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All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2023

Radionuclide Waste Disposal: Development of Multi-scale Experimental and Modeling Capabilities (Final Report)

The DOE EPSCoR Implementation project “Radioactive waste management: Development of multi-scale experimental and modeling capabilities” helped to develop a team of scientists and engineers from Clemson University, South Carolina State University, and the University of South Carolina to address the disposition of nuclear wastes and study the transport of radioisotopes from a waste repository in the near and far field. The project involved 20 faculty from the three institutions as well as 13 postdoctoral fellows, 32 graduate students, and 32 undergraduate students and was active from 2014-2019. Additionally, we forged new collaborations with nine researchers from DOE laboratories SRNL, LLNL, and ANL as well as the University of Manchester and the China Academy of Engineering Physics. The overarching goal of the project was to understand the conditions under which important classes of co-reactants, ranging from counter ions in crystal lattices to dissolved oxygen in pores, control the chemistry and transport characteristics of radionuclides in engineered waste forms and natural soils. Our approach was to characterize the time and length scales over which non-equilibrium states are maintained by rate-limiting, or rate-enhancing, reactions between radionuclides and co-reactants due to interactions between physical mass-transfer processes (i.e., advection, diffusion) and (biogeo) chemical reactions. We have focused our project on three specific classes of reactions relevant to radionuclide transport at DOE legacy sites: ion exchange/substitution, ligand complexation, and redox-mediated reactions. Understanding radionuclide migration requires detailed knowledge of how changes to a system – whether engineered or natural – drive the behavior of co-reactants, which in turn provide the geochemical context controlling radionuclide transport. Student engagement and training were a primary focus of the project in order to create a pipeline of researchers who could work in the area of nuclear waste disposition to support the state and the nation. Over the duration of the project we worked with 32 undergraduate, graduated 18 M.S. students and 14 Ph.D. students, and advised 13 postdoctoral fellows. The Ph.D students and postdocs have primarily taken positions at DOE laboratories, academia, and industry. Through our collaborative team, numerous follow on projects have been started with over $5M in sponsored research. Additionally, thus far the team has published 53 peer reviewed papers and given over 75 technical presentations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Development and Implementation of A Small Satellite Systems Engineering Webinar Series: A Collaboration Between the United Nations Office for Outer Space Affairs and the National Aeronautics and Space Administration

The United Nations Office for Outer Space Affairs (UNOOSA) in collaboration with the National Aeronautics and Space Administration (NASA) established a webinar series on NASA systems engineering standards and practices for the purpose of sharing knowledge in this area. UNOOSA’s “Access to Space for All” initiative provides capacity-building opportunities in space science, technology, and space applications for United Nations member states. Due to the cooperation among established space actors, the United Nations, and emerging space entities, the initiative enables students from developing countries from all over the world to carry out projects using technologies and space applications. Through NASA’s Small Spacecraft Systems Virtual Institute (S3VI), the four-part webinar series was designed to cover basic systems engineering and project management skills that are fundamental to planning, developing, and implementing an experiment or a space project and that serve as critical knowledge for those engaged in space activities, whether as a designer, builder, or manager of space infrastructure and services. The first series of webinars was convened over the course of November 2023 through February 2024.

Systems Engineering↗
DOE OSTI2021

Redundancy in Aromatic O -Demethylation and Ring-Opening Reactions in Novosphingobium aromaticivorans and Their Impact in the Metabolism of Plant-Derived Phenolics

