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At least 523 records · Page 29

Global Design Optimization for Fluid Machinery Applications

Recent experiences in utilizing the global optimization methodology, based on polynomial and neural network techniques for fluid machinery design are summarized. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. Another advantage is that these methods do not need to calculate the sensitivity of each design variable locally. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables and methods for predicting the model performance. Examples of applications selected from rocket propulsion components including a supersonic turbine and an injector element and a turbulent flow diffuser are used to illustrate the usefulness of the global optimization method.

Shyy, Wei↗

Behavior Of Costas Loop In Reception Of Telemetry

Report presents study of behavior of Costas loop in reception of binary non-return-to-zero telemetry signal phase-shift-modulated onto sinusoidal or square-wave subcarrier signal in turn phase-modulated onto carrier signal. Equations describe degradation of performance of Costas loop in terms of phase jitter, conditions causing loss of lock, and other effects. Costas loop used to track telemetry signal with residual carrier in presence of Doppler shift. Performance optimized by suitable choice of bit rate, waveform and frequency of subcarrier, and noise bandwidth of filters in arms of Costas loop.

Nguyen, Tien Manh↗

Prospects and progress of high Tc superconductivity for space applications

Current research in the area of high temperature superconductivity is organized around four key areas: communications and data, sensors and cryogenics, propulsion and power, and space materials technology. Recently, laser ablated YBa2Cu3O(7-x) films on LaAlO3 produced far superior RF characteristics when compared to metallic films on the same substrate. The achievement has enabled a number of unique microwave device applications, such as low insertion loss phase shifters and high-Q filters. Melt texturing and melt-quenched techniques are being used to produce bulk material with optimized magnetic properties. These yttrium-enriched materials possess enhanced flux pinning characteristics and could lead to prototype cryocooler bearings. Significant progress has also occurred in bolometer and current lead technology. Studies were conducted to evaluate the effect of high temperature superconducting materials on the performance and life of high power magnetoplasma-dynamic thrusters. Extended studies were also performed to evaluate the benefit of superconducting magnetic energy storage for LEO space station, lunar, and Mars mission applications.

Romanofsky, Robert R.↗

Suboptimal schemes for atmospheric data assimilation based on the Kalman filter

This work is directed toward approximating the evolution of forecast error covariances for data assimilation. The performance of different algorithms based on simplification of the standard Kalman filter (KF) is studied. These are suboptimal schemes (SOSs) when compared to the KF, which is optimal for linear problems with known statistics. The SOSs considered here are several versions of optimal interpolation (OI), a scheme for height error variance advection, and a simplified KF in which the full height error covariance is advected. To employ a methodology for exact comparison among these schemes, a linear environment is maintained, in which a beta-plane shallow-water model linearized about a constant zonal flow is chosen for the test-bed dynamics. The results show that constructing dynamically balanced forecast error covariances rather than using conventional geostrophically balanced ones is essential for successful performance of any SOS. A posteriori initialization of SOSs to compensate for model - data imbalance sometimes results in poor performance. Instead, properly constructed dynamically balanced forecast error covariances eliminate the need for initialization. When the SOSs studied here make use of dynamically balanced forecast error covariances, the difference among their performances progresses naturally from conventional OI to the KF. In fact, the results suggest that even modest enhancements of OI, such as including an approximate dynamical equation for height error variances while leaving height error correlation structure homogeneous, go a long way toward achieving the performance of the KF, provided that dynamically balanced cross-covariances are constructed and that model errors are accounted for properly. The results indicate that such enhancements are necessary if unconventional data are to have a positive impact.

Todling, Ricardo↗

Stochastic Filtering of Rain Profiles Using Radar, Surface-Referenced Radar, or Combined Radar-Radiometer Measurements

This paper describes a computationally efficient nearly optimal Bayesian algorithm to estimate rain (and drop size distribution) profiles, given a radar reflectivity profile at a single attenuating wavelength. In addition to estimating the averages of all the mutually ambiguous combinations of rain parameters that can produce the data observed, the approach also calculates the n-ns uncertainty in its estimates (this uncertainty thus quantifies "the amount of ambiguity" in the "solution"). The paper also describes a more general approach that can make estimates based on a radar reflectivity profile together with an approximate measurement of the path-integrated attenuation, or a radar reflectivity profile and a set of passive microwave brightness temperatures. This more general "combined" algorithm is currently being adapted for the Tropical Rainfall Measuring Mission.

