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At least 73 records · Page 4

1997 NASA-ODU American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. Objectives of the program are as follows: (1) To further the professional knowledge of qualified engineering and science faculty members, (2) To stimulate and exchange ideas between participants and NASA; (3) To enrich and refresh the research and teaching activities of participants' institutions; and (4) To contribute to the research objectives of the NASA center. Program description is as follows: College or university faculty members will be appointed as Research Fellows to spend 10 weeks in cooperative research and study at the NASA Langley Research Center. The Fellow will devote approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program will consist of lectures and seminars on topics of interest or that are directly relevant to the Fellows' research topics. The lectures and seminar leaders will be distinguished scientists and engineers from NASA, education, and industry.

Tiwari, Surendra N.↗

1998 NASA-HU American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. The program objectives include: (1) To further the professional knowledge of qualified engineering and science faculty members; (2) To stimulate and exchange ideas between participants and NASA; (3) To enrich and refresh the research and teaching activities of participants' institutions; (4) To contribute to the research objectives of the NASA center. College or university faculty members will be appointed as Research Fellows to spend 10 weeks in cooperative research and study at the NASA Langley Research Center. The Fellow will devote approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program will consist of lectures and seminars on topics of interest or that are directly relevant to the Fellows' research topics. The lecture and seminar leaders will be distinguished scientists and engineers from NASA, education, and industry.

Marable, William P.↗

National Aeronautics and Space Administration (NASA)/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program, 1998

The continuous increase in complexity of electronic systems is making the design and manufacturing of such systems more challenging than ever before. As a result, designers are finding it impossible to design efficient systems without the use of sophisticated Electronic Design Automation (EDA) tools. These tools offer integrated simulation of the electrical, mechanical, and manufacturing functions and lead to a correct by design methodology. This report identifies the EDA tools that would be needed to design, analyze, simulate, and evaluate electronic systems for spacecraft vehicles. In addition, the report presents recommendations to enhance the current JSC electronic design capabilities. This includes cost information and a discussion as to the impact, both positive and negative, of implementing the recommendations.

Richard B Bannero↗

1999 NASA - ODU American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program or summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. Objectives: (1) To further the professional knowledge of qualified engineering and science faculty members; (2) To stimulate and exchange ideas between participants and NASA; (3) To enrich and refresh the research and teaching activities of participants' institutions; (4) To contribute to the research objectives of the NASA center. Program Description: College or university faculty members will be appointed as Research Fellows to spend 10 weeks in cooperative research and study at the NASA Langley Research Center. The Fellow will devote approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program will consist of lectures and seminars on topics of interest or that are directly relevant to the Fellows' research topics. The lecture and seminar leaders will be distinguished scientists and engineers from NASA, education, and industry.

Tiwari, Surendra N.↗

2000 NASA-HU American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend ten weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. The objectives are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate and exchange ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of participants' institutions; and (4) to contribute to the research objectives of the NASA center. College or university faculty members will be appointed as Research Fellows to spend ten weeks in cooperative research and study at the NASA Langley Research Center. The Fellow will devote approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program will consist of lectures and seminars on topics of interest or that are directly relevant to the Fellows' research topics. The lecture and seminar leaders will be distinguished scientists and engineers from NASA, education, and industry. A list of the abstracts of the presentations is provided.

Marable, William P.↗

2001 NASA-ODU American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises these programs. Objectives: (1) To further the professional knowledge of qualified engineering and science faculty members; (2) To stimulate and exchange ideas between participants and NASA; (3) To enrich and refresh the research and teaching activities of participants' institutions; (4 To contribute to the research objectives of the NASA center. Program Description: College or university faculty members will be appointed as Research Fellows to spend 10 weeks in cooperative research and study at the NASA Langley Research Center. The Fellow will devote approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program will consist of lectures and seminars on topics of interest or that are directly relevant to the Fellow's research topics. The lecture and seminar leaders wil be distinguished scientists and engineers from NASA, education and industry.

