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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

The US National Transonic Facility, NTF

The construction of the National Transonic Facility was completed in September 1982 and the start-up and checkout of tunnel systems were performed over the next two years. In August 1984, the Operational Readiness Review (ORR) was conducted and the facility was declared operational for final checkout of cryogenic instrumentation and control systems, and for the aerodynamic calibration and testing to commence. Also, the model access system for the cryogenic mode of operation would be placed into operation along with tunnel testing. Since the ORR, a host of operating problems resulting from the cryogenic environment were identified and solved. These range from making mechanical and electrical systems functional to eliminating temperature induced model vibration to coping with the outgassing of moisture from the thermal insulation. Additionally, a series of aerodynamic tests have demonstrated data quality and provided research data on several configurations. Some of the more significant efforts are reviewed since the ORR and the NTF status concerning hardware, instrumentation and process controls systems, operating constraints imposed by the cryogenic environment, and data quality are summarized.

Bruce, Walter E., Jr.↗
NASA NTRS1992

Transonic turbine blade cascade testing facility

NASA LeRC has designed and constructed a new state-of-the-art test facility. This facility, the Transonic Turbine Blade Cascade, is used to evaluate the aerodynamics and heat transfer characteristics of blade geometries for future turbine applications. The facility's capabilities make it unique: no other facility of its kind can combine the high degree of airflow turning, infinitely adjustable incidence angle, and high transonic flow rates. The facility air supply and exhaust pressures are controllable to 16.5 psia and 2 psia, respectively. The inlet air temperatures are at ambient conditions. The facility is equipped with a programmable logic controller with a capacity of 128 input/output channels. The data acquisition system is capable of scanning up to 1750 channels per sec. This paper discusses in detail the capabilities of the facility, overall facility design, instrumentation used in the facility, and the data acquisition system. Actual research data is not discussed.

Verhoff, Vincent G.↗
NASA NTRS1992

Transonic turbine blade cascade testing facility

NASA LeRC has designed and constructed a new state-of-the-art test facility. This facility, the Transonic Turbine Blade Cascade, is used to evaluate the aerodynamics and heat transfer characteristics of blade geometries for future turbine applications. The facility's capabilities make it unique: no other facility of its kind can combine the high degree of airflow turning, infinitely adjustable incidence angle, and high transonic flow rates. The facility air supply and exhaust pressures are controllable to 16.5 psia and 2 psia, respectively. The inlet air temperatures are at ambient conditions. The facility is equipped with a programmable logic controller with a capacity of 128 input/output channels. The data acquisition system is capable of scanning up to 1750 channels per sec. This paper discusses in detail the capabilities of the facility, overall facility design, instrumentation used in the facility, and the data acquisition system. Actual research data is not discussed.

Verhoff, Vincent G.↗
NASA NTRS2009

HRP Data Accessibility Current Status

Overview of talk: a) Content of Human Life Science data; b) Data archive structure; c) Applicable legal documents and policies; and d) Methods for data access. Life Science Data Archive (LSDA) contains research data from NASA-funded experiments, primarily data from flight experiments and ground analog data collected at NASA facilities. Longitudinal Study of Astronaut Health (LSAH) contains electronic health records (medical data) of all astronauts, including mission data. Data are collected for clinical purposes. Clinical data are analyzed by LSAH epidemiologists to identify trends in crew health and implement changes in pre-, in-, or post-flight medical care.

Sams, Clarence↗
NASA NTRS2017

Greased Lightning (GL-10) Performance Flight Research: Flight Data Report

Modern aircraft design methods have produced acceptable designs for large conventional aircraft performance. With revolutionary electronic propulsion technologies fueled by the growth in the small UAS (Unmanned Aerial Systems) industry, these same prediction models are being applied to new smaller, and experimental design concepts requiring a VTOL (Vertical Take Off and Landing) capability for ODM (On Demand Mobility). A 50% sub-scale GL-10 flight model was built and tested to demonstrate the transition from hover to forward flight utilizing DEP (Distributed Electric Propulsion)[1][2]. In 2016 plans were put in place to conduct performance flight testing on the 50% sub-scale GL-10 flight model to support a NASA project called DELIVER (Design Environment for Novel Vertical Lift Vehicles). DELIVER was investigating the feasibility of including smaller and more experimental aircraft configurations into a NASA design tool called NDARC (NASA Design and Analysis of Rotorcraft)[3]. This report covers the performance flight data collected during flight testing of the GL-10 50% sub-scale flight model conducted at Beaver Dam Airpark, VA. Overall the flight test data provides great insight into how well our existing conceptual design tools predict the performance of small scale experimental DEP concepts. Low fidelity conceptual design tools estimated the (L/D)( sub max)of the GL-10 50% sub-scale flight model to be 16. Experimentally measured (L/D)( sub max) for the GL-10 50% scale flight model was 7.2. The aerodynamic performance predicted versus measured highlights the complexity of wing and nacelle interactions which is not currently accounted for in existing low fidelity tools.