Haddad, Ziad S.↗

A simulation study of turbofan engine deterioration estimation using Kalman filtering techniques

Deterioration of engine components may cause off-normal engine operation. The result is an unecessary loss of performance, because the fixed schedules are designed to accommodate a wide range of engine health. These fixed control schedules may not be optimal for a deteriorated engine. This problem may be solved by including a measure of deterioration in determining the control variables. These engine deterioration parameters usually cannot be measured directly but can be estimated. A Kalman filter design is presented for estimating two performance parameters that account for engine deterioration: high and low pressure turbine delta efficiencies. The delta efficiency parameters model variations of the high and low pressure turbine efficiencies from nominal values. The filter has a design condition of Mach 0.90, 30,000 ft altitude, and 47 deg power level angle (PLA). It was evaluated using a nonlinear simulation of the F100 engine model derivative (EMD) engine, at the design Mach number and altitude over a PLA range of 43 to 55 deg. It was found that known high pressure turbine delta efficiencies of -2.5 percent and low pressure turbine delta efficiencies of -1.0 percent can be estimated with an accuracy of + or - 0.25 percent efficiency with a Kalman filter. If both the high and low pressure turbine are deteriorated, the delta efficiencies of -2.5 percent to both turbines can be estimated with the same accuracy.

Lambert, Heather H.↗

High efficiency ground data transmission

It is demonstrated that state-of-the-art communications technology can be implemented and reliably operated on a global basis to increase the transmission rates and efficiencies on circuits with bandwidths greater than the typical speech channel. Optimization is affected by optimum clock recovery procedures, multilevel pulse amplitude modulation, single sideband amplitude modulation, transversal filter equalizers, data scrambling, and active compensation for phase instability.

Dickinson, W. B.↗

Measurement updating using the U-D factorization

A new mechanization of the Kalman updating algorithm based on a U-D factorization of the estimate error covariance is introduced. Efficient and stable updating recursions are developed for the unit upper triangular factor U and the diagonal factor D, treating only the parameter estimation problem. Properties of the factorization update performed here include efficient one point at a time processing that requires little more computation than the optimal but numerically unstable conventional Kalman measurement update algorithm, and stability that compares with the square root filter.

Bierman, G. J.↗

Flight-test results using nonlinear control with the F-8C digital fly-by-wire aircraft

The design and operation of the cooperative advanced digital research experiment (CADRE) to develop nonlinear pitch flight control algorithms is described, and the results of an in-flight evaluation using the F-8C digital fly-by-wire (DFBW) research aircraft are presented. The CADRE controller is described, including the initial filter, linear command prefilter, nonlinear command prefilter, and gain scheduling. The variable-integral control-to-optimize response of the controller is considered, and CADRE parameter combinations are addressed. The remotely-augmented-vehicle interface used in the DFBW aircraft experiment is discussed. The distanct-tracking and close-formation tracking evaluation tasks for the aircraft are described along with evaluation configurations, and the test results are presented and discussed. The latter indicate that a nonlinear adaptive controller is a feasible control system technique for the fighter tracking task.

Larson, R. R.↗

KL techniques for optimal processing of time sequential imagery

Time-sequential imagery is difficult to analyze because of its high dimensionality. This paper advances a new algorithm that screens input data in an intelligent way, discards data with negligible information, and uses the remaining images to represent the sequence in an optimal compact form. Data are presented to illustrate how this algorithm can be used to do novelty filtering, novelty detection, segmentation, background independent modeling, and classification.

Vermeulen, Pieter↗

Spectral dispersion and fringe detection in IOTA

Pupil plane beam combination, spectral dispersion, detection, and fringe tracking are discussed for the IOTA interferometer. A new spectrometer design is presented in which the angular dispersion with respect to wavenumber is nearly constant. The dispersing element is a type of grism, a series combination of grating and prism, in which the constant parts of the dispersion add, but the slopes cancel. This grism is optimized for the display of channelled spectra. The dispersed fringes can be tracked by a matched-filter photon-counting correlator algorithm. This algorithm requires very few arithmetic operations per detected photon, making it well-suited for real-time fringe tracking. The algorithm is able to adapt to different stellar spectral types, intensity levels, and atmospheric time constants. The results of numerical experiments are reported.

