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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Study of high speed complex number algorithms

A method of evaluating the radiation integral on the curved surface of a reflecting antenna is presented. A three dimensional Fourier transform approach is used to generate a two dimensional radiation cross-section along a planer cut at any angle phi through the far field pattern. Salient to the method is an algorithm for evaluating a subset of the total three dimensional discrete Fourier transform results. The subset elements are selectively evaluated to yield data along a geometric plane of constant. The algorithm is extremely efficient so that computation of the induced surface currents via the physical optics approximation dominates the computer time required to compute a radiation pattern. Application to paraboloid reflectors with off-focus feeds in presented, but the method is easily extended to offset antenna systems and reflectors of arbitrary shapes. Numerical results were computed for both gain and phase and are compared with other published work.

Heisler, R.↗
NASA NTRS1973

The calculation of efficient high precision orbits by optimum matching of the formulation and numerical integrator

The development of improved computer algorithms is considered for calculating earth satellite orbital trajectories by optimum selection of the analytical method that minimizes the number of perturbative acceleration computations for a given accuracy. A variation of parameter algorithm considering the equation of motion for a satellite proved superior for the geosynchronous orbit.

Velez, C. E.↗
NASA NTRS1995

Excursion-Set-Mediated Genetic Algorithm

Excursion-set-mediated genetic algorithm (ESMGA) is embodiment of method of searching for and optimizing computerized mathematical models. Incorporates powerful search and optimization techniques based on concepts analogous to natural selection and laws of genetics. In comparison with other genetic algorithms, this one achieves stronger condition for implicit parallelism. Includes three stages of operations in each cycle, analogous to biological generation.

Noever, David↗
NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗
NASA NTRS2012

Orion GN and C Model Based Development: Experience and Lessons Learned

The Orion Guidance Navigation and Control (GN&C) team is charged with developing GN&C algorithms for the Exploration Flight Test One (EFT-1) vehicle. The GN&C team is a joint team consisting primarily of Prime Contractor (Lockheed Martin) and NASA personnel and contractors. Early in the GN&C development cycle the team selected MATLAB/Simulink as the tool for developing GN&C algorithms and Mathworks autocode tools as the means for converting GN&C algorithms to flight software (FSW). This paper provides an assessment of the successes and problems encountered by the GN&C team from the perspective of Orion GN&C developers, integrators, FSW engineers and management. The Orion GN&C approach to graphical development, including simulation tools, standards development and autocode approaches are scored for the main activities that the team has completed through the development phases of the program.

Jackson, Mark C.↗
NASA NTRS2017

QSPIN: A High Level Java API for Quantum Computing Experimentation

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Quantu↗
NASA NTRS2014

Time-Dependent Response Versus Scan Angle for MODIS Reflective Solar Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently operate onboard the National Aeronautics and Space Administration (NASA's) Terra and Aqua spacecraft, launched on December 18, 1999 and May 4, 2002, respectively. MODIS has 36 spectral bands, among which 20 are reflective solar bands (RSBs) covering a spectral range from 0.412 to 2.13 μm. The RSBs are calibrated on orbit using a solar diffuser (SD) and an SD stability monitor and with additional measurements from lunar observations via a space view (SV) port. Selected pseudo-invariant desert sites are also used to track the RSB on-orbit gain change, particularly for short-wavelength bands. MODIS views the Earth surface, SV, and the onboard calibrators using a two-sided scan mirror. The response versus scan angle (RVS) of the scan mirror was characterized prior to launch, and its changes are tracked using observations made at different angles of incidence from onboard SD, lunar, and Earth view (EV) measurements. These observations show that the optical properties of the scan mirror have experienced large wavelength-dependent degradation in both the visible and near infrared spectral regions. Algorithms have been developed to track the on-orbit RVS change using the calibrators and the selected desert sites. These algorithms have been applied to both Terra and Aqua MODIS Level 1B (L1B) to improve the EV data accuracy since L1B Collection 4, refined in Collection 5, and further improved in the latest Collection 6 (C6). In C6, two approaches have been used to derive the time-dependent RVS for MODIS RSB. The first approach relies on data collected from sensor onboard calibrators and mirror side ratios from EV observations. The second approach uses onboard calibrators and EV response trending from selected desert sites. This approach is mainly used for the bands with much larger changes in their time-dependent RVS, such as the Terra MODIS bands 1-4, 8, and 9 and the Aqua MODIS bands 8- and 9. In this paper, the algorithms of these approaches are described, their performance is demonstrated, and their impact on L1B products is discussed. In general, the shorter wavelength bands have experienced a larger on-orbit RVS change, which, in general, are mirror side and detector dependent. The on-orbit RVS change due to the degradation of band 8 can be as large as 35 percent for Terra MODIS and 20 percent for Aqua MODIS. Vital to maintaining the accuracy of the MODIS L1B products is an accurate characterization of the on-orbit RVS change. The derived time-independent RVS, implemented in C6, makes an important improvement to the quality of the MODIS L1B products.

MODIS↗
NASA NTRS2017

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.

