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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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Description of a simplified one-dimensional treatment of fuel injection for supersonic combustor performance analysis. Representative mixing efficiency variations for both parallel and cross-stream injection are obtained, and approximate means for estimating the length required for complete mixing are demonstrated. Comparisons of calculated and measured data show good agreement.
The structure and direction of bow shock waves and the occurence of Pc 3, 4 micropulsations were investigated. An observational description is given of a quasi-parallel structure in a plasma parameter regime. The use of approximation to estimate the thickness of thin, nearly perpendicular bow shocks at supralaminar Mach numbers is discussed. The pattern of energies of backstreaming protons in the foreshock are predicted.
An explicit adaptive control algorithm based on maximum likelihood estimation of parameters was designed. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm was implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer, surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software.
The objectives and accomplishments of the two-and-a-half year effort to describe how returns from on-board Doppler radar are to be used to detect the presence of a wind shear are reported. The problem is modeled as one of first passage in terms of state variables, the state estimates are generated by a bank of extended Kalman filters working in parallel, and the decision strategy involves the use of a voting algorithm for a series of likelihood ratio tests. The performance issue for filtering is addressed in terms of error-covariance reduction and filter divergence, and the performance issue for detection is addressed in terms of using a probability measure transformation to derive theoretical expressions for the error probabilities of a false alarm and a miss.
Independent checkpointing allows maximum process autonomy but suffers from potential domino effects. Coordinated checkpointing eliminates the domino effect by sacrificing a certain degree of process autonomy. In this paper, we propose the technique of lazy checkpoint coordination which preserves process autonomy while employing communication-induced checkpoint coordination for bounding rollback propagation. The introduction of the notion of laziness allows a flexible trade-off between the cost for checkpoint coordination and the average rollback distance. Worst-case overhead analysis provides a means for estimating the extra checkpoint overhead. Communication trace-driven simulation for several parallel programs is used to evaluate the benefits of the proposed scheme for real applications.
We investigate the formulation and application of element-level error indicators based on parametrized variational principles. The qualifier 'element-level' means that no information from adjacent elements is used for error estimation. This property is ideally suited to drive adaptive mesh refinement on parallel computers where access to neighboring elements resident on different processors may incur significant computational overhead. Furthermore, such indicators are not affected by physical jumps at junctures or interfaces. An element-level indicator has been derived from the higher-order element energy and applied to r and h mesh adaptation of meshes in plates and shell structures. We report on our initial experiments with a cylindrical shell that intersects with fist plates forming a simplified 'wing-body intersection' benchmark problem.
Independent checkpointing allows maximum process autonomy but suffers from potential domino effects. Coordinated checkpointing eliminates the domino effect by sacrificing a certain degree of process autonomy. In this paper, we propose the technique of lazy checkpoint coordination which preserves process autonomy while employing communication-induced checkpoint coordination for bounding rollback propagation. The introduction of the notion of laziness allows a flexible trade-off between the cost for checkpoint coordination and the average rollback distance. Worst-case overhead analysis provides a means for estimating the extra checkpoint overhead. Communication trace-driven simulation for several parallel programs is used to evaluate the benefits of the proposed scheme for real applications.
