Design and operating characteristics of a centralized on-line data processing system at Langley Research Center
Centralized on-line data processing system providing concurrent service for five test facilities
Kopelson, S.↗
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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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Open data sets for assessing photovoltaic system reliability
Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.
14 SOLAR ENERGY↗
Opening Historical Airborne Data to Present Day Researchers
For more than 50 years, NASA has flown airborne sensors to carry out research, validate satellite sensors, and test new instrument capabilities. Data collected prior to 2000 are typically analog and difficult to locate and use. The Airborne Data Management Group (ADMG) facilitates rescue of these valuable data to ensure easier discovery, access, and use. But opening historical data comes at a cost of both time and money. Careful decisions are required in assessing the return on investment. - Is there interest in the science community? - Are there government data requirements? - What is the temporal / spatial value of the data? - Can data be transformed to a digital format? - What is cost of transformation? - What time period is needed for rescue? Converting the data to today’s digital storage standards increases value and provides data access. The addition of metadata makes the data easier to search for.
Deborah Smith↗
Estimation of longitudinal stability and control derivatives for an icing research aircraft from flight data
The results of applying a modified stepwise regression algorithm and a maximum likelihood algorithm to flight data from a twin-engine commuter-class icing research aircraft are presented. The results are in the form of body-axis stability and control derivatives related to the short-period, longitudinal motion of the aircraft. Data were analyzed for the baseline (uniced) and for the airplane with an artificial glaze ice shape attached to the leading edge of the horizontal tail. The results are discussed as to the accuracy of the derivative estimates and the difference between the derivative values found for the baseline and the iced airplane. Additional comparisons were made between the maximum likelihood results and the modified stepwise regression results with causes for any discrepancies postulated.
Batterson, James G.↗
Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data
Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.
vegetation canopy↗
Examining the Trends in Financial Support Given to Science Teams for Data Analysis in Mission Proposals
Introduction: The goal of this summer internship research project was to analyze trends in financial support proposed for the science teams of planetary missions. The analysis focuses on the funding for Co-Investigators (Co-Is) to conduct research and/or data analysis needed to achieve the science objectives of the mission. The operational portion of the missions after launch (i.e., Phase E, including cruise and prime operations at the final destination) were examined since that is when the bulk of research is funded and conducted. The objectives of the project were to determine the average level of support for Co-Investigators, identify variation between mission competitions and over time, and determine the relationship between mission type and the amount of support requested. Methodology: This project was conducted using data from 90 proposals submitted to six mission competitions in the Discovery and New Frontiers programs. The level of support for Co-Is was determined by examining Work Breakdown Structure (WBS) 4 (Science Analysis) for Phase E, which was further subdivided into cruise and prime operations. This data represents a proxy rather than the actual funding Co-Is receive to perform research and data analysis because not every dollar in WBS 4 is spent on this activity. Therefore, the proxy obtained in this research represents an overestimate of the funds allocated to Co-Is for research and data analysis. Findings: Analysis shows that on average a Co-I receives approximately four full years of support spread across the entirety of Phase E for science analysis. The variation among proposed missions is less than expected given the variety of factors that are expected to drive this metric (length of mission, mission type, etc.). Additionally, the level of requested support for Co-Is has been remarkably consistent across every variable considered (by competition, over time, by mission type) over the six competitions and nearly 20 years spanned by this project. This remains true for cruise, primary operations, and all of Phase E. Conclusions: A remarkable amount of science is accomplished by the science teams of planetary missions. However, a surprisingly small amount of funding is requested to support the science analysis driving this productivity, both in terms of absolute magnitude of funding and as a portion of total mission cost. This suggests improvements are needed to refine the estimates of Co-I support and/or that Co-Is rely on other funding sources to conduct their research. Better estimates can be determined by engaging directly with Co-Is and NASA centers to obtain data as well as finding other data sources. Additionally, NASA could consider mandating improved reporting of requested funding levels in mission competitions.
E Murray↗
Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface
The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.
Morkner, Paige↗
A data and information system for processing, archival, and distribution of data for global change research
Work on this project was focused on information management techniques for Marshall Space Flight Center's EOSDIS Version 0 Distributed Active Archive Center (DAAC). The centerpiece of this effort has been participation in EOSDIS catalog interoperability research, the result of which is a distributed Information Management System (IMS) allowing the user to query the inventories of all the DAAC's from a single user interface. UAH has provided the MSFC DAAC database server for the distributed IMS, and has contributed to definition and development of the browse image display capabilities in the system's user interface. Another important area of research has been in generating value-based metadata through data mining. In addition, information management applications for local inventory and archive management, and for tracking data orders were provided.
