Results for “Knowledge Transfer” — Page 8

NASA NTRS2002

Direct-Drive Gas-Cooled Reactor Power System: Concept and Preliminary Testing

This paper describes the concept and preliminary component testing of a gas-cooled, UN-fueled, pin-type reactor which uses He/Xe gas that goes directly into a recuperated Brayton system to produce electricity for nuclear electric propulsion. This Direct-Drive Gas-Cooled Reactor (DDG) is designed to be subcritical under water or wet- sand immersion in case of a launch accident. Because the gas-cooled reactor can directly drive the Brayton turbomachinery, it is possible to configure the system such that there are no external surfaces or pressure boundaries that are refractory metal, even though the gas delivered to the turbine is 1144 K. The He/Xe gas mixture is a good heat transport medium when flowing, and a good insulator when stagnant. Judicious use of stagnant cavities as insulating regions allows transport of the 1144-K gas while keeping all external surfaces below 900 K. At this temperature super-alloys (Hastelloy or Inconel) can be used instead of refractory metals. Super-alloys reduce the technology risk because they are easier to fabricate than refractory metals, we have a much more extensive knowledge base on their characteristics, and, because they have a greater resistance to oxidation, system testing is eased. The system is also relatively simple in its design: no additional coolant pumps, heat exchanger, or freeze-thaw systems are required. Key to success of this concept is a good knowledge of the heat transfer between the fuel pins and the gas, as well as the pressure drop through the system. This paper describes preliminary testing to obtain this key information, as well as experience in demonstrating electrically heated testing of simulated reactor components.

Wright, S. A.↗

NASA NTRS2003

Thermally Simulated Testing of a Direct-Drive Gas-Cooled Nuclear Reactor

This paper describes the concept and preliminary component testing of a gas-cooled, UN-fueled, pin-type reactor which uses He/Xe gas that goes directly into a recuperated Brayton system to produce electricity for nuclear electric propulsion. This Direct-Drive Gas-Cooled Reactor (DDG) is designed to be subcritical under water or wet-sand immersion in case of a launch accident. Because the gas-cooled reactor can directly drive the Brayton turbomachinery, it is possible to configure the system such that there are no external surfaces or pressure boundaries that are refractory metal, even though the gas delivered to the turbine is 1144 K. The He/Xe gas mixture is a good heat transport medium when flowing, and a good insulator when stagnant. Judicious use of stagnant cavities as insulating regions allows transport of the 1144-K gas while keeping all external surfaces below 900 K. At this temperature super-alloys (Hastelloy or Inconel) can be used instead of refractory metals. Super-alloys reduce the technology risk because they are easier to fabricate than refractory metals, we have a much more extensive knowledge base on their characteristics, and, because they have a greater resistance to oxidation, system testing is eased. The system is also relatively simple in its design: no additional coolant pumps, heat exchanger, or freeze-thaw systems are required. Key to success of this concept is a good knowledge of the heat transfer between the fuel pins and the gas, as well as the pressure drop through the system. This paper describes preliminary testing to obtain this key information, as well as experience in demonstrating electrical thermal simulation of reactor components and concepts.

Godfroy, Thomas↗

NASA NTRS2004

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers.

optical depth↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

NASA NTRS1995

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 52: A comparison of the technical communications practices of Japanese and US aerospace engineers and scientists

To understand the diffusion of aerospace knowledge, it is necessary to understand the communications practices and the information-seeking behaviors of those involved in the production, transfer, and use of aerospace knowledge at the individual, organizational, national, and international levels. In this paper, we report selected results from a survey of Japanese and U.S. aerospace engineers and scientists that focused on communications practices and information-seeking behaviors in the workplace. Data are presented for the following topics: importance of and time spent communicating information, collaborative writing, need for an undergraduate course in technical communications, use of libraries, the use and importance of electronic (computer) networks, and the use and importance of foreign and domestically produced technical reports. The responses of the survey respondents are placed within the context of the Japanese culture. We assume that differences in Japanese and U.S. cultures influence the communications practices and information-seeking behaviors of Japanese and U.S. aerospace engineers and scientists.

Pinelli, Thomas E.↗

NASA NTRS1996

A Comparison of the Technical Communications Practices of Japanese and U.S. Aerospace Engineers and Scientists

To understand the diffusion of aerospace knowledge, it is necessary to understand the communications practices and the information-seeking behaviors of those involved in the production, transfer, and use of aerospace knowledge at the individual, organizational, national, and international levels. In this paper, we report selected results from a survey of Japanese and U.S. aerospace engineers and scientists that focused on communications practices and information-seeking behaviors in the workplace. Data are presented for the following topics: importance of and time spent communicating information, collaborative writing, need for an undergraduate course in technical communications, use of libraries, the use and importance of electronic (computer) networks, and the use and importance of foreign and domestically produced technical reports. The responses of the survey respondents are placed within the context of the Japanese culture. We assume that differences in Japanese and U.S. cultures influence the communications practices and information-seeking behaviors of Japanese and U.S. aerospace engineers and scientists.

