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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Research on Personal Protective Equipment for Dual-Use Technology and Technology Transfer

The National Aeronautics and Space Administration (NASA) places highest priority on the safety of its astronauts and support personnel. Because this is so, and to ensure the continuation of this safety, the agency has undertaken to thoroughly research and develop and provide personal protective equipment (PPE) and individual life support systems (LSS) in support of manned spaceflight. It is probable that technology developed for manned spaceflight in the field of PPE and individual LSS can be utilized in certain industrial/commercial endeavors. In an attempt to determine these other uses for this PPE and individual LSS, the Space Suit Systems Branch of the NASA JSC Crew Systems Division initiated a research project designed to access potential common technology that could benefit industry. Such dual-use technology transfer could eventually involve a joint effort by Government and industry. The research project took place over several months and involved discussions with various manufacturers/suppliers/users, as well as regulatory agencies and industries, of PPE and individual LSS. Research data was compiled and evaluated and a summary of significant findings is presented for identifying and establishing opportunities for future cooperation between Government and industry in the field of PPE and individual LSS.

Driggers, Donald C.↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗
NASA NTRS1977

Data collecting activities of the 'Outlook for Space' Panel

The paper describes the work of the 'Outlook for Space' Panel, a NASA-wide study group concerned with the role space flight might play in American society during the years approaching 2000. The study considers the progression of projects from 'could do' (for which capability exists), to 'should do' (because of social benefits), to 'will do' (unknown at this time). Opinions as to objectives were solicited from NASA personnel, advisory committees, industrial organizations, and academic theoreticians. Poll data was examined. A large-scale survey of the attitudes of young people toward the future and space was also undertaken, and a complete matrix is presented of themes (such as production and management of food and forestry resources) and theme subcategory specific activities (for example, global crop production), versus the students' perceived areas of national interest or benefit (e.g., expansion of human knowledge).

Stroud, W. G.↗
NASA NTRS2004

The LATEST Project: Operational Assessment of Total Lightning Data in the U.S.

A government, university, and industry alliance has joined forces to transition total lightning observations from ground-based research networks and NASA satellites (LIS/TRMM) to improve the short range prediction of severe weather. This interest builds on the desire of the U.S Weather Research Program to foster a national Nowcasting Test Bed, with this specific transition activity initiated through the NASA short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL. A kick-off national workshop sponsored by the SPoRT Center was held in Huntsville April 1-2 to identify the common goals and objectives of the research and operational community, and to assign roles and responsibilities within the alliance. The workshop agenda, presentations, and summary are available at the SPoRT Center Web site ( h h under the "Meetings" tab. The next national workshop is planned for 2005 in Dallas, TX. The NASA North Alabama regional Lightning Mapping Array &MA) has been operational in the Huntsville area for 3 years, and has continuously sampled a variety of severe weather systems during that period. A gridded version of the LMA total lightning data is currently being supplied to National Weather Service offices in Huntsville, Nashville and Birmingham through the NWS AWES decision support system, for the purposes of assessing the utility of the data in the nowcasting of severe weather such as tornadoes, damaging straight line winds, flash flooding and other weather hazards (lightning induced forest fires, microbursts). While the raw LMA data have been useful to NWS forecasters, even greater utility would be realized if higher-order data products could be supplied through AWIPS along with the gridded data over a larger domain. In 2003-2004 additional LMA systems have been deployed across the southern US. from Florida to New Mexico, providing an opportunity for more than 20 NWS forecast offices to evaluate the incremental value of total lightning data in the warning decision making process.

Goodman, Steven↗
NASA NTRS1992

Commercial potential of remote sensing data from the Earth observing system

The purpose was to assess the market potential of remote sensing value-added products from the Earth Observing System (EOS) platform. Sensors on the EOS platform were evaluated to determine which qualities and capabilities could be useful to the commercial user. The approach was to investigate past and future satellite data distribution programs. A questionnaire was developed for use in a telephone survey. Based on the results of the survey of companies that add value to remotely sensed data, conversations with the principal investigators in charge of each EOS sensor, a study of past commercial satellite data ventures, and reading from the commercial remote sensing industry literature, three recommendations were developed: develop a strategic plan for commercialization of EOS data, define a procedure for commercial users within the EOS data stream, and develop an Earth Observations Commercial Applications Program-like demonstration program within NASA using EOS simulated data.