Graves, Sara J.↗
BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions
Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.
25 - ENERGY STORAGE↗
Investigating Building Energy Consumption and CO2 Emission in Phoenix Using AutoBEM and Future Typical Meteorological Year (fTMY) Weather Data
This research investigates the energy performance and CO2 emissions of each building stock across the Phoenix metropolitan area using the Automatic Building Energy Modeling (AutoBEM) framework and Model America v2 (MAv2) dataset from Oak Ridge National Laboratory (ORNL). Typical Meteorological Year (TMY) and Future Typical Meteorological Year (fTMY) files were used for AutoBEM simulation. The simulation results from TMY and fTMY were compared. It was found that a projected 10.28% increase in total CO2 emissions and a 9.30% rise in total energy consumption by 2080–2099 relative to current typical conditions. The results highlight the disparities in emissions among different building stocks and the influence of climate change on future energy demand. The findings underscore the necessity of targeted policy interventions and retrofitting strategies (eg. advanced HVAC systems, improved insulation, reflective roofing) to mitigate emissions in high-energy-use and emission-intensed buildings, particularly as climate conditions evolve. This study contributes to the growing understanding of building-sector emissions and their long-term implications under future climate scenarios.
Li, Hang [ORNL] (ORCID:0000000306001920)↗
Flox/light-hydrocarbon propellant propulsion research.
Experimental data on performance and cooling rates of rocket thrust chambers using FLOX/light- hydrocarbon propellants
Matheson, J. C.↗
An analysis of astronaut performance capability in the lunar environment. Volume 1 - Performance problems and requirements for additional research
Analyzing data on expected astronaut performance in lunar environment
Bender, H. E.↗
Blown flap noise research
Noise data with models of both internally and externally blown jet flaps designed for STOL aircraft
Dorsch, R. G.↗
Definition Research Study
Data were complied on the physical behavior and characteristics of plasma gas and/or dust in the context of how they relate to the self-contamination of manned orbiting vehicles. A definition is given of a systematic experimental program designed to yield the required empirical data on the plasma, neutral gas, and/or the particulate matter surrounding the orbiting vehicles associated with shuttle missions. Theoretical analyses were completed on the behavior of materials to be released from the orbiting or subsatellite shuttle vehicles. The results were used to define some general experimental design recommendations directly applicable to the space shuttle program requirement. An on-board laser probe technique is suggested for measuring the dynamic behavior, inventory, and physical characteristics of particulates in the vicinity of an orbiting spacecraft. Laser probing of cometary photodissociation is also assessed.
Marmo, F. F.↗
Adaptation of time line analysis program to single pilot instrument flight research
A data base was developed for SPIFR operation and the program was run. The outputs indicated that further work was necessary on the workload models. In particular, the workload model for the cognitive channel should be modified as the output workload appears to be too small. Included in the needed refinements are models to show the workload when in turbulence, when overshooting a radial or glideslope, and when copying air traffic control clearances.
Hinton, D. A.↗
Hydrogen fluoride and deuterium fluoride lasers. Citations from the International Aerospace Abstracts data base
Research cited from the international literature adresses various aspects of hydrogen fluoride and deuterium fluoride lasers. Topics covered include flows, laser outputs, molecular relaxation, molecular rotation, energy conversion efficiency, reaction kinetics, and laser materials. Continous wave and pulsed laser are considered. This updated bibliography contains 283 citations, 53 of which are new additions to the previous edition.
Mauk, S. C.↗
Muon spin rotation research program
Data from cyclotron experiments and room temperature studies of dilute iron alloys and iron crystals under strain were analyzed. The Fe(Mo) data indicate that the effect upon the contact hyperfine field in Fe due to the introduction of Mo is considerably less than that expected from pure dilution, and the muon (+) are attracted to the Mo impurity sites. There is a significant change in the interstitial magnetic field with Nb concentration. The Fe(Ti) data, for which precession could clearly be observed early only at 468K and above, show that the Ti impurities are attractive to muon (+), and the magnitude of B(hf) is reduced far beyond the amount expected from pure dilution. Changes in the intersitital magnetic field with the introduction of Cr, W, Ge, and Si are also discussed. When strained to the elastic limit, the interstitial magnetic field in Fe crystals is reduced by 33 gauss, and the relaxation rate of the precession signal increases by 47%.
Stronach, C. E.↗
Rice scene radiation research plan
Data requirements, tasks to be accomplished, and the technical approaches to be used in identifying the characteristics of rice for crop inventories are listed as well as methods for estimating crop development and assessing its conditions.
Heilman, J.↗