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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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Postprocessing algorithms devised to facilitate vibrational-mode analyses of dynamics of complicated structures. Yields inertia matrices and elastic/rigid-coupling matrices. Such analyses important in simulation and control in active suppression of vibrations in large building or in precise aiming of large antenna.
This paper demonstrates an approach to nonlinear control system design that uses linearization by state feedback to allow faster maneuvering of payloads by the Shuttle Remote Manipulator System (SRMS). A nonlinear feedback law is defined to cancel the nonlinear plant dynamics so that a linear controller can be designed for the SRMS. First a nonlinear design model was generated via SIMULINK. This design model included nonlinear arm dynamics derived from the Lagrangian approach, linearized servo model, and linearized gearbox model. The current SRMS position hold controller was implemented on this system. Next, a trajectory was defined using a rigid body kinematics SRMS tool, KRMS. The maneuver was simulated. Finally, higher bandwidth controllers were developed. Results of the new controllers were compared with the existing SRMS automatic control modes for the Space Station Freedom Mission Build 4 Payload extended on the SRMS.
A unique experiment makes it now possible to obtain detailed images in microgravity showing how an individual vortex causes the wrinkling, stretching, area increase, and eventual extinction of a premixed flame. The repeatable, controllable flame-vortex interaction represents the fundamental building block of turbulent combustion concepts. New information is provided that is central to turbulent flame models, including measurements of all components of flame stretch, strain, and vorticity. Simultaneous measurements of all components of these quantities are not possible in fully turbulent flames but are possible in the present axisymmetric, repeatable experiment. Advanced PIV diagnostics have been used at one-g and have been developed for microgravity. Numerical simulations of the interaction are being performed at NRL. It is found that microgravity conditions greatly augment the flame wrinkling process. Flame area and the amplitude of wrinkles at zero-g are typically twice that observed at one-g. It is inferred that turbulent flames in microgravity could have larger surface area and thus propagate significantly faster than those in one-g, which is a potential safety hazard. A new mechanism is identified by PIV images that shows how buoyancy retards flame wrinkling at one-g; buoyancy produces new vorticity (due to baroclinic torques) that oppose the wrinkling and the stretch imposed by the original vortex. Microgravity conditions remove this stabilizing mechanism and the amplitude of flame wrinkling typically is found to double. Microgravity also increases the flame speed by a factor of 1.8 to 2.2. Both methane and propane-air flames were studied at the NASA Lewis drop tower. Results indicate that it is important to add buoyancy to models of turbulent flames to simulate the correct flame wrinkling, stretch and burning velocity.
Terminal Countdown and Demonstration Test (TCDT) activities are shown, such as the STS-50 crew (Commander Richards, Pilot Kenneth D. Bowersox, Payload Commander Bonnie J. Dunbar, Mission Specialists Ellen S. Baker and Carl J. Meade, and Payload Specialists Lawrence J. DeLucas and Eugene H. Trinh) emerging from T-38 aircraft and being introduced by Commander Richards. Emergency egress training is seen, as is the crew's departure from the Operations and Checkout (O&C) Building. Footage shows the launch pad and launch control room as the countdown nears the engine ignition simulation.
A new generation of sensor rich, massively distributed, autonomous systems are being developed that have the potential for profound social, environmental, and economic change. These include networked building energy systems, autonomous space probes, chemical plant control systems, satellite constellations for remote ecosystem monitoring, power grids, biosphere-like life support systems, and reconfigurable traffic systems, to highlight but a few. To achieve high performance, these immobile robots (or immobots) will need to develop sophisticated regulatory and immune systems that accurately and robustly control their complex internal functions. To accomplish this, immobots will exploit a vast nervous system of sensors to model themselves and their environment on a grand scale. They will use these models to dramatically reconfigure themselves in order to survive decades of autonomous operations. Achieving these large scale modeling and configuration tasks will require a tight coupling between the higher level coordination function provided by symbolic reasoning, and the lower level autonomic processes of adaptive estimation and control. To be economically viable they will need to be programmable purely through high level compositional models. Self modeling and self configuration, coordinating autonomic functions through symbolic reasoning, and compositional, model-based programming are the three key elements of a model-based autonomous systems architecture that is taking us into the New Millennium.
