sites based on point rainfall data collected are presented along with extrapolations of the attenuation and point rainfall data.

Hyde, G.↗
NASA NTRS2004

A search for mountain waves in MLS stratospheric limb radiances fron the winter Northern Hemisphere: data analysis and global mountain wave modeling

Despite evidence from ground-based data that flow over mountains is a dominant source of gravity waves (GWs) for the Northern Hemisphere winter middle atmosphere, GW-related signals in global limb radiances from the Microwave Limb Sounder (MLS) on the Upper Atmosphere Research Satellite (UARS) have shown little direct evidence of mountain waves.

gravity waves dynamics general circulation global ↗