ABSTRACT Lignin is a plant heteropolymer composed of phenolic subunits. Because of its heterogeneity and recalcitrance, the development of efficient methods for its valorization still remains an open challenge. One approach to utilize lignin is its chemical deconstruction into mixtures of monomeric phenolic compounds, followed by biological funneling into a single product. Novosphingobium aromaticivorans DSM 12444 has been previously engineered to produce 2-pyrone-4,6-dicarboxylic acid (PDC) from depolymerized lignin by simultaneously metabolizing multiple aromatics through convergent routes involving the intermediates 3-methoxygallic acid (3-MGA) and protocatechuic acid (PCA). We investigated enzymes predicted to be responsible for O -demethylation and oxidative aromatic ring opening, two critical reactions involved in the metabolism of phenolic compounds by N. aromaticivorans . The results showed the involvement of DesA in O -demethylation of syringic and vanillic acids, LigM in O- demethylation of vanillic acid and 3-MGA, and a new O- demethylase, DmtS, in the conversion of 3-MGA into gallic acid (GA). In addition, we found that LigAB was the main aromatic ring-opening dioxygenase involved in 3-MGA, PCA, and GA metabolism and that a previously uncharacterized dioxygenase, LigAB2, had high activity with GA. Our results indicate a metabolic route not previously identified in N. aromaticivorans that involves O -demethylation of 3-MGA to GA. We predict that this pathway channels ∼15% of the carbon flow from syringic acid, with the rest following ring opening of 3-MGA. The new knowledge obtained in this study allowed for the creation of an improved engineered strain for the funneling of aromatic compounds that exhibits stoichiometric conversion of syringic acid into PDC. IMPORTANCE For lignocellulosic biorefineries to effectively contribute to reduction of fossil fuel use, they need to become efficient at producing chemicals from all major components of plant biomass. Making products from lignin will require engineering microorganisms to funnel multiple phenolic compounds to the chemicals of interest, and N. aromaticivorans is a promising chassis for this technology. The ability of N. aromaticivorans to efficiently and simultaneously degrade many phenolic compounds may be linked to having functionally redundant aromatic degradation pathways and enzymes with broad substrate specificity. A detailed knowledge of aromatic degradation pathways is thus essential to identify genetic engineering targets to maximize product yields. Furthermore, knowledge of enzyme substrate specificity is critical to redirect flow of carbon to desired pathways. This study described an uncharacterized pathway in N. aromaticivorans and the enzymes that participate in this pathway, allowing the engineering of an improved strain for production of PDC from lignin.

Biotechnology & Applied Microbiology↗
NASA NTRS1988

Fault diagnosis in orbital refueling operations

Usually, operation manuals are provided for helping astronauts during space operations. These manuals include normal and malfunction procedures. Transferring operation manual knowledge into a computerized form is not a trivial task. This knowledge is generally written by designers or operation engineers and is often quite different from the user logic. The latter is usually a compiled version of the former. Experiments are in progress to assess the user logic. HORSES (Human - Orbital Refueling System - Expert System) is an attempt to include both of these logics in the same tool. It is designed to assist astronauts during monitoring and diagnosis tasks. Basically, HORSES includes a situation recognition level coupled to an analytical diagnoser, and a meta-level working on both of the previous levels. HORSES is a good tool for modeling task models and is also more broadly useful for knowledge design. The presentation is represented by abstract and overhead visuals only.