Accidents and incidents show that high workload-induced stress and poor teamwork skills lead to performance decrements and errors. Research on teamwork shows that effective teams are able to adapt to stressful situations, and to reduce workload by using successful strategies for communication and decision making, and through dynamic redistribution of tasks among team members. Furthermore, superior teams are able to recognize signs and symptoms of workload-induced stress early, and to adapt their coordination and communication strategies to the high workload, or stress conditions. Mission Control Center (MCC) teams often face demanding situations in which they must operate as an effective team to solve problems with crew and vehicle during onorbit operations. To be successful as a team, flight controllers (FCers) must learn effective teamwork strategies. Such strategies are the focus of Space Flight Resource Management (SFRM) training. SFRM training in MOD has been structured to include some classroom presentations of basic concepts and case studies, with the assumption that skill development happens in mission simulation. Integrated mission simulations do provide excellent opportunities for FCers to practice teamwork, but also require extensive technical knowledge of vehicle systems, mission operations, and crew actions. Such technical knowledge requires lengthy training. When SFRM training is relegated to integrated simulations, FCers can only practice SFRM after they have already mastered the technical knowledge necessary for these simulations. Given the centrality of teamwork to the success of MCC, holding SFRM training till late in the flow is inefficient. But to be able to train SFRM earlier in the flow, the training cannot rely on extensive mission-specific technical knowledge. Hence, the need for a generic SFRM training framework that would allow FCers to develop basic teamwork skills which are mission relevant, but without the required mission knowledge. Work on SFRM training has been conducted in collaboration with the Expedition Vehicle Division at the Mission Operations Directorate (MOD) and with United Space Alliance (USA) which provides training to Flight Controllers. The space flight resource management training work is part of the Human Factors in Training Directed Research Project (DRP) of the Space Human Factors Engineering (SHFE) Project under the Space Human Factors and Habitability (SHFH) Element of the Human Research Program (HRP). Human factors researchers at the Ames Research Center have been investigating team work and distributed decision making processes to develop a generic SFRM training framework for flight controllers. The work proposed for FY10 continues to build on this strong collaboration with MOD and the USA Training Group as well as previous research in relevant domains such as aviation. In FY10, the work focuses on documenting and analyzing problem solving strategies and decision making processes used in MCC by experienced FCers.
Stirling cycle power conversion is an enabling technology that provides high thermodynamic efficiency but also presents unique challenges with regard to electrical power generation, management, and distribution. The High Power Linear Alternator Test Rig (HPLATR) located at the NASA Glenn Research Center (GRC) in Cleveland, OH is a demonstration test bed that simulates electrical power generation from a Stirling engine driven alternator. It implements the high power electronics necessary to provide a well regulated DC user load bus. These power electronics use a novel design solution that includes active rectification and power factor control, active ripple suppression, along with a unique building block approach that permits the use of high voltage or high current alternator designs. This presentation describes the HPLATR, the test program, and the operational results.
Stirling cycle power conversion is an enabling technology that provides high thermodynamic efficiency but also presents unique challenges with regard to electrical power generation, management, and distribution. The High Power Linear Alternator Test Rig (HPLATR) located at the NASA Glenn Research Center (GRC) in Cleveland, Ohio is a demonstration test bed that simulates electrical power generation from a Stirling engine driven alternator. It implements the high power electronics necessary to provide a well regulated DC user load bus. These power electronics use a novel design solution that includes active rectification and power factor control, active ripple suppression, along with a unique building block approach that permits the use of high voltage or high current alternator designs. This report describes the HPLATR, the test program, and the operational results.
Calcium-aluminum-rich inclusions (CAIs) are the oldest surviving solids to have formed in the Solar System. Their chemical and isotopic compositions provide a record of the conditions present in the protoplanetary disk where they formed and can aid our understanding of how solids formed in the solar nebula, an important step in the eventual process of planet building. The isotopic compositions of CAIs are primarily controlled by volatility. Evaporation/sublimation are well understood through both theory and experimental work to produce an enrichment in the heavy isotopes of an element, but less is understood about the effects of condensation. Mass-dependent fractionation can potentially provide a record of nebular condensation. Ti is not likely to experience evaporation due to its refractory nature, making it a useful tool for assessing the effects of condensation. We have undertaken a study of the stable isotope fractionation of Ti isotopes as a tracer of processes that predate the last evaporation events affecting CAIs. We compare the 49Ti/47Ti stable isotope ratio with excess 50Ti common in CAIs. We have collected Ti, Mg, Si, and Ca isotope data for a suite of CAIs in order to search for heterogeneity in each of these isotope systems, and for potential correlations among them. We compare our results to expectations for condensation.
Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model.
The National Electrical Manufacturers Association (NEMA) is the nation's largest trade association for manufacturers of electrical equipment. Its member companies produce components, end-use equipment and systems for the generation, transmission, distribution, control and use of electricity. The wire and cable division is presented in 6 sections: building wire and cable, fabricated conductors, flexible cords, high performance wire and cable, magnet wire, and power and control cable. Participating companies are listed.
We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.
