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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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Automatic input data generation for finite element method using algorithm based on complex geometrical configurations topological classification in terms of natural coordinates
An approach to extracting depth information out of a stereo pair of images is described. Special camera pair configurations are shown to be effective in reducing complexity. A simple algorithm which pairs objects in the two images and allows verification is described.
One approach to the problem of simplifying complex nonlinear filtering algorithms is through using stratified probability approximations where the continuous probability density functions of certain random variables are represented by discrete mass approximations. This technique is developed in this paper and used to simplify the filtering algorithms developed for the optimum receiver for signals corrupted by both additive and multiplicative noise.
A precise statement of the relationship between sequential computation at one rate, parallel or pipeline computation at a much higher rate, the data movement rate between levels of memory, the fraction of inherently sequential operations or data that must be processed sequentially, the fraction of data to be moved that cannot be overlapped with computation, and the relative computational complexity of the algorithms for the two processes, scalar and vector, was developed. The relationship should be applied to the multirate processes that obtain in the employment of various new or proposed computer architectures for computational aerodynamics. The relationship, an efficiency measure that the single user of the computer system perceives, argues strongly in favor of separating scalar and vector processes, sometimes referred to as loosely coupled processes, to achieve optimum use of hardware.
The author has identified the following significant results. Data sets for corn, soybeans, winter wheat, and spring wheat were used to evaluate the following schemes for crop identification: (1) per point Gaussian maximum classifier; (2) per point sum of normal densities classifiers; (3) per point linear classifier; (4) per point Gaussian maximum likelihood decision tree classifiers; and (5) texture sensitive per field Gaussian maximum likelihood classifier. Test site location and classifier both had significant effects on classification accuracy of small grains; classifiers did not differ significantly in overall accuracy, with the majority of the difference among classifiers being attributed to training method rather than to the classification algorithm applied. The complexity of use and computer costs for the classifiers varied significantly. A linear classification rule which assigns each pixel to the class whose mean is closest in Euclidean distance was the easiest for the analyst and cost the least per classification.
A process for adjusting perturbation magnitude for accurate difference-quotient estimation of derivatives is described. The process is intended to be carried out sequentially, alternating with iterations of a parameter-optimization algorithm. A more complex and computationally-expensive scheme for occasional auxiliary use is also described.
A large class of computational problems is characterized by frequent synchronization, and computational requirements which change as a function of time. When such a problem must be solved on a message passing multiprocessor machine, the combination of these characteristics lead to system performance which decreases in time. Performance can be improved with periodic redistribution of computational load; however, redistribution can exact a sometimes large delay cost. We study the issue of deciding when to invoke a global load remapping mechanism. Such a decision policy must effectively weigh the costs of remapping against the performance benefits. We treat this problem by constructing two analytic models which exhibit stochastically decreasing performance. One model is quite tractable; we are able to describe the optimal remapping algorithm, and the optimal decision policy governing when to invoke that algorithm. However, computational complexity prohibits the use of the optimal remapping decision policy. We then study the performance of a general remapping policy on both analytic models. This policy attempts to minimize a statistic W(n) which measures the system degradation (including the cost of remapping) per computation step over a period of n steps. We show that as a function of time, the expected value of W(n) has at most one minimum, and that when this minimum exists it defines the optimal fixed-interval remapping policy. Our decision policy appeals to this result by remapping when it estimates that W(n) is minimized. Our performance data suggests that this policy effectively finds the natural frequency of remapping. We also use the analytic models to express the relationship between performance and remapping cost, number of processors, and the computation's stochastic activity.
A computational approach is taken to solve the optimal nonlinear stochastic control problem. The approach is to systematically solve the stochastic dynamic programming equations forward in time, using a nested stochastic approximation technique. Although computationally intensive, this provides a straightforward numerical solution for this class of problems and provides an alternative to the usual dimensionality problem associated with solving the dynamic programming equations backward in time. It is shown that the cost degrades monotonically as the complexity of the algorithm is reduced. This provides a strategy for suboptimal control with clear performance/computation tradeoffs. A numerical study focusing on a generic optimal stochastic adaptive control example is included to demonstrate the feasibility of the method.
Ada packages implementing selected mathematical functions for the support of scientific and engineering applications were written. The packages provide the Ada programmer with the mathematical function support found in the languages Pascal and FORTRAN as well as an extended precision arithmetic and a complete complex arithmetic. The algorithms used are fully described and analyzed. Implementation assumes that the Ada type FLOAT objects fully conform to the IEEE 754-1985 standard for single binary floating-point arithmetic, and that INTEGER objects are 32-bit entities. Codes for the Ada packages are included as appendixes.