Merry, Carolyn J.↗
NASA NTRS1999

The Commtech Methodology: A Demand-Driven Approach to Efficient, Productive, and Measurable Technology Transfer and Commercialization

This paper presents a comprehensive review and assessment of a demonstration technology transfer and commercialization prouram called "CommTech". The pro-ram was conceived and initiated in early to mid-fiscal year 1995, and extended roughly three years into the future. Market research sources were used to initially gather primary technological problems and needs data from non-aerospace companies in three targeted industry sectors: environmental, surface transportation, and bioengineering. Company-supplied information served as input data to activate or start-up an internal, phased matchmaking process. This process was based on technical-level relationship exploration followed by business-level agreement negotiations. and culminated with project management and execution. Space Act Agreements represented near-term outputs. Company product or process commercialization derived from NASA Glenn support and measurable economic effects represented far-term outputs.

Horsham, Gary A. P.↗
NASA NTRS1993

The application of automated operations at the Institutional Processing Center

The JPL Institutional and Mission Computing Division, Communications, Computing and Network Services Section, with its mission contractor, OAO Corporation, have for some time been applying automation to the operation of JPL's Information Processing Center (IPC). Automation does not come in one easy to use package. Automation for a data processing center is made up of many different software and hardware products supported by trained personnel. The IPC automation effort formally began with console automation, and has since spiraled out to include production scheduling, data entry, report distribution, online reporting, failure reporting and resolution, documentation, library storage, and operator and user education, while requiring the interaction of multi-vendor and locally developed software. To begin the process, automation goals are determined. Then a team including operations personnel is formed to research and evaluate available options. By acquiring knowledge of current products and those in development, taking an active role in industry organizations, and learning of other data center's experiences, a forecast can be developed as to what direction technology is moving. With IPC management's approval, an implementation plan is developed and resources identified to test or implement new systems. As an example, IPC's new automated data entry system was researched by Data Entry, Production Control, and Advance Planning personnel. A proposal was then submitted to management for review. A determination to implement the new system was made and elements/personnel involved with the initial planning performed the implementation. The final steps of the implementation were educating data entry personnel in the areas effected and procedural changes necessary to the successful operation of the new system.

Barr, Thomas H.↗
NASA NTRS1979

A normative price for a manufactured product: The SAMICS methodology. Volume 2: Analysis

The Solar Array Manufacturing Industry Costing Standards provide standard formats, data, assumptions, and procedures for determining the price a hypothetical solar array manufacturer would have to be able to obtain in the market to realize a specified after-tax rate of return on equity for a specified level of production. The methodology and its theoretical background are presented. The model is sufficiently general to be used in any production-line manufacturing environment. Implementation of this methodology by the Solar Array Manufacturing Industry Simultation computer program is discussed.

Chamberlain, R. G.↗
NASA NTRS1978

Quantitative mapping of particulate iron in an ocean dump using remotely sensed data

A remote sensing experiment was conducted at the industrial acid waste ocean dump site located approximately 38 n mi SE of Cape Henlopen, Delaware, to see if there was a relationship between aircraft remotely sensed spectral signatures and the iron concentration measured in the plume. Results are presented which show that aircraft remotely sensed spectral data can be used to quantify and map an acid waste dump in terms of its particulate iron concentration. A single variable equation using the ratio of band 2 (440-490 nm) radiance to band 4 (540-580 nm) radiance was used to quantify the acid plume and the surrounding water. The acid waste varied in age from freshly dumped to 3 1/2 hours old. Particulate iron concentrations in the acid waste were estimated to range up to 1.1 mg/liter at the 0.46 meter depth. A classification technique was developed to remove sunglitter-affected pixels from the data set.

Ohlhorst, C. W.↗
NASA NTRS2003

The Sun/Earth System and Space Weather

Solar variability and solar activity are now seen as significant drivers with respect to the Earth and human technology systems. Observations over the last 10 years have significantly advanced our understanding of causes and effects in the Sun/Earth system. On a practical level the interactions between the Sun and Earth dictate how we build our systems in space (communications satellites, GPS, etc), and some of our ground systems (power grids). This talk will be about the Sun/Earth system: how it changes with time, its magnetic interactions, flares, the solar wind, and how the Sun effects human systems. Data will be presented from some current spacecraft which show, for example, how we are able to currently give warnings to the scientific community, the Government and industry about space storms and how this data has improved our physical understanding of processes on the Sun and in the magnetosphere. The scientific advances provided by our current spacecraft has led to a new program in NASA to develop a 'Space Weather' system called 'Living With a Star'. The current plan for the 'Living With a Star' program will also be presented.