Tiwari, Surendra N.↗

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

numerical analysi↗

History of the American Geophysical Union Atmospheric and Space Electricity Section

Atmospheric and Space Electricity (ASE) has been a part of the American Geophysical Union (AGU) since its initial founding and organization in 1919. John Fleming, who invented the vacuum tube, was the first Secretary of the AGU Terrestrial Magnetism and Atmospheric Electricity Section, and today has an AGU medal named after him. ASE played an important role in the post-World War II era of AGU, as a locus for scientific discussions regarding major ASE-related events, such as the Thunderstorm Project (1946–1949) and the 1969 Apollo 12 lightning incident. By the 1970s and 1980s, the ASE community was represented by the Committee on ASE (CASE) within the Atmospheric Sciences Section. CASE was able to bridge the gap between the fields of aeronomy and atmospheric science by sponsoring its own sessions and nominating AGU Fellow awardees. ASE business meetings at the AGU Fall and Spring Meetings lasted for hours, with anyone from the community presenting scientific ideas, field campaigns, and more - practically turning the business meeting into an ad hoc AGU session!

Lang, Timothy↗

Aeroservoelastic Control Law Development for the Integrated Adaptive Wing Technology Maturation Wind-Tunnel Test

The NASA Advanced Air Transport Technology (AATT) Project seeks to “explore and develop technologies and concepts for improved energy efficiency and environmental compatibility for fixed wing subsonic transports” [1]. The IAWTM project is a subproject within AATT and is a joint Boeing/NASA effort to, in part, demonstrate the active control systems necessary to employ high-aspect ratio wings for improved aerodynamic efficiency. The aircraft configuration under study for the IAWTM project is a generic jet transport based on the NASA Common Research Model (CRM) whose wing aspect ratio has been increased to 13.5 (as opposed to nominal CRM aspect ratio of 9) and whose development is given in Ref. [2]. A semi-span model of the high-aspect-ratio CRM with 10 trailing edge control surfaces is currently being fabricated and will be delivered to the NASA Langley Transonic Dynamics Tunnel (TDT). There, several tests will be conducted to demonstrate maneuver load alleviation (MLA), gust load alleviation (GLA), active flutter suppression (AFS), and drag reduction, all at transonic conditions. A layout of the wind tunnel model is shown in Fig. 1. The wind-tunnel model is a spar/pod wing design with a relatively rigid fuselage attached to a mounting structure (seen in Fig. 1), which in turn is attached to a load balance behind the tunnel wall. Shims exist that can be attached to force the load to go through the fuselage rather than through the balance so as not to damage the balance in the event of flutter. The spar/pod design is similar to that used in the Boeing truss-braced wing aeroelastic model tested in the TDT in 2013 [3]. There is a central spar running the span of the wing to which the pods are attached that form the aerodynamic shape of the wing. The pods are constructed of ribs for attachment to the spar and skins to create the outer mold line. There are ten active control surfaces that will be used for the test objectives discussed above. Three of these (two outboard ailerons and one inboard aileron) are high-speed electrohydraulic actuators, and the remaining seven are low-speed mini-plane flaps, which have slower servo motors that will be used primarily for drag and maneuver load reductions. Control laws must be developed for each test (MLA, GLA, AFS, and drag reduction) and must be able to work in tandem when two or more control strategies are being tested simultaneously (e.g., when control laws to mitigate maneuver loads and gust loads operate simultaneously). The development of these control laws requires accurate mathematical representations of the aerodynamics, structural dynamics, and control surface dynamics of the system. Taken together, this mathematical representation—which is often in state-space form— is the ASE model. Three low-order ASE models of differing fidelities were developed for the IAWTM test and will be presented here. The differences in fidelity appeared in the aerodynamic modeling—one model assumed purely linear aerodynamics, while the other two models used different techniques to linearize the aerodynamics about a nonlinear mean. Furthermore, simple observer-based full-state feedback controllers for each test (MLA, GLA, AFS, and drag reduction) were designed from these low-order ASE models and implemented in a higher-order, nonlinear computational ASE simulation to assess the effectiveness of each controller. Observers were designed from each of the three lower-order ASE models, and each (linear) observer was then used as an estimate of the nonlinear dynamics of the system. Using the estimated states and the full-state feedback controller, control surface commands were fed back to the higher-order, nonlinear ASE system. The insight gained during this development will be applied to control law development for the physical IAWTM wind-tunnel test.