Boy, Guy A.↗
NASA NTRS2016

Investigating the Simulink Auto-Coding Process

Model based program design is the most clear and direct way to develop algorithms and programs for interfacing with hardware. While coding "by hand" results in a more tailored product, the ever-growing size and complexity of modern-day applications can cause the project work load to quickly become unreasonable for one programmer. This has generally been addressed by splitting the product into separate modules to allow multiple developers to work in parallel on the same project, however this introduces new potentials for errors in the process. The fluidity, reliability and robustness of the code relies on the abilities of the programmers to communicate their methods to one another; furthermore, multiple programmers invites multiple potentially differing coding styles into the same product, which can cause a loss of readability or even module incompatibility. Fortunately, Mathworks has implemented an auto-coding feature that allows programmers to design their algorithms through the use of models and diagrams in the graphical programming environment Simulink, allowing the designer to visually determine what the hardware is to do. From here, the auto-coding feature handles converting the project into another programming language. This type of approach allows the designer to clearly see how the software will be directing the hardware without the need to try and interpret large amounts of code. In addition, it speeds up the programming process, minimizing the amount of man-hours spent on a single project, thus reducing the chance of human error as well as project turnover time. One such project that has benefited from the auto-coding procedure is Ramses, a portion of the GNC flight software on-board Orion that has been implemented primarily in Simulink. Currently, however, auto-coding Ramses into C++ requires 5 hours of code generation time. This causes issues if the tool ever needs to be debugged, as this code generation will need to occur with each edit to any part of the program; additionally, this is lost time that could be spent testing and analyzing the code. This is one of the more prominent issues with the auto-coding process, and while much information is available with regard to optimizing Simulink designs to produce efficient and reliable C++ code, not much research has been made public on how to reduce the code generation time. It is of interest to develop some insight as to what causes code generation times to be so significant, and determine if there are architecture guidelines or a desirable auto-coding configuration set to assist in streamlining this step of the design process for particular applications. To address the issue at hand, the Simulink coder was studied at a foundational level. For each different component type made available by the software, the features, auto-code generation time, and the format of the generated code were analyzed and documented. Tools were developed and documented to expedite these studies, particularly in the area of automating sequential builds to ensure accurate data was obtained. Next, the Ramses model was examined in an attempt to determine the composition and the types of technologies used in the model. This enabled the development of a model that uses similar technologies, but takes a fraction of the time to auto-code to reduce the turnaround time for experimentation. Lastly, the model was used to run a wide array of experiments and collect data to obtain knowledge about where to search for bottlenecks in the Ramses model. The resulting contributions of the overall effort consist of an experimental model for further investigation into the subject, as well as several automation tools to assist in analyzing the model, and a reference document offering insight to the auto-coding process, including documentation of the tools used in the model analysis, data illustrating some potential problem areas in the auto-coding process, and recommendations on areas or practices in the current Ramses model that should be further investigated. Several skills were required to be built up over the course of the internship project. First and foremost, my Simulink skills have improved drastically, as much of my experience had been modeling electronic circuits as opposed to software models. Furthermore, I am now comfortable working with the Simulink Auto-coder, a tool I had never used until this summer; this tool also tested my critical thinking and C++ knowledge as I had to interpret the C++ code it was generating and attempt to understand how the Simulink model affected the generated code. I had come into the internship with a solid understanding of Matlab code, but had done very little in using it to automate tasks, particularly Simulink tasks; along the same lines, I had rarely used shell script to automate and interface with programs, which I gained a fair amount of experience with this summer, including how to use regular expression. Lastly, soft-skills are an area everyone can continuously improve on; having never worked with NASA engineers, which to me seem to be a completely different breed than what I am used to (commercial electronic engineers), I learned to utilize the wealth of knowledge present at JSC. I wish I had come into the internship knowing exactly how helpful everyone in my branch would be, as I would have picked up on this sooner. I hope that having gained such a strong foundation in Simulink over this summer will open the opportunity to return to work on this project, or potentially other opportunities within the division. The idea of leaving a project I devoted ten weeks to is a hard one to cope with, so having the chance to pick up where I left off sounds appealing; alternatively, I am interested to see if there are any opening in the future that would allow me to work on a project that is more in-line with my research in estimation algorithms. Regardless, this summer has been a milestone in my professional career, and I hope this has started a long-term relationship between JSC and myself. I really enjoy the thought of building on my experience here over future summers while I work to complete my PhD at Missouri University of Science and Technology.

Gualdoni, Matthew J.↗
NASA NTRS1987

A learning apprentice for software parts composition

An overview of the knowledge acquisition component of the Bauhaus, a prototype computer aided software engineering (CASE) workstation for the development of domain-specific automatic programming systems (D-SAPS) is given. D-SAPS use domain knowledge in the refinement of a description of an application program into a compilable implementation. The approach to the construction of D-SAPS was to automate the process of refining a description of a program, expressed in an object-oriented domain language, into a configuration of software parts that implement the behavior of the domain objects.

