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Professor Xiong will investigate robust synchronization schemes for dynamic channel environment. A sliding window will be investigated for symbol timing synchronizer and an open loop carrier estimator for carrier synchronization. Matlab/Simulink will be used for modeling and simulations.
This paper presents methods which enable the use of passivity-based control design techniques to control non-passive systems. For inherently non-passive finite- dimensional linear time-invaraint systems, passification methods are presented to render such systems passive by suitable compensation. The passified system can then be controlled by a class of passive linear controllers. The idea is to exploit the robust stability properties of passivity-based control laws for uncertain systems. The proposed passification methods are demonstrated by application to the ACC benchmark problem and to pitch-axis control of an F-18 High Alpha Research Vehicle (HARV) model.
One half of Professor Xiong's effort will investigate robust timing synchronization schemes for dynamically varying characteristics of aviation communication channels. The other half of his time will focus on efficient modulation and coding study for the emerging quantum communications.
A method has been developed for real-time stability margin measurement calculations. The method relies on a tailored-forced excitation targeted to a specific frequency range. Computation of the frequency response is matched to the specific frequencies contained in the excitation. A recursive Fourier transformation is used to make the method compatible with real-time calculation. The method was incorporated into the X-38 nonlinear simulation and applied to an X-38 robustness test. X-38 stability margins were calculated for different variations in aerodynamic and mass properties over the vehicle flight trajectory. The new method showed results comparable to more traditional stability analysis techniques, and at the same time, this new method provided coverage that is more complete and increased efficiency.
This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.
Despite their expense tape silos are still often the only affordable option for petabytescale science data archives, particularly when other factors such as data reliability, floor space, power and cooling load are accounted for. However, the complexity, management software, hardware reliability and access latency of tape silos make online data storage ever more attractive. Drastic reductions in low-cost mass-market PC disk drivers help to make this more affordable (approx. 1$/GB), but are challenging to scale to the petabyte range and of questionable reliability for archival use, On the other hand, if much of the science archive could be "virtualized", i.e., produced on demand when requested by users, we would need store only a fraction of the data online, perhaps bringing an online-only system into in affordable range. Radiance data from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides a good opportunity for such a virtual archive: the raw data amount to 140 GB/day, but these are small relative to the 550 GB/day making up the radiance products. These data are routinely processed as inputs for geophysical parameter products and then archived on tape at the Goddard Earth Sciences Distributed Active Archive (GES DAAC) for distributing to users. Virtualizing them would be an immediate and signifcant reduction in the amount of data being stored in the tape archives and provide more customizable products. A prototype of such a virtual archive is being developed to prove the concept and develop ways of incorporating the robustness that a science data archive requires.
Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.
Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the thousands and will reach tens or hundreds of thousands in the near future.
Advanced ceramics and fiber-reinforced ceramic matrix composites with high strength and toughness, good thermal conductivity, thermal shock resistance, and oxidation resistance are needed for high-temperature structural applications in advanced high-efficiency and high-performance engines, space propulsion components, and land-based systems. The engineering designs of these systems require the manufacturing of large parts with complex shapes, which are either quite expensive or impossible to fabricate. In many instances, it is more economical to build complex shapes by joining together simple geometrical shapes. Thus, joining has been recognized as an enabling technology for the successful utilization of advanced ceramics and fiber-reinforced composite components in high-temperature applications. However, such joints must retain their structural integrity at high temperatures and must have mechanical strength and environmental stability comparable to those of the bulk materials. In addition, the joining technique should be robust, practical, and reliable. ARCJoinT, which is based on the reaction-forming approach, is unique in terms of producing joints with tailorable microstructures. The formation of joints by this approach is attractive since the thermomechanical properties of the joint interlayer can be tailored to be very close to those of the base materials. In addition, high-temperature fixturing is not needed to hold the parts at the infiltration temperature. The joining process begins with the application of a carbonaceous mixture in the joint area, holding the items to be joined in a fixture, and curing at 110 to 120 C for 10 to 20 min. This step fastens the pieces together. Then, silicon or a silicon alloy in tape, paste, or slurry form is applied around the joint region and heated to 1250 to 1425 C (depending on the type of infiltrant) for 10 to 15 min. The molten silicon or silicon-refractory metal alloy reacts with carbon to form silicon carbide with controllable amounts of silicon and other phases as determined by the alloy composition. Joint thickness can be readily controlled through adjustments of the properties of the carbonaceous paste and the applied fixturing force. The photograph shows various shapes of silicon-carbide-based ceramics and fiberreinforced composites that have been joined using ARCJoinT. Thermomechanical and thermochemical characterization of joints is underway for a wide variety of silicon-carbidebased advanced ceramics and fiber-reinforced composites under the hostile environments that will be encountered in engine applications. ARCJoinT, which was developed by researchers at the NASA Glenn Research Center at Lewis Field, received R&D Magazine's prestigious R&D 100 Award in 1999.