In order to meet the data research requirements of the Safety, Reliability & Quality Assurance activities at Kennedy Space Center (KSC), a new computer search method for technical data documents was developed. By their very nature, technical documents are partially encrypted because of the author's use of acronyms, abbreviations, and shortcut notations. This problem of computerized searching is compounded at KSC by the volume of documentation that is produced during normal Space Shuttle operations. The Centralized Document Database (CDD) is designed to solve this problem. It provides a common interface to an unlimited number of files of various sizes, with the capability to perform any diversified types and levels of data searches. The heart of the CDD is the nature and capability of its search algorithms. The most complex form of search that the program uses is with the use of a domain-specific database of acronyms, abbreviations, synonyms, and word frequency tables. This database, along with basic sentence parsing, is used to convert a request for information into a relational network. This network is used as a filter on the original document file to determine the most likely locations for the data requested. This type of search will locate information that traditional techniques, (i.e., Boolean structured key-word searching), would not find.
A new computational method and algorithm, based on complex Fourier analysis, is used to derive the spectral density of plane and circularly polarized fluctuation components of the interplanetary magnetic field. Applications of the method have been made using HEOS 2 (1 AU), Pioneer 10 (5 AU), Pioneer 11 (20 AU), and International Cometary Explorer (ICE) (Giocabini-Zinner's comet) data sets. The results show the existence of circularly polarized magnetohydrodynamic (MHD) waves in all cases.
The simulation of flowfields in the transition flow regime is notoriously difficult with high demands on computer resources (CPU time and storage) and user expertise/labor. This paper describes a new, efficient code which has been developed to simulate high Knudsen number flowfields in three dimensions about bodies of arbitrarily complex geometry. The algorithm has been tested over a wide range of conditions, from free molecular to near-continuum flow regimes, for slender and blunt bodies, for re-entry vehicles and spacecraft. A series of validation tests have been conducted using both wind-tunnel measurements and flight data.
This report presents a study on the CCSDS recommended 8-dimensional 8 PSK Trellis Coded Modulation (TCM) scheme. The important steps of the CCSDS scheme include: conversion of serial data into parallel form, differential encoding, convolutional encoding, constellation mapping, and filtering the 8-PSK symbols using the square root raised cosine (SRRC) pulses. The last step, namely the filtering of the 8 PSK symbols using SRRC pulses, significantly affects the bandwidth of the signal. If a nonlinear power amplifier is used, the SRRC filtered signal creates spectral regrowth. The purpose of this report is to investigate a technique, called the smooth phase interpolated keying (SPIK), that can provide an alternative to SRRC filtering so that good spectral as well as power efficiencies can be obtained with the CCSDS encoder. The results of this study show that the CCSDS encoder does not affect the spectral shape of the SRRC filtered signal or the SPIK signal. When a nonlinear traveling wave tube amplifier (TWTA) is used, the spectral performance of the SRRC signal degrades significantly while the spectral performance of SPIK remains unaffected. The degrading effect of a nonlinear solid state power amplifier (SSPA) on SRRC is found to be less than that due to a nonlinear TWTA. However, in both cases, the spectral performance of the SRRC modulated signal is worse than that of the SPIK signal. The bit error rate (BER) performance of the SRRC signal in a linear amplifier environment is about 2.5 dB better than that of the SPIK signal when both the receivers use algorithms of similar complexity. In a nonlinear TWTA environment, the SRRC signal requires accurate phase tracking since the TWTA introduces additional phase distortion. This problem does not arise with SPIK signal due to its constant envelope property. When a nonlinear amplifier is used, the SRRC method loses nearly 1 dB in the bit error rate performance. The SPIK signal does not lose any performance. Thus the performance gap between SRRC and SPIK reduces. The BER performance of SPIK can be improved even further by using a more optimal receiver. A similar optimal receiver for SRRC is quite complex since the amplifier distorts the pulse shape. However, this requires further investigation and is not covered in this report.
The cosine or correlation measures of similarity used to cluster high dimensional data are interpreted as projections, and the orthogonal components are used to define a complementary dissimilarity measure to form a similarity-dissimilarity measure pair. Using a geometrical approach, a number of properties of this pair is established. This approach is also extended to general inner-product spaces of any dimension. These properties include the triangle inequality for the defined dissimilarity measure, error estimates for the triangle inequality and bounds on both measures that can be obtained with a few floating-point operations from previously computed values of the measures. The bounds and error estimates for the similarity and dissimilarity measures can be used to reduce the computational complexity of clustering algorithms and enhance their scalability, and the triangle inequality allows the design of clustering algorithms for high dimensional distributed data.
This paper addresses the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. The approach taken uses unsupervised clustering of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by detailed analysis of outliers to detect anomalies. As the LCS measure is expensive to compute, the first part of the paper discusses existing algorithms, such as the Hunt-Szymanski algorithm, that have low time-complexity. We then discuss why these algorithms often do not work well in practice and present a new hybrid algorithm for computing the LCS that, in our tests, outperforms the Hunt-Szymanski algorithm by a factor of five. The second part of the paper presents new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. The algorithms provide a coherent description to an analyst of the anomalies in the sequence, compared to more normal sequences. The algorithms we present are general and domain-independent, so we discuss applications in related areas such as anomaly detection.