Pinelli, Thomas E.↗

NASA NTRS2003

Transfer Wisdom Workshops: Coming to a NASA Center Near You

In november 2001, the APPL Knowledge Sharing Initiative introduced a new product, the transfer wisdom workshop. The idea was to give practitioners at each of the NASA centers the opportunity to engage in a knowledge sharing activity.

Lee, Denise↗

NASA NTRS1979

Improving NASA's technology transfer process through increased screening and evaluation in the information dissemination program

The current status of NASA's technology transfer system can be improved if the technology transfer process is better understood. This understanding will only be gained if a detailed knowledge about factors generally influencing technology transfer is developed, and particularly those factors affecting technology transfer from government R and D agencies to industry. Secondary utilization of aerospace technology is made more difficult because it depends on a transfer process which crosses established organizational lines of authority and which is outside well understood patterns of technical applications. In the absence of a sound theory about technology transfer and because of the limited capability of government agencies to explore industry's needs, a team approach to screening and evaluation of NASA generated technologies is proposed which calls for NASA, and other organizations of the private and public sectors which influence the transfer of NASA generated technology, to participate in a screening and evaluation process to determine the commercial feasibility of a wide range of technical applications.

Laepple, H.↗

NASA NTRS1991

A knowledge-based system design/information tool for aircraft flight control systems

Research aircraft have become increasingly dependent on advanced electronic control systems to accomplish program goals. These aircraft are integrating multiple disciplines to improve performance and satisfy research objective. This integration is being accomplished through electronic control systems. Systems design methods and information management have become essential to program success. The primary objective of the system design/information tool for aircraft flight control is to help transfer flight control system design knowledge to the flight test community. By providing all of the design information and covering multiple disciplines in a structured, graphical manner, flight control systems can more easily be understood by the test engineers. This will provide the engineers with the information needed to thoroughly ground test the system and thereby reduce the likelihood of serious design errors surfacing in flight. The secondary object is to apply structured design techniques to all of the design domains. By using the techniques in the top level system design down through the detailed hardware and software designs, it is hoped that fewer design anomalies will result. The flight test experiences are reviewed of three highly complex, integrated aircraft programs: the X-29 forward swept wing; the advanced fighter technology integration (AFTI) F-16; and the highly maneuverable aircraft technology (HiMAT) program. Significant operating technologies, and the design errors which cause them, is examined to help identify what functions a system design/informatin tool should provide to assist designers in avoiding errors.

Mackall, Dale A.↗

NASA NTRS2003

An Introduction to Atmospheric Radiation: Review for the Bulletin of AMS

Whether you like a certain geophysical book or not, largely depends on your background. The field of radiative transfer and atmospheric radiation, in particular, combines people with a wide range of mathematical skills: from theoretical astrophysicists and nuclear physicists to meteorologists and ecologists. There is always a delicate balance between physical explanations and their mathematical interpretations. This balance is very personal and is based on your background. I came to the field of atmospheric radiative transfer as a mathematician with little knowledge of atmospheric physics. After being in the field for more than a decade, I still have gaps in my atmospheric science education. Thus I assess a radiative transfer book fi-om two main criteria: how well does it describe the material that is familiar to me (the radiative transfer equation and its numerical solutions) and how well does it help me to fill the gaps in my personal knowledge. So I present this review fi-om the perspective of a former mathematician working in the field of atmospheric radiation. . After being asked to review the book, my first intention was to compare the new edition with the previous one (Liou, 1980). In doing so, you can clearly follow the progress made in the field of atmospheric radiation over the past two decades. If there are few changes (as in Fundamental Radiative Transfer) or no changes at all (as in the Maxwell s equations), then the field has not seen much development. To the contrary, many differences between the two editions illustrate areas of major progress in the field, such as evidenced in Thermal Ineared Radiative Transfer and even in the creations of completely new fields like Three-Dimensional Radiative Transfer or Light Scattering by Nonspherical Particles. Obviously, the major changes happened not in the theory, which is at least half a century old, but in data quality and completely new measurements (mostly due to new satellite data) with higher accuracy and more reliability. The new edition illustrates this progress well.