McSwain, Robert G.↗
NASA NTRSDate not supplied

Why We Do What We Do: Data Reuse, Open Access and Privacy in Data Management at the Life Sciences Data Archive

As custodians of the unique and irreplaceable collections of human subject research data generated by the Human Research Program and its predecessors throughout the agency’s history, the Life Sciences Data Archive (LSDA) is charged with protecting participants’ privacy and implementing their consent decisions as it provides retrospective data for use in new studies. This active, stewardship-focused approach to data management and preservation shapes the products that LSDA provides to researchers and the responsibilities of researchers in using the data and publishing their results. This presentation reviews how federal and agency mandates shape LSDA’s data management procedures and expectations for researchers. Topics covered will include LSDA’s movement towards implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles and the archive’s evolving data management practices; collaboration between LSDA and the Lifetime Surveillance of Astronaut Health (LSAH) project (the repository of astronaut medical data); LSDA’s response to the challenges of performing its stewardship role and maintaining trust given the public profiles of the subjects whose data it preserves; and the ever-increasing challenges to expectations of subject privacy stemming from the growing power and ubiquity of data analysis and aggregation tools.

data management↗
NASA NTRS2025

Why We Do What We Do: Data Reuse, Open Access, and Privacy in Data Management at the Life Sciences Data Archive

As custodian of the unique and irreplaceable collections of human subject research data generated by the Human Research Program and its predecessors throughout the agency’s history, the Life Sciences Data Archive (LSDA) is charged with protecting participants’ privacy and implementing their consent decisions as it provides retrospective data for use in new studies. This active, stewardship-focused approach to data management and preservation shapes the products that LSDA provides to researchers and the responsibilities of researchers in using the data and publishing their results. This presentation reviews how federal and agency mandates shape LSDA’s data management procedures and expectations for researchers. Topics covered will include LSDA’s movement towards implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles and how the archive’s evolving data management practices support FAIR-ness; collaboration between LSDA and the Lifetime Surveillance of Astronaut Health (LSAH) project (the repository of astronaut medical data); LSDA’s response to the challenges of performing its stewardship role and maintaining trust given the public profiles of the subjects whose data it preserves; and the ever-increasing challenges to expectations of subject privacy stemming from the growing power and ubiquity of of data analysis and aggregation tools.

Data↗
NASA NTRSDate not supplied

Beyond Fair: Engagement, Data Usability, and Open Community Productivity through the NASA Open Science Data Repository

The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.

data↗
NASA NTRS1991

Software fault tolerance using data diversity

Research on data diversity is discussed. Data diversity relies on a different form of redundancy from existing approaches to software fault tolerance and is substantially less expensive to implement. Data diversity can also be applied to software testing and greatly facilitates the automation of testing. Up to now it has been explored both theoretically and in a pilot study, and has been shown to be a promising technique. The effectiveness of data diversity as an error detection mechanism and the application of data diversity to differential equation solvers are discussed.

Knight, John C.↗
NASA NTRS1984

Computer control for automated flight test maneuvering

The application of an experimental flight test maneuver autopilot test technique for collecting aerodynamic and structural flight research data on a highly maneuverable aircraft is described in this paper. This technique, which was developed to increase the quality and quantity of data obtained during flight test, was applied to the highly maneuverable aircraft technology (HiMAT) vehicle. A primary flight experiment was to verify the design techniques used to develop the HiMAT aerodynamics and structures. This required the performance of maneuvers for collection of large quantities of high-quality pressure distribution, loads, and wing and canard deflection data. Flight data obtained while executing these research maneuvers are presented to demonstrate the effectiveness of this new technique.

Duke, E. L.↗
NASA NTRS1998

Open Architecture Data System for NASA Langley Combined Loads Test System

The Combined Loads Test System (COLTS) is a new structures test complex that is being developed at NASA Langley Research Center (LaRC) to test large curved panels and cylindrical shell structures. These structural components are representative of aircraft fuselage sections of subsonic and supersonic transport aircraft and cryogenic tank structures of reusable launch vehicles. Test structures are subjected to combined loading conditions that simulate realistic flight load conditions. The facility consists of two pressure-box test machines and one combined loads test machine. Each test machine possesses a unique set of requirements or research data acquisition and real-time data display. Given the complex nature of the mechanical and thermal loads to be applied to the various research test articles, each data system has been designed with connectivity attributes that support both data acquisition and data management functions. This paper addresses the research driven data acquisition requirements for each test machine and demonstrates how an open architecture data system design not only meets those needs but provides robust data sharing between data systems including the various control systems which apply spectra of mechanical and thermal loading profiles.

Lightfoot, Michael C.↗
NASA NTRS2011

Analysis of NASA Common Research Model Dynamic Data

Recent NASA Common Research Model (CRM) tests at the Langley National Transonic Facility (NTF) and Ames 11-foot Transonic Wind Tunnel (11-foot TWT) have generated an experimental database for CFD code validation. The database consists of force and moment, surface pressures and wideband wing-root dynamic strain/wing Kulite data from continuous sweep pitch polars. The dynamic data sets, acquired at 12,800 Hz sampling rate, are analyzed in this study to evaluate CRM wing buffet onset and potential CRM wing flow separation.

Balakrishna, S.↗
NASA NTRS1990

The vortex flap F-106B, overcoming safety and data problems in flight testing

A NASA, F-106B airplane equipped with a vortex flap is establishing a data base for calibration of design and analysis tools for this vortical flow control concept. Some of the problems in safely and precisely flying to research data points were caused by the modified airplane's low longitudinal stability and low margin of structural strength. These characteristics are, in part, a consequence of the program's low cost approach which utilizes a bolt-on, ground-adjustable flap attached to a minimally modified airplane. Presently, the 40-degree flap deflection flight research is being concluded with a flow visualization phase. A similar pattern of flight envelope expansion, pressure distribution, performance, and flow visualization phases remain to be accomplished for the 30-degree flap setting. To date, good research flight data has followed resolution of the safety and data problems described.

Brown, Philip W.↗
DOE OSTI2024

Predictive Phenomics Initiative Project Dataset Catalog Collection

The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.

59 BASIC BIOLOGICAL SCIENCES↗