Josiah M Waite↗

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Silva, Walter A.↗

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Walter A. Silva↗

Aeroservoelastic Control Law Development for the Integrated Adaptive Wing Technology Maturation Wind-Tunnel Test

In this paper, a linear quadratic Gaussian (LQG) regulator was applied to a computational aeroservoelastic (ASE) model of the Integrated Adaptive Wing Technology Maturation (IAWTM) wind-tunnel model to demonstrate its effectiveness for active flutter suppression. The aerodynamics within this computational ASE model were solved using unsteady Reynolds-averaged Navier-Stokes (RANS) equations; the structural dynamics of the model were solved using modal analysis. This RANS-based ASE model was used as the plant for the LQG regulator. The Kalman filter and controller used within the LQG regulator were derived from a reduced-order model (ROM) of the RANS-based ASE model. This ROM-based ASE model was generated using system identification techniques. It was shown that the Kalman filter adequately predicted important states of the plant, and that LQG regulator successfully stabilized an aeroelastically unstable plant without exceeding reasonable control surface limitations. All of this was demonstrated using simulation data, and the methods presented here appear feasible for use in the upcoming IAWTM wind-tunnel tests.

Josiah M. Waite↗

Lunar base and Mars base design projects

The space design classes at the University of Texas at Austin undertook seven projects in support of the NASA/USRA advanced space design program during the 1988-89 year. A total of 51 students, including 5 graduate students, participated in the design efforts. Four projects were done within the Aerospace Engineering (ASE) design program and three within the Mechanical Engineering (ME) program. Both lunar base and Mars base design efforts were studied, and the specific projects were as follows: Lunar Crew Emergency Rescue Vehicle (ASE); Mars Logistics Lander Convertible to a Rocket Hopper (ME); A Robotically Constructed Production and Supply Base on Phobos (ASE); A Mars/Phobos Transportation System (ASE); Manned Base Design and Related Construction Issues for Mars/Phobos Mission (ME); and Health Care Needs for a Lunar Colony and Design of Permanent Medical Facility (ME).

Amos, J.↗

Automotive Stirling Engine Development Project

The development and verification of automotive Stirling engine (ASE) component and system technology is described as it evolved through two experimental engine designs: the Mod 1 and the Mod 2. Engine operation and performance and endurance test results for the Mod 1 are summarized. Mod 2 engine and component development progress is traced from the original design through hardware development, laboratory test, and vehicle installation. More than 21,000 hr of testing were accomplished, including 4800 hr with vehicles that were driven more dm 59,000 miles. Mod 2 engine dynamometer tests demonstrated that the engine system configuration had accomplished its performance goals for power (60 kW) and efficiency (38.5%) to within a few percent. Tests with the Mod 2 engine installed in a delivery van demonstrated combined metro-highway fuel economy improvements consistent with engine performance goals and the potential for low emission levels. A modified version of the Mod 2 has been identified as a manufacturable design for an ASE. As part of the ASE project, the Industry Test and Evaluation Program (ITEP), NASA Technology Utilization (TU) project, and the industry-funded Stirling Natural Gas Engine program were undertaken to transfer ASE technology to end users. The results of these technology transfer efforts are also summarized.

Ernst, William D.↗

Autonomous Vegetation Cover Scene Classification of EO-1 Hyperion Hyperspectral Data

The Autonomous Sciencecraft Experiment (ASE) is a JPL-led, New Millennium Program mission containing new technology in the form of software to be flown on the Earth Observer-1 (EO-1) satellite in early 2004. This new technology will facilitate an artificially intelligent machine with autonomous science-driven capabilities. Among the ASE flight software is a set of onboard science algorithms designed for autonomous data processing, primarily based on change detection from observation to observation. Using the output from these algorithms, ASE has the ability to autonomously modify the EO-1 observation plan, retargeting itself for a more in-depth observation of a scientific event in progress. Furthermore, intelligent and selective information down-linking will maximize return of the most valuable scientific data. Among the algorithms developed for use on ASE is a Lava-Vegetation (L-V) detection algorithm. This algorithm can effectively identify the initial location and extent of lava and vegetation coverage based on spectral shape. Comparison of several different observations, all classified via this algorithm, can make change detection possible.

Lee, R. J.↗

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Ip, Felipe↗