A two phase effort was conducted to assess the capabilities and limitations of the DataGlove, a lightweight glove input device that can output signals in real-time based on hand shape, orientation, and movement. The first phase was a period for system integration, checkout, and familiarization in a virtual environment. The second phase was a formal experiment using the DataGlove as input device to control the protoflight manipulator arm (PFMA) - a large telerobotic arm with an 8-ft reach. The first phase was used to explore and understand how the DataGlove functions in a virtual environment, build a virtual PFMA, and consider and select a reasonable teleoperation control methodology. Twelve volunteers (six males and six females) participated in a 2 x 3 (x 2) full-factorial formal experiment using the DataGlove to control the PFMA in a simple retraction, slewing, and insertion task. Two within-subjects variables, time delay (0, 1, and 2 seconds) and PFMA wrist flexibility (rigid/flexible), were manipulated. Gender served as a blocking variable. A main effect of time delay was found for slewing and total task times. Correlations among questionnaire responses, and between questionnaire responses and session mean scores and gender were computed. The experimental data were also compared with data collected in another study that used a six degree-of-freedom handcontroller to control the PFMA in the same task. It was concluded that the DataGlove is a legitimate teleoperations input device that provides a natural, intuitive user interface. From an operational point of view, it compares favorably with other 'standard' telerobotic input devices and should be considered in future trades in teleoperation systems' designs.
The Control of Flexible Structures (COFS) 1 Project provides the invaluable opportunity to test, validate, and measure the effectiveness of theories, structural concepts, control systems, and flight certification processes for future missions through a research program focusing on multiple issues in large flexible structures, dynamics, and controls. The COFS 1 Project consists of a series of ground and flight activities building progressively from modeling and dynamic characterization of large space systems to the more complex issues of flexible-body control. The program objectives are to: determine the degree to which theory and ground testing can predict flight performance of next-generation low-frequency structures; evaluate structural fidelity of representative next-generation large deployable precision structure; assess math modeling requirements for large lightweight complex systems on which ground test results are questionable; determine degree to which scale model analysis and tests can be correlated to full-scale performance; evaluate system identification and state estimation algorithms on complex lightweight structures in the space environment; evaluate and verify controls/structures modeling capability; evaluate control laws and control systems; and evaluate damping effects in micro-g environment.
A peak-seeking control approach for real-time trim configuration optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control approach is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are controlled for optimization of fuel flow. This paper presents the design and integration of this peak-seeking controller on a modified NASA F/A-18 airplane with research flight control computers. A research flight was performed to collect data to build a realistic model of the performance function and characterize measurement noise. This model was then implemented into a nonlinear six-degree-of-freedom F/A-18 simulation along with the peak-seeking control algorithm. With the goal of eventual flight tests, the algorithm was first evaluated in the improved simulation environment. Results from the simulation predict good convergence on minimum fuel flow with a 2.5-percent reduction in fuel flow relative to the baseline trim of the aircraft.
A peak-seeking control approach for real-time trim configuration optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control approach is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an FA-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are controlled for optimization of fuel flow. This presentation presents the design and integration of this peak-seeking controller on a modified NASA FA-18 airplane with research flight control computers. A research flight was performed to collect data to build a realistic model of the performance function and characterize measurement noise. This model was then implemented into a nonlinear six-degree-of-freedom FA-18 simulation along with the peak-seeking control algorithm. With the goal of eventual flight tests, the algorithm was first evaluated in the improved simulation environment. Results from the simulation predict good convergence on minimum fuel flow with a 2.5-percent reduction in fuel flow relative to the baseline trim of the aircraft.
The principles and reasons for employing Human Autonomy Teaming is discussed. Application of these techniques to multi-vehicle control is described. In several operational environments from small drone delivery to air taxi to autonomous cargo, many companies will need technologies that will allow for the operation of an unmanned aircraft (UAS or eVTOL) by a small crew of individuals that are located in a remote network operations center. That is, Multiple operators supervising an increasing Number of vehicles (M:N). This will require a new control/supervisory paradigm where the supervisors team with automation to achieve their joint tasks; Human Autonomy Teaming (HAT). This task will follow the HAT philosophy and tenants (e.g., trust, bi-directional communication, pilot directed interfaces). It will also develop and employ specific HAT tools (e.g., playbook, working agreements, predictive timeline displays, transparent interfaces to build trust). This presentation discusses the future of GCS control stations and need for Human Systems Integration.
The emission of secondary electrons from dielectrics subject to numerous effects of electric field which are experimentally difficult to control is discussed. Measurements are reported using pulse techniques such that local fields do not build to significant levels, but measurements with fields present are also of interest. A specific series of measurements under controlled conditions are described and their implications in terms of fields, magnitude and angle, near the dielectric surface were examined. The measurements were made for a charged fluorinated-ethylene-propylene surface near a grounded aluminum half-round resting on the surface. The geometry produced a stable surface-charge gradient being controlled by a strongly enhanced secondary emission for which a model is constructed. Observations of surface flashovers under various conditions confirm the predictions of some scaling exercises.