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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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At least 703 records · Page 39

An economical semi-analytical orbit theory for micro-computer applications

An economical algorithm is presented for predicting the position of a satellite perturbed by drag and zonal harmonics J sub 2 through J sub 4. Simplicity being of the essence, drag is modeled as a secular decay rate in the semi-axis (retarded motion); with the zonal perturbations modeled from a modified version of the Brouwers formulas. The algorithm is developed as: an alternative on-board orbit predictor; a back up propagator requiring low energy consumption; or a ground based propagator for microcomputer applications (e.g., at the foot of an antenna). An O(J sub 2) secular retarded state partial matrix (matrizant) is also given to employ with state estimation. The theory was implemented in BASIC on an inexpensive microcomputer, the program occupying under 8K bytes of memory. Simulated trajectory data and real tracking data are employed to illustrate the theory's ability to accurately accommodate oblateness and drag effects.

Gordon, R. A.↗

The role of radiation-dynamics interaction in regional numerical weather prediction

The role of radiation-dynamics interaction in regional numerical weather prediction of severe storm environment and mesoscale convective systems over the United States is researched. Based upon the earlier numerical model simulation experiments, it is believed that such interaction can have a profound impact on the dynamics and thermodynamics of regional weather systems. The research will be carried out using real-data model forecast experiments performed on the Cray-X/MP computer. The forecasting system to be used is a comprehensive mesoscale prediction system which includes analysis and initialization, the dynamic model, and the post-forecast diagnosis codes. The model physics are currently undergoing many improvements in parameterizing radiation processes in the model atmosphere. The forecast experiments in conjunction with in-depth model verification and diagnosis are aimed at a quantitative understanding of the interaction between atmospheric radiation and regional dynamical processes in mesoscale models as well as in nature. Thus, significant advances in regional numerical weather prediction can be made. Results shall also provide valuable information for observational designs in the area of remote sensing techniques to study the characteristics of air-land thermal interaction and moist processes under various atmospheric conditions.

Chang, Chia-Bo↗

On the generation of a bubbly universe - A quantitative assessment of the CfA slice

A first attempt is made to calculate the properties of the matter distribution in a universe filled with overlapping bubbles produced by multiple explosions. Each spherical shell follows the cosmological Sedov-Taylor solution until it encounters another shell. Thereafter, mergers are allowed to occur in pairs on the basis of N-body results. At the final epoch, the matrix of overlapping shells is populated with 'galaxies' and the properties of slices through the numerically constructed cube compare well with CfA survey results for specified initial conditions. A statistic is found which measures the distance distribution from uniformly distributed points to the nearest galaxies on the projected plane which appears to provide a good measure of the bubbly character of the galaxy distribution. In a quantitative analysis of the CfA 'slice of the universe', a very good match is found between simulation and the real data for final average bubble radii of (13.5 + or - 1.5)/h Mpc with formal filling factor 1.0-1.5 or actual filling factor of 65-80 percent.

Ostriker, J. P.↗

Baseline estimation with semidynamic and geometric satellite methods

The potential of a semidynamic method for an estimation of satellite position was investigated in a real data environment, using observations of Lageos collected during the MERIT campaign. In this method, quasi-simultaneous laser range observations of Lageos by pairs of stations were transformed to simultaneous range differences (SRDs), in order to reduce the effects of orbital and observational residual biases. Baselines obtained via the SRD method were compared to those obtained by the geometric method. It was found that, for baselines of regional extent, the SRD method is very efficient and at least as accurate as the more complex dynamic methods.

Dedes, George C.↗

Extended Kalman filter for attitude estimation of the earth radiation budget satellite

The design and testing of an Extended Kalman Filter (EKF) for ground attitude determination, misalignment estimation and sensor calibration of the Earth Radiation Budget Satellite (ERBS) are described. Attitude is represented by the quaternion of rotation and the attitude estimation error is defined as an additive error. Quaternion normalization is used for increasing the convergence rate and for minimizing the need for filter tuning. The development of the filter dynamic model, the gyro error model and the measurement models of the Sun sensors, the IR horizon scanner and the magnetometers which are used to generate vector measurements are also presented. The filter is applied to real data transmitted by ERBS sensors. Results are presented and analyzed and the EKF advantages as well as sensitivities are discussed. On the whole the filter meets the expected synergism, accuracy and robustness.