High contrast imaging from space relies on coronagraphs to limit diffraction and a wavefront control systems to compensate for imperfections in both the telescope optics and the coronagraph. The extreme contrast required (up to 10(exp -10) for terrestrial planets) puts severe requirements on the wavefront control system, as the achievable contrast is limited by the quality of the wavefront. This paper presents a general closed loop correction algorithm for high contrast imaging coronagraphs by minimizing the energy in a predefined region in the image where terrestrial planets could be found. The estimation part of the algorithm reconstructs the complex field in the image plane using phase diversity caused by the deformable mirror. This method has been shown to achieve faster and better correction than classical speckle nulling.
The Lunar Reconnaissance Orbiter (LRO), a spacecraft designed and built at the National Aeronautics and Space Administration s (NASA) Goddard Space Flight Center (GSFC) in Greenbelt, MD, was launched on June 18, 2009 from Cape Canaveral. It is currently in orbit about the Moon taking detailed science measurements and providing a highly accurate mapping of the suface in preparation for the future return of astronauts to a permanent moon base. Onboard the spacecraft is a complex set of algorithms designed by the attitude control engineers at GSFC to control the pointig for all operational events, including anomalies that require the spacecraft to be put into a well known attitude configuration for a sufficiently long duration to allow for the investigation and correction of the anomaly. GSFC level requirements state that each spacecraft s control system design must include a configuration for this pointing and lso be able to maintain a thermally safe and power positive attitude. This stable control algorithm for anomalous events is commonly referred to as the safe mode and consists of control logic thatwill put the spacecraft in this safe configuration defined by the spacecraft s hardware, power and environment capabilities and limitations. The LRO Sun Safe mode consists of a coarse sun-pointing set of algorithms that puts the spacecraft into this thermally safe and power positive attitude and can be achieved wihin a required amount of time from any initial attitude, provided that the system momentum is within the momentum capability of the reaction wheels. On LRO the Sun Safe mode makes use of coarse sun sensors (CSS), an inertial reference unit (IRU) and reaction wheels (RW) to slew the spacecraft to a solar inertial pointing. The CSS and reaction wheels have some level of redundancy because of their numbers. However, the IRU is a single-point-failure piece of hardware. Without the rate information provided by the IRU, the Sun Safe control algorithms could not maintain the required pointing, so a sub-mode of the Sun Safe mode that does not use the IRU was designed. This submode, referred to as the Sun Safe Gyroless control mode, consists of an algorithm that estimates rate information from the CSS and the RW measurements. RW momentum information is used to estimate the body rate parallel to the target sunline, which CSS alone would not be able to observe. Sun Safe can be autonomously, or via ground command, entered from any other control mode and in the event the IRU is not providing rate information, the control mode is switched to the gyroless submode. This paper looks at the design of the Sun Safe modes and discusses the constraints placed on the algorithm and how the mode wored around these constraints. Items of particular interest include CSS placement on the Solar Array (SA) and its implications to design, estimation of body rate information for the Sun Safe Gyroless control mode, and the effect of solar eclipse on each of the Sun Safe modes. Placing CSS on the SA was necessary for the means to put the Sun along the targeted sun-line, nominally normal to the SA panels, for all operational considerations. This had design implications for determining a sun vector during normal SA operations, if one or both gimbals become inoperable and when the SA is in a stowed configuration. The ability of body rate estimation in Sun Safe Gyroless not only uses CSS sun vector data but requires RW momentum measuremens to estimate rates parallel to the sun-line. LRO encounters solar eclipses of some length for most of its orbits about the Moon. With the lack of CSS measurement data a design was implemented in both Sun Safe and Sun Safe Gyroless, they differ because of having or not having IRU measurement data, to carry the spacecraft through these eclipse periods. This paper also includes some discussion of sun avoidance and how it affected design decisions during nominal and eclipse perids for each of the Sun Safe modes.
A combination of methods is proposed of predicting spacecraft trajectories that possibly include multiple maneuvers and/or perturbing accelerations, with greater speed, accuracy, and repeatability than were heretofore achievable. The combination is denoted the WeavEncke method because it is based on unpublished studies by Jonathan Weaver of the orbit-prediction formulation of the noted astronomer Johann Franz Encke. Weaver evaluated a number of alternatives that arise within that formulation, arriving at an orbit-predicting algorithm optimized for complex trajectory operations. In the WeavEncke method, Encke's method of prediction of perturbed orbits is enhanced by application of modern numerical methods. Among these methods are efficient Kepler s-equation time-of-flight solutions and self-starting numerical integration with time as the independent variable. Self-starting numerical integration satisfies the requirements for accuracy, reproducibility, and efficiency (and, hence, speed). Self-starting numerical integration also supports fully analytic regulation of integration step sizes, thereby further increasing speed while maintaining accuracy.