Khlopenkov, Konstantin V.↗
NASA NTRS1992

Antenna analysis using neural networks

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

Smith, William T.↗
NASA NTRS2014

Space Launch System Implementation of Adaptive Augmenting Control

Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

Wall, John H.↗
NASA NTRS2012

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗
NASA NTRS1994

On current compositing algorithms

Several techniques exist for compositing the multitemporal NOAA Advanced Very High Resolution Radiometer (AVHRR) data for vegetation studies. The major pixel selection criteria of these techniques rely on the characteristics of the NDVI (Normalized Difference Vegetative Index): appearance of clouds, poor atmospheric conditions, and off-nadir viewing geometries would depress the NDVI values. Consequently, selecting the pixels with the maximum value of NDVI would presumably eliminate these external perturbating effects. However, the maximum NDVI does not always correspond to these ideal conditions. In fact, the NDVI varies with these external factors in an unpredictable way. There was an indication that the maximum NDVI tended to favor the off-nadir view in the forward direction. The resultant composite product would be consequently affected. To improve the multitemporal data via compositing, therefore, both the pixel selection criteria and the classifier NDVI need to be modified or corrected for external factors. The current compositing algorithms were reviewed, and alternatives were proposed to use the combinations of the red and near infrared channels and biological characteristics of vegetation as second criteria in pixel selections. The traditional classifier NDVI was replaced with different vegetation indices. The approach was applied to an AVHRR data set over the HAPEX study site in Niger in 1992. The results showed that the approach improved the AVHRR time series quality and was promising towards the development of an efficient compositing algorithm.

Qi, J.↗
NASA NTRS1975

Study report on interfacing major physiological subsystem models: An approach for developing a whole-body algorithm

Using a whole body algorithm simulation model, a wide variety and large number of stresses as well as different stress levels were simulated including environmental disturbances, metabolic changes, and special experimental situations. Simulation of short term stresses resulted in simultaneous and integrated responses from the cardiovascular, respiratory, and thermoregulatory subsystems and the accuracy of a large number of responding variables was verified. The capability of simulating significantly longer responses was demonstrated by validating a four week bed rest study. In this case, the long term subsystem model was found to reproduce many experimentally observed changes in circulatory dynamics, body fluid-electrolyte regulation, and renal function. The value of systems analysis and the selected design approach for developing a whole body algorithm was demonstrated.

Fitzjerrell, D. G.↗
NASA NTRS1992

Algorithms for airborne Doppler radar wind shear detection

Honeywell has developed algorithms for the detection of wind shear/microburst using airborne Doppler radar. The Honeywell algorithms use three dimensional pattern recognition techniques and the selection of an associated scanning pattern forward of the aircraft. This 'volumetric scan' approach acquires reflectivity, velocity, and spectral width from a three dimensional volume as opposed to the conventional use of a two dimensional azimuthal slice of data at a fixed elevation. The algorithm approach is based on detection and classification of velocity patterns which are indicative of microburst phenomenon while minimizing the false alarms due to ground clutter return. Simulation studies of microburst phenomenon and x-band radar interaction with the microburst have been performed and results of that study are presented. Algorithm performance indetection of both 'wet' and 'dry' microbursts is presented.

Gillberg, Jeff↗
NASA NTRS2002

Field-Programmable Gate Array Computer in Structural Analysis: An Initial Exploration

This paper reports on an initial assessment of using a Field-Programmable Gate Array (FPGA) computational device as a new tool for solving structural mechanics problems. A FPGA is an assemblage of binary gates arranged in logical blocks that are interconnected via software in a manner dependent on the algorithm being implemented and can be reprogrammed thousands of times per second. In effect, this creates a computer specialized for the problem that automatically exploits all the potential for parallel computing intrinsic in an algorithm. This inherent parallelism is the most important feature of the FPGA computational environment. It is therefore important that if a problem offers a choice of different solution algorithms, an algorithm of a higher degree of inherent parallelism should be selected. It is found that in structural analysis, an 'analog computer' style of programming, which solves problems by direct simulation of the terms in the governing differential equations, yields a more favorable solution algorithm than current solution methods. This style of programming is facilitated by a 'drag-and-drop' graphic programming language that is supplied with the particular type of FPGA computer reported in this paper. Simple examples in structural dynamics and statics illustrate the solution approach used. The FPGA system also allows linear scalability in computing capability. As the problem grows, the number of FPGA chips can be increased with no loss of computing efficiency due to data flow or algorithmic latency that occurs when a single problem is distributed among many conventional processors that operate in parallel. This initial assessment finds the FPGA hardware and software to be in their infancy in regard to the user conveniences; however, they have enormous potential for shrinking the elapsed time of structural analysis solutions if programmed with algorithms that exhibit inherent parallelism and linear scalability. This potential warrants further development of FPGA-tailored algorithms for structural analysis.

Singleterry, Robert C., Jr.↗
NASA NTRS1985

Supercomputing on massively parallel bit-serial architectures

Research on the Goodyear Massively Parallel Processor (MPP) suggests that high-level parallel languages are practical and can be designed with powerful new semantics that allow algorithms to be efficiently mapped to the real machines. For the MPP these semantics include parallel/associative array selection for both dense and sparse matrices, variable precision arithmetic to trade accuracy for speed, micro-pipelined train broadcast, and conditional branching at the processing element (PE) control unit level. The preliminary design of a FORTRAN-like parallel language for the MPP has been completed and is being used to write programs to perform sparse matrix array selection, min/max search, matrix multiplication, Gaussian elimination on single bit arrays and other generic algorithms. A description is given of the MPP design. Features of the system and its operation are illustrated in the form of charts and diagrams.

Iobst, Ken↗
NASA NTRS1995

Design tool for multiprocessor scheduling and evaluation of iterative dataflow algorithms

A graph-theoretic design process and software tool is defined for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. Graph-search algorithms and analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool applies the design process to a given problem and includes performance optimization through the inclusion of additional precedence constraints among the schedulable tasks.

Jones, Robert L., III↗