Deutschmann, Julie↗

A PBL-radiation model for application to regional numerical weather prediction

Often in the short-range limited-area numerical weather prediction (NWP) of extratropical weather systems the effects of planetary boundary layer (PBL) processes are considered secondarily important. However, it may not be the case for the regional NWP of mesoscale convective systems over the arid and semi-arid highlands of the southwestern and south-central United States in late spring and summer. Over these dry regions, the PBL can grow quite high up into the lower middle troposphere (600 mb) due to very effective solar heating and hence a vigorous air-land thermal interaction can occur. The interaction representing a major heat source for regional dynamical systems can not be ignored. A one-dimensional PBL-radiation model was developed. The model PBL consists of a constant-flux surface layer superposed with a well-mixed (Ekman) layer. The vertical eddy mixing coefficients for heat and momentum in the surface layer are determined according to the surface similarity theory, while their vertical profiles in the Ekman layer are specified with a cubic polynomial. Prognostic equations are used for predicting the height of the nonneutral PBL. The atmospheric radiation is parameterized to define the surface heat source/sink for the growth and decay of the PBL. A series of real-data numerical experiments has been carried out to obtain a physical understanding how the model performs under various atmospheric and surface conditions. This one-dimensional model will eventually be incorporated into a mesoscale prediction system. The ultimate goal of this research is to improve the NWP of mesoscale convective storms over land.

Chang, Chia-Bo↗

Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately

The mathematical relationships between the shape parameter Beta and estimates of reliability and a life limit lower bound for the two parameter Weibull distribution are investigated. It is shown that under rather general conditions, both the reliability lower bound and the allowable life limit lower bound (often called a tolerance limit) have unique global minimums over a range of Beta. Hence lower bound solutions can be obtained without assuming or estimating Beta. The existence and uniqueness of these lower bounds are proven. Some real data examples are given to show how these lower bounds can be easily established and to demonstrate their practicality. The method developed here has proven to be extremely useful when using the Weibull distribution in analysis of no-failure or few-failures data. The results are applicable not only in the aerospace industry but anywhere that system reliabilities are high.

Huang, Zhaofeng↗

Ionospheric refraction effects on orbit determination using the orbit determination error analysis system

The influence of ionospheric refraction on orbit determination was studied through the use of the Orbit Determination Error Analysis System (ODEAS). The results of a study of the orbital state estimate errors due to the ionospheric refraction corrections, particularly for measurements involving spacecraft-to-spacecraft tracking links, are presented. In current operational practice at the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), the ionospheric refraction effects on the tracking measurements are modeled in the Goddard Trajectory Determination System (GTDS) using the Bent ionospheric model. While GTDS has the capability of incorporating the ionospheric refraction effects for measurements involving ground-to-spacecraft tracking links, such as those generated by the Ground Spaceflight Tracking and Data Network (GSTDN), it does not have the capability to incorporate the refraction effects for spacecraft-to-spacecraft tracking links for measurements generated by the Tracking and Data Relay Satellite System (TDRSS). The lack of this particular capability in GTDS raised some concern about the achievable accuracy of the estimated orbit for certain classes of spacecraft missions that require high-precision orbits. Using an enhanced research version of GTDS, some efforts have already been made to assess the importance of the spacecraft-to-spacecraft ionospheric refraction corrections in an orbit determination process. While these studies were performed using simulated data or real tracking data in definitive orbit determination modes, the study results presented here were obtained by means of covariance analysis simulating the weighted least-squares method used in orbit determination.

Yee, C. P.↗

Experiments on neural network architectures for fuzzy logic

The use of fuzzy logic to model and manage uncertainty in a rule-based system places high computational demands on an inference engine. In an earlier paper, the authors introduced a trainable neural network structure for fuzzy logic. These networks can learn and extrapolate complex relationships between possibility distributions for the antecedents and consequents in the rules. Here, the power of these networks is further explored. The insensitivity of the output to noisy input distributions (which are likely if the clauses are generated from real data) is demonstrated as well as the ability of the networks to internalize multiple conjunctive clause and disjunctive clause rules. Since different rules with the same variables can be encoded in a single network, this approach to fuzzy logic inference provides a natural mechanism for rule conflict resolution.

Keller, James M.↗

Extended Kalman Filter for attitude estimation of the Earth Radiation Budget Satellite

The design and testing of an Extended Kalman Filter (EKF) for ground attitude determination, misalignment estimation and sensor calibration of the Earth Radiation Budget Satellite (ERBS) are described. Attitude is represented by the quaternion of rotation and the attitude estimation error is defined as an additive error. Quaternion normalization is used for increasing the convergence rate and for minimizing the need for filter tuning. The development of the filter dynamic model, the gyro error model and the measurement models of the sun sensors, the IR horizon scanner and the magnetometers which are used to generate vector measurements are also presented. The filter is applied to real data transmitted by ERBS sensors. Results are presented and analyzed and the EKF advantages as well as sensitivities are discussed. On the whole the filter meets the expected synergism, accuracy and robustness.