Active integral twist control for vibration reduction of helicopter rotors during forward flight is investigated. The twist deformation is obtained using embedded anisotropic piezocomposite actuators. An analytical framework is developed to examine integrally-twisted blades and their aeroelastic response during different flight conditions: frequency domain analysis for hover, and time domain analysis for forward flight. Both stem from the same three-dimensional electroelastic beam formulation with geometrical-exactness, and axe coupled with a finite-state dynamic inflow aerodynamics model. A prototype Active Twist Rotor blade was designed with this framework using Active Fiber Composites as the actuator. The ATR prototype blade was successfully tested under non-rotating conditions. Hover testing was conducted to evaluate structural integrity and dynamic response. In both conditions, a very good correlation was obtained against the analysis. Finally, a four-bladed ATR system is built and tested to demonstrate its concept in forward flight. This experiment was conducted at NASA Langley T~ansonic Dynamics Tunnel and represents the first-of-a-kind Mach-scaled fully-active-twist rotor system to undergo forward flight test. In parallel, the impact upon the fixed- and rotating-system loads is estimated by the analysis. While discrepancies are found in the amplitude of the loads under actuation, the predicted trend of load variation with respect to its control phase correlates well. It was also shown, both experimentally and numerically, that the ATR blade design has the potential for hub vibratory load reduction of up to 90% using individual blade control actuation. Using the numerical framework, system identification is performed to estimate the harmonic transfer functions. The linear time-periodic system can be represented by a linear time-invariant system under the three modes of blade actuation: collective, longitudinal cyclic, and lateral cyclic. A vibration minimizing controller is designed based on this result, which implements classical disturbance rejection algorithm with some modifications. The controller is simulated numerically, and more than 90% of the 4P hub vibratory load is eliminated. By accomplishing the experimental and analytical steps described in this thesis, the present concept is found to be a viable candidate for future generation low-vibration helicopters. Also, the analytical framework is shown to be very appropriate for exploring active blade designs, aeroelastic behavior prediction, and as simulation tool for closed-loop controllers.
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
A distributed-parameter model of the structural dynamics of the space-shuttle-deployed Solar Array Flight Experiment is developed and used to produce estimates of the modal frequencies and mode shapes. A lumped parameter version of the distributed model is used to estimate model characteristics by analyzing the measured responses of 32 targets. To make the modeling more tenable, a distributed parameter system is used to reduce the number of unknown parameters, a modified Newton-Raphson technique is used for rapid convergence, and a parallel processing supercomputer is used for more efficient computation. The performances of computers with a high-speed serial processor and with a high-speed parallel processor are compared. The best results are obtained with the modeling approach in which maximum likelihood estimation is applied to distributed parameter models.
Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.
A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.
The Commercial Low Earth Orbit (LEO) Development Program team has been working with NASA and the International Space Station (ISS) National Lab (NL) stakeholders to identify capabilities of interest to both conduct research/technology demonstrations and estimate the resources that will be needed from Commercial LEO Destinations (CLDs). Through a series of one-on-one and working group meetings with users/stakeholders, hardware items of interest to the user community were identified and converted into capabilities (e.g., centrifugation, microscope, pressure chamber, etc.). In parallel, resources needed to operate the research equipment (e.g., crew time, number of experiments, volume, etc.) were estimated in order for the CLD providers to better understand NASA’s potential future service requirements. The capabilities and the resources included in this White Paper do not represent NASA requirements. Instead, they constitute a preliminary set of potential capability and resource needs collated to guide CLD providers in appropriately sizing and outfitting their CLD designs. NASA is requesting feedback from industry on how these capabilities and resources align with their own needs as well as those of their non-NASA customers. Information on how the capabilities/resources impact the CLD designs is also requested. After assessing industry’s feedback to this white paper, NASA plans to issue a preliminary set of requirements for review.
A design study was completed to explore the theoretical physical capacity (TPC) of the John F. Kennedy International Airport (KJFK) runway system for a northflow configuration assuming impedance-free (to throughput) air traffic control functionality. Individual runways were modeled using an agent-based, airspace simulation tool, the Airspace Concept Evaluation System (ACES), with all runways conducting both departures and arrivals on a first-come first-served (FCFS) scheduling basis. A realistic future flight schedule was expanded to 3.5 times the traffic level of a selected baseline day, September 26, 2006, to provide a steady overdemand state for KJFK runways. Rules constraining departure and arrival operations were defined to reflect physical limits beyond which safe operations could no longer be assumed. Safety buffers to account for all sources of operational variability were not included in the TPC estimate. Visual approaches were assumed for all arrivals to minimize inter-arrival spacing. Parallel runway operations were assumed to be independent based on lateral spacing distances. Resulting time intervals between successive airport operations were primarily constrained by same-runway and then by intersecting-runway spacing requirements. The resulting physical runway capacity approximates a theoretical limit that cannot be exceeded without modifying runway interaction assumptions. Comparison with current KJFK operational limits for a north-flow runway configuration indicates a substantial throughput gap of approximately 48%. This gap may be further analyzed to determine which part may be feasibly bridged through the deployment of advanced systems and procedures, and which part cannot, because it is either impossible or not cost-effective to control. Advanced systems for bridging the throughput gap may be conceptualized and simulated using this same experimental setup to estimate the level of gap closure achieved.