Allen, Bradley P.↗
NASA NTRS2007

MatLab Script and Functional Programming

MatLab Script and Functional Programming: MatLab is one of the most widely used very high level programming languages for scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. The MatLab seminar covers the functional and script programming aspect of MatLab language. Specific expectations are: a) Recognize MatLab commands, script and function. b) Create, and run a MatLab function. c) Read, recognize, and describe MatLab syntax. d) Recognize decisions, loops and matrix operators. e) Evaluate scope among multiple files, and multiple functions within a file. f) Declare, define and use scalar variables, vectors and matrices.

Shaykhian, Gholam Ali↗
DOE OSTI2013

30-kW Maintenance-Free Stirling Engine for High-Performance Dish Concentrating Solar

This final report summarizes the final results of the 30-kW Maintenance-Free Stirling Engine for High-Performance Dish Concentrating Solar project performed by Infinia Corporation for the U.S. Department of Energy under contract DE-FC36-08GO18032 during the project period of March 1, 2008 – March 31, 2012. Over the course of the project, Infinia Corporation achieved substantial progress in the design, fabrication, assembly, testing and evaluation of a 30-kW multi-cylinder, free-piston Stirling engine (MCFPSE) prototype. In this effort, prior MCFPSE conceptual design approaches were adapted for the development of a 30-kW design, thereby producing a cohesive design package and detailed performance specifications. Numerical analysis using the Stirling Engine Analysis and Optimization Code (SAGE) was completed culminating in the selection of a fully balanced 6-cylinder configuration composed of two 3-cylinder engine modules. The model was refined throughout the program to include all wall conduction losses, piston and rod seal losses, appendix, shuttle and pumping losses, and piston radiation loss to closely represent the real system. Performance mapping of the engine was then completed using the detailed model. Based on knowledge and experience from its existing commercial products, and using the results from the extensive numerical modeling discussed above, Infinia successfully fabricated, assembled and tested two sets of 30-kW engine modules. One of these configurations was driven by an external power supply and operated as a cooler in order to verify the mechanical integrity of the system. In the engine configuration, induction heaters provided the energy to the heater head to operate the engine. Considerable effort was expended on correcting problems associated with contact and rubbing of internal components, identification and subsequent elimination of internal leaks, and undesirable amounts of piston bias. Many details concerning the fabrication and testing efforts are considered proprietary. As a result, those findings are not disclosed herein but rather can be found in proprietary reports supplied to the DOE on a periodic basis. The prototype did not fully demonstrate performance nor did it realize the projected cost targets. Furthermore, the basis of the mechanical and electrical architecture of the 30-kW multi-cylinder prototype design is now at least two generations old. Alternatively, Infinia’s 8-kW Bonneville generator, which was successfully demonstrated in April 2012, and is slated to enter commercial production in late 2013, offers immediate benefits of lower cost and significantly higher power density such that the generator will likely meet DOE’s Sunshot LCOE target goal of $\$$0.07-0.10/kWh by 2015 and $\$$0.05-0.07/kWh by 2020. Therefore, the design of a 30-kW Stirling engine as disclosed in the project will not be pursued further. However, Infinia remains keenly interested in developing higher power Stirling machines in the future based on the new Bonneville mechanical design.

14 SOLAR ENERGY↗
DOE OSTI2013

Scientific Data Management Center for Enabling Technologies

Managing scientific data has been identified by the scientific community as one of the most important emerging needs because of the sheer volume and increasing complexity of data being collected. Effectively generating, managing, and analyzing this information requires a comprehensive, end-to-end approach to data management that encompasses all of the stages from the initial data acquisition to the final analysis of the data. Fortunately, the data management problems encountered by most scientific domains are common enough to be addressed through shared technology solutions. Based on community input, we have identified three significant requirements. First, more efficient access to storage systems is needed. In particular, parallel file system and I/O system improvements are needed to write and read large volumes of data without slowing a simulation, analysis, or visualization engine.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1991

Theoretical foundations for information representation and constraint specification

Research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University is described. Outlined here are the theoretical foundations necessary to construct a Neutral Information Representation Scheme (NIRS), which will allow for automated data transfer and translation between model languages, procedural programming languages, database languages, transaction and process languages, and knowledge representation and reasoning control languages for information system specification.