Traub, W. A.↗

Dynamic rain fade compensation techniques for the advanced communications technology satellite

The dynamic and composite nature of propagation impairments that are incurred on earth-space communications links at frequencies in and above the 30/20 GHz Ka band necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) project by the implementation of optimal processing schemes derived through the use of the ACTS Rain Attenuation Prediction Model and nonlinear Markov filtering theory. The ACTS Rain Attenuation Prediction Model discerns climatological variations on the order of 0.5 deg in latitude and longitude in the continental U.S. The time-dependent portion of the model gives precise availability predictions for the 'spot beam' links of ACTS. However, the structure of the dynamic portion of the model, which yields performance parameters such as fade duration probabilities, is isomorphic to the state-variable approach of stochastic control theory and is amenable to the design of such statistical fade processing schemes which can be made specific to the particular climatological location at which they are employed.

Manning, Robert M.↗

Machine-Vision Aids for Improved Flight Operations

The development of machine vision based pilot aids to help reduce night approach and landing accidents is explored. The techniques developed are motivated by the desire to use the available information sources for navigation such as the airport lighting layout, attitude sensors and Global Positioning System to derive more precise aircraft position and orientation information. The fact that airport lighting geometry is known and that images of airport lighting can be acquired by the camera, has lead to the synthesis of machine vision based algorithms for runway relative aircraft position and orientation estimation. The main contribution of this research is the synthesis of seven navigation algorithms based on two broad families of solutions. The first family of solution methods consists of techniques that reconstruct the airport lighting layout from the camera image and then estimate the aircraft position components by comparing the reconstructed lighting layout geometry with the known model of the airport lighting layout geometry. The second family of methods comprises techniques that synthesize the image of the airport lighting layout using a camera model and estimate the aircraft position and orientation by comparing this image with the actual image of the airport lighting acquired by the camera. Algorithms 1 through 4 belong to the first family of solutions while Algorithms 5 through 7 belong to the second family of solutions. Algorithms 1 and 2 are parameter optimization methods, Algorithms 3 and 4 are feature correspondence methods and Algorithms 5 through 7 are Kalman filter centered algorithms. Results of computer simulation are presented to demonstrate the performance of all the seven algorithms developed.

Menon, P. K.↗

Life Cycle Testing of Ba(x)Sr(1-x)TiO3 Ferroelectric Thin Films in a Tunable Microwave Device

Thin film ferroelectrics are being studied as candidates for novel tunable microwave components such as tunable filters, tunable oscillators, and phase shifters for applications in phased array antennas. Much work has been done optimizing the ferroelectric material and in producing proof-of-concepts of these components. However, little attention has been given to their reliability. In this study we present our results on the reliability of high quality K-band phase shifters made of Ba(sub x)Sr(sub 1-x)TiO3 (BSTO) ferroelectric thin films (0.5 to 0.75 micrometers thick) on MgO and LAO. The phase shift and insertion loss were measured at 300 K over 104 operation cycles within a 0 to 400 V dc bias range (0 to 40 V/micrometer) at 15, 18, and 22 GHz. Results for these phase shifters indicate that in general there were no appreciable changes in phase shift after 4x10(exp 4) cycles, suggesting that these phase shifters are robust enough to sustain optimal performance under the operating mode typical of fast tracking phased arrays.

Miranda, Felix A.↗

GPU Accelerated Vector Median Filter

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

Aras, Rifat↗

Space Launch System Ascent Flight Control Design

A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. As the SLS configurations represent a potentially significant increase in complexity and performance capability of the integrated flight vehicle, it was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight load relief through the use of a nonlinear observer driven by acceleration measurements, and envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.

VanZwieten, Tannen S.↗

Space Launch System Ascent Flight Control Design

A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. The SLS configurations represent a potentially significant increase in complexity and performance capability when compared with other manned launch vehicles. It was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight disturbance compensation through the use of nonlinear observers driven by acceleration measurements. Envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.

Orr, Jeb S.↗