A number of theoretical works have suggested that MHD plasma fluctuations in solar winds should play an important role particularly in the acceleration of high speed winds inside or near 0.1 AU from the sun. Since velocity fluctuations in solar winds are expected to be caused by the MHD plasma fluctuations, measurements of the velocity fluctuations give clues to reveal the acceleration process of solar winds. We made interplanetary scintillation (IPS) observations at the region out of 0.1 AU to investigate dependence of velocity fluctuations on flow speeds. For evaluating the velocity fluctuation of a flow, we selected the IPS data-set acquired at 2 separate antennas which located in the projected flow direction onto the baseline plane, and tried to compare skewness of the observed cross correlation function(CCF) with skewness of modeled CCFs in which velocity fluctuations were parametrized. The integration effect of IPS along a ray path was also taken into account in the estimation of modeled CCFs. Although this analysis method is significant to derive only parallel fluctuation components to the flow directions, preliminary analyses show following results: (1) High speed winds (Vsw greater than or equal to 500 km/s out of 0.3 AU) indicate enhancement of velocity fluctuations near 0.1 AU; and (2) Low speed winds (Vsw less than or equal to 400 Km/s out of 0.3 AU) indicate small velocity fluctuations at any distances.
This grant addresses the topic of research on computer systems benchmarking and is more generally concerned with performance issues in computer systems. This report reviews work in those areas during the period of NASA support under this grant. The bulk of the work performed concerned benchmarking and analysis of CPUs, compilers, caches, and benchmark programs. The first part of this work concerned the issue of benchmark performance prediction. A new approach to benchmarking and machine characterization was reported, using a machine characterizer that measures the performance of a given system in terms of a Fortran abstract machine. Another report focused on analyzing compiler performance. The performance impact of optimization in the context of our methodology for CPU performance characterization was based on the abstract machine model. Benchmark programs are analyzed in another paper. A machine-independent model of program execution was developed to characterize both machine performance and program execution. By merging these machine and program characterizations, execution time can be estimated for arbitrary machine/program combinations. The work was continued into the domain of parallel and vector machines, including the issue of caches in vector processors and multiprocessors. All of the afore-mentioned accomplishments are more specifically summarized in this report, as well as those smaller in magnitude supported by this grant.
Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.
Observations of upflowing ionospheric ions are obtained nearly simultaneously by DE 1 and DE 2 over the nightside auroral regions. At low altitudes, the mean value of the net upward ion number flux is of the order of 10 exp 9/sq cm per sec. The ionosphere is predominantly O(+), and the flux of ions with energy greater than 5 eV is a very small fraction (less than 1 percent) of the total ion flux. At high altitudes, the upflowing ions are accelerated by a parallel electric field and heated (with characteristic energies of hundreds of electron volts). Comparing upflowing fluxes at high and low altitudes yields an estimated height of the bottom of the auroral acceleration region of 1400-1700 km for the region of peak potential drop. This low-altitude acceleration could either be from a parallel electric field or from perpendicular acceleration. The fluxes at the edges of the arc are mostly H(+) thus implying a higher-altitude base of the acceleration region at the edges where the potential drop is lower.