Deutschmann, Julie↗

Automatic ground control point recognition with parallel associative memory

The basic principle of the associative memory is to match the unknown input pattern against a stored training set, and responding with the 'closest match' and the corresponding label. Generally, an associative memory system requires two preparatory steps: selecting attributes of the pattern class, and training the system by associating patterns with labels. Experimental results gained from using Parallel Associative Memory are presented. The primary concern is an automatic search for ground control points in aerial photographs. Synthetic patterns are tested followed by real data. The results are encouraging as a relatively high level of correct matches is reached.

Al-Tahir, Raid↗

Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately

The mathematical relationships between the shape parameter Beta and estimates of reliability and a life limit lower bound for the two parameter Weibull distribution are investigated. It is shown that under rather general conditions, both the reliability lower bound and the allowable life limit lower bound (often called a tolerance limit) have unique global minimums over a range of Beta. Hence lower bound solutions can be obtained without assuming or estimating Beta. The existence and uniqueness of these lower bounds are proven. Some real data examples are given to show how these lower bounds can be easily established and to demonstrate their practicality. The method developed here has proven to be extremely useful when using the Weibull distribution in analysis of no-failure or few-failures data. The results are applicable not only in the aerospace industry but anywhere that system reliabilities are high.

Huang, Zhaofeng↗

An Embedded Rule-Based Diagnostic Expert System in Ada

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Jones, Robert E.↗

A global multilevel atmospheric model using a vector semi-Lagrangian finite-difference scheme. I - Adiabatic formulation

An adiabatic global multilevel primitive equation model using a two time-level, semi-Lagrangian semi-implicit finite-difference integration scheme is presented. A Lorenz grid is used for vertical discretization and a C grid for the horizontal discretization. The momentum equation is discretized in vector form, thus avoiding problems near the poles. The 3D model equations are reduced by a linear transformation to a set of 2D elliptic equations, whose solution is found by means of an efficient direct solver. The model (with minimal physics) is integrated for 10 days starting from an initialized state derived from real data. A resolution of 16 levels in the vertical is used, with various horizontal resolutions. The model is found to be stable and efficient, and to give realistic output fields. Integrations with time steps of 10 min, 30 min, and 1 h are compared, and the differences are found to be acceptable.

Bates, J. R.↗

Hubble Space Telescope characterized by using phase-retrieval algorithms

We describe several results characterizing the Hubble Space Telescope from measured point spread functions by using phase-retrieval algorithms. The Cramer-Rao lower bounds show that point spread functions taken well out of focus result in smaller errors when aberrations are estimated and that, for those images, photon noise is not a limiting factor. Reconstruction experiments with both simulated and real data show that the calculation of wave-front propagation by the retrieval algorithms must be performed with a multiple-plane propagation rather than a simple fast Fourier transform to ensure the high accuracy required. Pupil reconstruction was performed and indicates a misalignment of the optical axis of a camera relay telescope relative to the main telescope. After we accounted for measured spherical aberration in the relay telescope, our estimate of the conic constant of the primary mirror of the HST was - 1.0144.

Fienup, J. R.↗

A nonhydrostatic version of the Penn State-NCAR Mesoscale Model - Validation tests and simulation of an Atlantic cyclone and cold front

A nonhydrostatic extension to the Pennsylvania State University-NCAR Mesoscale Model is presented, which employs reference pressure as the basis for a terrain-following vertical coordinate, and the fully compressible system of equations. It is shown that this model, combined with the existing initialization techniques and the physics of the current hydrostatic model, is capable of real-data simulations on any scale, limited only by data quality and resolution and by computer resources. An example of an explosive cyclone simulation is presented, demonstrating the capability of the nonhydrostatic model to reproduce the hydrostatic model results at large scales.

Dudhia, Jimy↗

Observing system simulation experiments at NASA. Goddard Space Flight Center

A series of realistic simulation studies is being conducted as a cooperative effort between the European Centre for Medium Range Weather Forecasts (ECMWF), the National Meteorological Center (NMC), and the Goddard Laboratory for Atmospheres (GLA), to provide a quantitative assessment of the potential impact of future observing systems on large scale numerical weather prediction. A special objective is to avoid the unrealistic character of earlier simulation studies. Following a brief review of previous simulation studies and real data impact tests, the methodology for the current simulation system will be described. Results from an assessment of the realism of the simulation system and of the potential impact of advanced observing systems on numerical weather prediction and preliminary results utilizing this system will be presented at the conference.

Atlas, R.↗

A multi-variance analysis in the time domain

Recently a new technique for characterizing the noise processes affecting oscillators was introduced. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique was applied to both simulated and real data with excellent results.

Walter, Todd↗