Menzel, Christopher P.↗
NASA NTRS2010

Unique Education and Workforce Development for NASA Engineers

NASA engineers are some of the world's best-educated graduates, responsible for technically complex, highly significant scientific programs. Even though these professionals are highly proficient in traditional analytical competencies, there is a unique opportunity to offer continuing education that further enhances their overall scientific minds. With a goal of maintaining the Agency's passionate, "best in class" engineering workforce, the NASA Academy of Program/Project & Engineering Leadership (APPEL) provides educational resources encouraging foundational learning, professional development, and knowledge sharing. NASA APPEL is currently partnering with the scientific community's most respected subject matter experts to expand its engineering curriculum beyond the analytics and specialized subsystems in the areas of: understanding NASA's overall vision and its fundamental basis, and the Agency initiatives supporting them; sharing NASA's vast reservoir of engineering experience, wisdom, and lessons learned; and innovatively designing hardware for manufacturability, assembly, and servicing. It takes collaboration and innovation to educate an organization that possesses such a rich and important history~and a future that is of great global interest. NASA APPEL strives to intellectually nurture the Agency's technical professionals, build its capacity for future performance, and exemplify its core values~alJ to better enable NASA to meet its strategic vision~and beyond.

Forsgren, Roger C.↗
DOE OSTI2019

Common principles and best practices for engineering microbiomes

Despite broad scientific interest in harnessing the power of Earth’s microbiomes, knowledge gaps hinder their efficient use for addressing urgent societal and environmental challenges. We argue that structuring research and technology developments around a design–build–test–learn (DBTL) cycle will advance microbiome engineering and spur new discoveries of the basic scientific principles governing microbiome function. In this Review, we present key elements of an iterative DBTL cycle for microbiome engineering, focusing on generalizable approaches, including top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyse microbiome function. These approaches can be used to harness microbiomes for broad applications related to medicine, agriculture, energy and the environment. We also discuss key challenges and opportunities of each approach and synthesize them into best practice guidelines for engineering microbiomes. Here, we anticipate that adoption of a DBTL framework will rapidly advance microbiome-based biotechnologies aimed at improving human and animal health, agriculture and enabling the bioeconomy.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2023

Identifying and Documenting Expert Knowledge, A Practical Study of Design Patterns

Globalization, powered by digitization, is increasing technology growth and knowledge transfer rates to levels not seen in the previous 3500 years, obscuring absolute truth and accelerating rates of innovation and production. Competing,or remaining competitive, in this global marketplace requires a learning organization adopt a method of capture, retention, and reuse for demonstrated tacit knowledge to accelerate the development of increasingly complex systems of high quality at a reasonable cost. The architectural theory of Patterns and Pattern Language is a validated methodology for mining tacit domain knowledge from a proven system. This work applies architectural theory to a multi-year development experiment and captures exposed knowledgeas a design patternin a model based systems engineering tool, demonstrating applicability ofdigital engineering initiativesin thedescription and reuse of expert design knowledge.By creating and archiving model based expressions of expert knowledge,a learning organization canimprovepractical decision making and avoid uninformed concept phase decision making

systems engineering↗
NASA NTRS1992

Some effects of time usage patterns on the productivity of engineers

The performance of the 1500+ engineers at MSFC is critical to the Center's mission. Worker's performance, however, is a variable affected by ability, motivation, role understanding, and other factors. Managing subordinates' performance is a great challenges to managers. Special challenges confront the managers of engineers because engineers often work with general goals, long deadlines, and considerable autonomy. The productivity of a team or branch is a function of the productivity of each of its members. While many managers have personal theories about how to run their work group, surprisingly little systematic scientific knowledge exerts about the effects of various factors on engineers' productivity. This study is intended to help lay the foundation for such a program of research.