Affordable, Robust Ceramic Joining Technology (ARCJoint) is a method for joining high temperature- resistant ceramic pieces together, establishing joints that are strong, and allowing joining to be done in the field. This new way of joining allows complex shapes to be formed by joining together geometrically simple shapes. The joining technology at NASA is one of the enabling technologies for the application of silicon-carbide-based ceramic and composite components in demanding and high-temperature applications. The technology is being developed and tested for high-temperature propulsion parts for aerospace use. Commercially, it can be used for joining ceramic pieces used for high temperature applications in the power-generating and chemical industries, as well as in the microelectronics industry. This innovation could yield big payoffs for not only the power-generating industry but also the Silicon Valley chipmakers. This technology, which was developed at the NASA Glenn Research Center by Dr. Mrityunjay Singh, is a two-step process involving first using a paste to join together ceramic pieces and bonding them by heating the joint to 110 to 120 C for between 10 and 20 min. This makes the joint strong enough to be handled for the final joining. Then, a silicon-based substance is applied to the joint and heated to 1400 C for 10 to 15 min. The resulting joint is as strong as the original ceramic material and can withstand the same high temperatures.
High-energy rotating machines, powering liquid propellant rocket engines, are subject to various sources of high and low cycle fatigue generated by unsteady flow phenomena. Given the tremendous need for reliability in a sustainable space exploration program, a fundamental change in the design methodology for engine components is required for both launch and space based systems. A design optimization system based on neural-networks has been applied and demonstrated in the redesign of the Space Shuttle Main Engine (SSME) Low Pressure Oxidizer Turbo Pump (LPOTP) turbine nozzle. One objective of the redesign effort was to increase airfoil thickness and thus increase its strength while at the same time detuning the vane natural frequency modes from the vortex shedding frequency. The second objective was to reduce the vortex shedding amplitude. The third objective was to maintain this low shedding amplitude even in the presence of large manufacturing tolerances. All of these objectives were achieved without generating any detrimental effects on the downstream flow through the turbine, and without introducing any penalty in performance. The airfoil redesign and preliminary assessment was performed in the Exploration Technology Directorate at NASA ARC. Boeing/Rocketdyne and NASA MSFC independently performed final CFD assessments of the design. Four different CFD codes were used in this process. They include WIL DCA T/CORSAIR (NASA), FLUENT (commercial), TIDAL (Boeing Rocketdyne) and, a new family (AardvarWPhantom) of CFD analysis codes developed at NASA MSFC employing LOX fluid properties and a Generalized Equation Set formulation. Extensive aerodynamic performance analysis and stress analysis carried out at Boeing Rocketdyne and NASA MSFC indicate that the redesign objectives have been fully met. The paper presents the results of the assessment analysis and discusses the future potential of robust optimal design for rocket engine components.
Advanced ceramic matrix composites (CMCs) are under active consideration for use in a wide variety of high temperature applications within the aerospace, energy, and nuclear industries. The engineering designs of CMC components require fabrication and manufacturing of large and complex shaped parts of various thicknesses. In many instances, it is more economical to build up complex shapes by joining simple geometrical shapes. Thus, joining and attachment have been recognized as enabling technologies for successful utilization of ceramic components in various demanding applications. In this presentation, various challenges and opportunities in design, fabrication, and testing of high temperature joints in ceramic matrix composites will be presented. A wide variety of ceramic composites, in different shapes and sizes, have been joined using an affordable, robust ceramic joining technology (ARCJoinT). Microstructure and mechanical properties of joints in melt infiltrated and CVI Sic matrix composites will be reported. Various joint design philosophies and design issues in joining of composites will be discussed.
The development of an advanced robust timing synchronization scheme is crucial for the support of two NASA programs--Advanced Air Transportation Technologies and Aviation Safety. A mobile aeronautical channel is a dynamic channel where various adverse effects--such as Doppler shift, multipath fading, and shadowing due to precipitation, landscape, foliage, and buildings--cause the loss of symbol timing synchronization.