Poland, Arthur I.↗
NASA NTRS1986

X-29 flight - Acid test for design predictions

The X-29 flight test data are being disseminated to interested industrial and military users as fast as it becomes available. The aircraft is extensively instrumented with accelerometers and pressure sensors and optical sensors for measuring wing deflection. The thoroughness of preflight preparations permitted a rapid advance through initial test checkpoints, which have both confirmed many predictions and revealed several discrepancies. The flight envelope had been expanded to Mach 1.1 and an altitude of 40,000 ft by December 1985. Notably, the X-29 has provided in-flight data which could not be faithfully depicted in a simulator, e.g., flare procedures during landing, and has shown that the stability adjustments, although adequate for controlling the aircraft, are not rapid enough to offer a satisfactory margin of harmony. The tests are now being performed in the transonic regime, where supercritical airfoil and forward swept wing drag reduction become significant factors.

Putnam, T. W.↗
NASA NTRS2014

Technical Data Interoperability (TDI) Pathfinder Via Emerging Standards

The TDI project (TDI) investigates trending technical data standards for applicability to NASA vehicles, space stations, payloads, facilities, and equipment. TDI tested COTS software compatible with a certain suite of related industry standards for capabilities of individual benefits and interoperability. These standards not only esnable Information Technology (IT) efficiencies, but also address efficient structures and standard content for business processes. We used source data from generic industry samples as well as NASA and European Space Agency (ESA) data from space systems.

Technical Data↗
NASA NTRS2018

TPSAS-NF1676L-32099-DND

This talk provides a short overview of the new POWER web site that provides data parameters to energy sector societal benefit areas from NASA research projects. The NASA research projects include the GEWEX Surface Radiation Budget project, the CERES Fast Shortwave and Longwave radiative flux project (FLASHFlux) and NASA Goddard's Global Modeling and Assimilation Office (GMAO) MERRA-2 atmospheric reanalysis. Data products are customized to the energy industry and make products available from the daily time scale to long-term climatological averages. The web services allow uses to choose multiple parameters and obtain the data in multiple file formats. This short talk is designed to be delivered at the NASA booth area at the 2018 Fall American Geophysical Union conference.

Paul W Stackhouse, Jr.↗
NASA NTRS2002

Summary of Data from the First AIAA CFD Drag Prediction Workshop

The results from the first AIAA CFD Drag Prediction Workshop are summarized. The workshop was designed specifically to assess the state-of-the-art of computational fluid dynamics methods for force and moment prediction. An impartial forum was provided to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify areas needing additional research and development. The subject of the study was the DLR-F4 wing-body configuration, which is representative of transport aircraft designed for transonic flight. Specific test cases were required so that valid comparisons could be made. Optional test cases included constant-C(sub L) drag-rise predictions typically used in airplane design by industry. Results are compared to experimental data from three wind tunnel tests. A total of 18 international participants using 14 different codes submitted data to the workshop. No particular grid type or turbulence model was more accurate, when compared to each other, or to wind tunnel data. Most of the results overpredicted C(sub Lo) and C(sub Do), but induced drag (dC(sub D)/dC(sub L)(exp 2)) agreed fairly well. Drag rise at high Mach number was underpredicted, however, especially at high C(sub L). On average, the drag data were fairly accurate, but the scatter was greater than desired. The results show that well-validated Reynolds-Averaged Navier-Stokes CFD methods are sufficiently accurate to make design decisions based on predicted drag.

Levy, David W.↗
NASA NTRS2008

Overview of the LaNCETS Flight Experiment and the CFD Analysis

LaCETS baseline flight study include: 29 high-quality nearfield shock structure probings at three Mach numbers; Shocks in exhaust plume measured; ! CFD study of simplified nozzle shows similar plume structures as flight data; ! Phase II flights scheduled for October 2008; and ! US Industry and Academia invited to participate in analysis, review, and assessment of LaNCETS data.

Cliatt, Larry J., II↗
NASA NTRS2011

An Investigation Into HPLC Data Quality Problems

This report summarizes the analyses and results produced by a five-member investigative team of Government, university, and industry experts, established by NASA HQ. The team examined data quality problems associated with high performance liquid chromatography (HPLC) analyses of pigment concentrations in seawater samples produced by the San Diego State University (SDSU) Center for Hydro-Optics and Remote Sensing (CHORS). This report shows CHORS did not validate the methods used before placing them into service to analyze field samples for NASA principal investigators (PIs), even though the HPLC literature contained easily accessible method validation procedures, and the importance of implementing them, more than a decade ago. In addition, there were so many sources of significant variance in the CHORS methodologies, that the HPLC system rarely operated within performance criteria capable of producing the requisite data quality. It is the recommendation of the investigative team to a) not correct the data, b) make all the data that was temporarily sequestered available for scientific use, and c) label the affected data with an appropriate warning, e.g., "These data are not validated and should not be used as the sole basis for a scientific result, conclusion, or hypothesis--independent corroborating evidence is required."

Hooker, Stanford B.↗