Jackson, Conrad N.↗
NASA NTRS2002

Rapid Modeling and Analysis Tools: Evolution, Status, Needs and Directions

Advanced aerospace systems are becoming increasingly more complex, and customers are demanding lower cost, higher performance, and high reliability. Increased demands are placed on the design engineers to collaborate and integrate design needs and objectives early in the design process to minimize risks that may occur later in the design development stage. High performance systems require better understanding of system sensitivities much earlier in the design process to meet these goals. The knowledge, skills, intuition, and experience of an individual design engineer will need to be extended significantly for the next generation of aerospace system designs. Then a collaborative effort involving the designer, rapid and reliable analysis tools and virtual experts will result in advanced aerospace systems that are safe, reliable, and efficient. This paper discusses the evolution, status, needs and directions for rapid modeling and analysis tools for structural analysis. First, the evolution of computerized design and analysis tools is briefly described. Next, the status of representative design and analysis tools is described along with a brief statement on their functionality. Then technology advancements to achieve rapid modeling and analysis are identified. Finally, potential future directions including possible prototype configurations are proposed.

Knight, Norman F., Jr.↗
NASA NTRS2013

Twenty Years of Systems Engineering on the Cassini-Huygens Mission

Over the past twenty years, the Cassini-Huygens Mission has successfully utilized systems engineering to develop and execute a challenging prime mission and two mission extensions. Systems engineering was not only essential in designing the mission, but as knowledge of the system was gained during cruise and science operations, it was critical in evolving operational strategies and processes. This paper discusses systems engineering successes, challenges, and lessons learned on the Cassini-Huygens Mission gathered from a thorough study of mission plans and developed scenarios, and interviews with key project leaders across its twenty-year history.

Manor-Chapman, Emily↗
NASA NTRS2004

Research and Technology 2003

The NASA Glenn Research Center at Lewis Field, in partnership with U.S. industries, universities, and other Government institutions, is responsible for developing critical technologies that address national priorities in aeropropulsion and space applications. Our work is focused on research for new aeropropulsion technologies, aerospace power, microgravity science (fluids and combustion), electric propulsion, and communications technologies for aeronautics, space, and aerospace applications. As NASA s premier center for aeropropulsion, aerospace power, and turbomachinery, our role is to conduct world-class research and to develop key technologies. We contribute to economic growth and national security through safe, superior, and environmentally compatible U.S. civil and military aircraft propulsion systems. Our Aerospace Power Program supports all NASA Enterprises and major programs, including the International Space Station, Advanced Space Transportation, and new initiatives in human and robotic exploration. Glenn Research Center leads NASA s research in the microgravity science disciplines of fluid physics, combustion science, and acceleration measurement. Almost every space shuttle science mission has had an experiment managed by NASA Glenn, and we have conducted a wide array of similar experiments on the International Space Station. The Glenn staff consists of over 3200 civil service employees and support service contractor personnel. Scientists and engineers comprise more than half of our workforce, with technical specialists, skilled workers, and an administrative staff supporting them. We aggressively strive for technical excellence through continuing education, increased diversity in our workforce, and continuous improvement in our management and business practices so that we can expand the boundaries of aeronautics, space, and aerospace technology. Glenn Research Center is a unique facility located in northeast Ohio. Situated on 350 acres of land adjacent to the Cleveland Hopkins International Airport, Glenn comprises more than 140 buildings, including 24 major facilities and over 500 specialized research and test facilities. Additional facilities are located at Plum Brook Station, which is about 50 miles west of Cleveland. Plum Brook Station has four large, major, world-class facilities for space research available for Government and industry programs. Knowledge is the end product of our activities. The R&T reports help make this knowledge fully available to potential users the aircraft engine industry, the space industry, the energy industry, the automotive industry, the aerospace industry, and others. It is organized so that a broad cross section of the community can readily use it. Each article begins with a short introductory paragraph that should prove valuable for the layperson. These articles summarize the progress made during the year in various technical areas and portray the technical and administrative support associated with Glenn s technology programs. We hope that this information is useful to all. If additional information is desired, readers are encouraged to contact the researchers identified at the end of each article and to visit Glenn on the World Wide Web at http://www.grc.nasa.gov.

Julian Earls↗