The primary objective of this research program is to develop vibration analysis tools, design tools, and design strategies to significantly improve the safety and robustness of turbine engine rotors. Bladed disks in turbine engines always feature small, random blade-to-blade differences, or mistuning. Mistuning can lead to a dramatic increase in blade forced-response amplitudes and stresses. Ultimately, this results in high-cycle fatigue, which is a major safety and cost concern. In this research program, the necessary steps will be taken to transform a state-of-the-art vibration analysis tool, the Turbo-Reduce forced-response prediction code, into an effective design tool by enhancing and extending the underlying modeling and analysis methods. Furthermore, novel techniques will be developed to assess the safety of a given design. In particular, a procedure will be established for using eigenfrequency curve veerings to identify "danger zones" in the operating conditions--ranges of rotational speeds and engine orders in which there is a great risk that the rotor blades will suffer high stresses. This work also will aid statistical studies of the forced response by reducing the necessary number of simulations. Finally, new strategies for improving the design of rotors will be pursued. Several methods will be investigated, including the use of intentional mistuning patterns to mitigate the harmful effects of random mistuning, and the modification of disk stiffness to avoid reaching critical values of interblade coupling in the desired operating range. Recent research progress is summarized in the following paragraphs. First, significant progress was made in the development of the component mode mistuning (CMM) and static mode compensation (SMC) methods for reduced-order modeling of mistuned bladed disks (see the following figure). The CMM method has been formalized and extended to allow a general treatment of mistuning. In addition, CMM allows individual mode mistuning, which accounts for the realistic effects of local variations in blade properties that lead to different mistuning values for different mode types (e.g., mistuning of the first torsion mode versus the second flexural mode). The accuracy and efficiency of the CMM method and the corresponding Turbo-Reduce code were validated for an example finite element model of a bladed disk.
The primary objective of this research program is to develop vibration analysis tools, design tools, and design strategies to significantly improve the safety and robustness of turbine engine rotors. Bladed disks in turbine engines always feature small, random blade-to-blade differences, or mistuning. Mistuning can lead to a dramatic increase in blade forced-response amplitudes and stresses. Ultimately, this results in high-cycle fatigue, which is a major safety and cost concern. In this research program, the necessary steps will be taken to transform a state-of-the-art vibration analysis tool, the Turbo- Reduce forced-response prediction code, into an effective design tool by enhancing and extending the underlying modeling and analysis methods. Furthermore, novel techniques will be developed to assess the safety of a given design. In particular, a procedure will be established for using natural-frequency curve veerings to identify ranges of operating conditions (rotational speeds and engine orders) in which there is a great risk that the rotor blades will suffer high stresses. This work also will aid statistical studies of the forced response by reducing the necessary number of simulations. Finally, new strategies for improving the design of rotors will be pursued.
Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems (developed for failure detection, identification, and reconfiguration, as well as upset recovery) need to be evaluated over broad regions of the flight envelope and under extreme flight conditions, and should include various sources of uncertainty. However, formulation of linear fractional transformation (LFT) models for representing system uncertainty can be very difficult for complex parameter-dependent systems. This paper describes a preliminary LFT modeling software tool which uses a matrix-based computational approach that can be directly applied to parametric uncertainty problems involving multivariate matrix polynomial dependencies. Several examples are presented (including an F-16 at an extreme flight condition, a missile model, and a generic example with numerous crossproduct terms), and comparisons are given with other LFT modeling tools that are currently available. The LFT modeling method and preliminary software tool presented in this paper are shown to compare favorably with these methods.
Space exploration applications can benefit greatly from autonomous systems. Great distances, limited communications and high costs make direct operations impossible while mandating operations reliability and efficiency beyond what traditional commanding can provide. Autonomous systems can improve reliability and enhance spacecraft capability significantly. However, there is reluctance to utilizing autonomous systems. In part this is due to general hesitation about new technologies, but a more tangible concern is that of reliability of predictability of autonomous software. In this paper, we describe ongoing work aimed at increasing robustness and predictability of autonomous software, with the ultimate goal of building trust in such systems. The work combines state-of-the-art technologies and capabilities in autonomous systems with advanced validation and synthesis techniques. The focus of this paper is on the autonomous system architecture that has been defined, and on how it enables the application of validation techniques for resulting autonomous systems.
In code division multiple access (CDMA), high efficiency for spectrum usage and robust jamming resistance have been increasingly important.