Marshak, Alexander↗

NASA NTRS1989

A knowledge-based system design/information tool for aircraft flight control systems

Research aircraft have become increasingly dependent on advanced control systems to accomplish program goals. These aircraft are integrating multiple disciplines to improve performance and satisfy research objectives. This integration is being accomplished through electronic control systems. Because of the number of systems involved and the variety of engineering disciplines, systems design methods and information management have become essential to program success. The primary objective of the system design/information tool for aircraft flight control system is to help transfer flight control system design knowledge to the flight test community. By providing all of the design information and covering multiple disciplines in a structured, graphical manner, flight control systems can more easily be understood by the test engineers. This will provide the engineers with the information needed to thoroughly ground test the system and thereby reduce the likelihood of serious design errors surfacing in flight. The secondary objective is to apply structured design techniques to all of the design domains. By using the techniques in the top level system design down through the detailed hardware and software designs, it is hoped that fewer design anomalies will result. The flight test experiences of three highly complex, integrated aircraft programs are reviewed: the X-29 forward-swept wing, the advanced fighter technology integration (AFTI) F-16, and the highly maneuverable aircraft technology (HiMAT) program. Significant operating anomalies and the design errors which cause them, are examined to help identify what functions a system design/information tool should provide to assist designers in avoiding errors.

Mackall, Dale A.↗

NASA NTRS1992

Heat transfer measurements and CFD comparison of swept shock wave/boundary-layer interactions

An experimental research program providing basic knowledge and establishing new data on the heat transfer in swept shock wave/boundary-layer interactions is described. An equilibrium turbulent boundary-layer on a flat plate is subjected to impingement by swept planar shock waves generated by a sharp fin. Five different interactions with fin angles ranging from 10 to 20 deg at freestream Mach numbers of 3.0 and 4.0 produce a variety of interaction strengths from weak to very strong. A foil heater generates a uniform heat flux over the flat plate surface and miniature thin-film-resistance sensors mounted on it are used to measure the local surface temperature. The heat convection equation is then solved for the heat transfer distribution within an interaction, yielding a total uncertainty of about +/- 10 percent. These experimental data are compared with the results of numerical Navier-Stokes solutions which employ a kappa-epsilon turbulence model. Finally, a simplified form of the peak heat transfer correlation for fin interactions is suggested.

Lee, Y.↗

NASA NTRS1993

NASA/DoD Aerospace Knowledge Diffusion Research Project. Paper 31: The information-seeking behavior of engineers

Engineers are an extraordinarily diverse group of professionals, but an attribute common to all engineers is their use of information. Engineering can be conceptualized as an information processing system that must deal with work-related uncertainty through patterns of technical communications. Throughout the process, data, information, and tacit knowledge are being acquired, produced, transferred, and utilized. While acknowledging that other models exist, we have chosen to view the information-seeking behavior of engineers within a conceptual framework of the engineer as an information processor. This article uses the chosen framework to discuss information-seeking behavior of engineers, reviewing selected literature and empirical studies from library and information science, management, communications, and sociology. The article concludes by proposing a research agenda designed to extend our current, limited knowledge of the way engineers process information.

Pinelli, Thomas E.↗

NASA NTRS1993

NASA/DoD Aerospace Knowledge Diffusion Research Project. Paper 29: The US government technical report and the transfer of federally funded aerospace R and D

This article discusses the U.S. government technical report and the transfer of federally funded aerospace research and development in a conceptual framework of the federal government as a producer of scientific and technical information. The article summarizes current literature and research and discusses U.S. government technical report use and the importance of using data obtained from the NASA/DoD Aerospace Knowledge Diffusion Research Project. The authors make a case for changing existing U.S. technology policy and present a research agenda for the U.S. government technical report.

Pinelli, Thomas E.↗

NASA NTRS1989

Knowledge based and interactive control for the Superfluid Helium On-orbit Transfer Project

NASA's Superfluid Helium On-Orbit Transfer (SHOOT) project is a Shuttle-based experiment designed to acquire data on the properties of superfluid helium in micro-gravity. Aft Flight Deck Computer Software for the SHOOT experiment is comprised of several monitoring programs which give the astronaut crew visibility into SHOOT systems and a rule based system which will provide process control, diagnosis and error recovery for a helium transfer without ground intervention. Given present Shuttle manifests, this software will become the first expert system to be used in space. The SHOOT Command and Monitoring System (CMS) software will provide a near real time highly interactive interface for the SHOOT principal investigator to control the experiment and to analyze and display its telemetry. The CMS software is targeted for all phases of the SHOOT project: hardware development, pre-flight pad servicing, in-flight operations, and post-flight data analysis.

Castellano, Timothy P.↗

NASA NTRS2010

Monthly Variations of Low-Energy Ballistic Transfers to Lunar Halo Orbits

The characteristics of low-energy transfers between the Earth and Moon vary from one month to the next largely due to the Earth's and Moon's non-circular, non-coplanar orbits in the solar system. This paper characterizes those monthly variations as it explores the trade space of low-energy lunar transfers across many months. Mission designers may use knowledge of these variations to swiftly design desirable low-energy lunar transfers in any given month.

Mission Design↗