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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

This project aims to implement the two-sigma lightning jump algorithm (LJA) developed using Lightning Mapping Arrays (LMAs), with GOES-16 Geostationary Lightning Mapper (GLM) flashes, evaluate its performance, and identify any needed adjustments to the algorithm to optimize operational skill. The GLM is projected to have lower detection efficiency (DE) (70-90 percent) than operational LMAs (95-99 percent). The reduced GLM DE coupled with the coarser spatial resolution of the GLM could have impacts on flash rates and trends that could affect the LJA in various ways. Deep dives are conducted on four separate cases. Three of four cases show LMAs seeing two to three times as many flashes as the GLM. Only fifteen of twenty five GLM jumps saw increases in radar intensity while fourteen of nineteen LMA jumps did. These results suggest a larger sample sized study must be conducted to determine how to implement the LJA with the GLM.

Curtis, Nathan↗
NASA NTRS1986

The Tukey algorithm for enhancing MST radar data

One of the most troublesome features in MSR (mesosphere stratosphere troposphere) velocity measurements is the determination of unwanted scatterer whose velocity is different from that of the surrounding atmosphere. Aircraft seen in the sidelobes of the antenna are the principal problem. Because coherent integration essentially eliminates echoes with line of sight velocities greater than 10 or 20 m/s, aircraft are seen only when their flight path is almost perpendicular to the line of sight. Then, they give large returns whose velocities may be positive or negative, and certainly different from that of the surrounding air. The glitches in the minute by minute velocity records are quite troublesome in that they may distort the statistics of the velocity. An objective way is therefore needed to remove sporadic points of this kind. For this purpose, the Tukey algorithm is appropriate and has some advantages over averaging. The Tukey algorithm, applied to a data array, uses for each data point the median of it and the two points surrounding it. If the three points form a monotonically increasing or decreasing sequence, the original point is copied with change. However, if the central point is remote from the other two, it is replaced by whichever of the two surrounding points is closest in value. The greatest effect of the Tukey algorithm is on data where the successive points are uncorrelated. Examples are given.

Bowhill, S. A.↗
NASA NTRS1972

Adaptive nonlinear optimization of the signal-to-noise ratio of an array subject to a constraint.

Investigation of a stochastic projected gradient algorithm which can be used to find a constrained optimum point for a concave or convex objective function subject to nonlinear constraints. When the constraint consists of only one linear equation, convergence to the constrained optimum value is proven, and bounds are obtained for the rate of convergence of the algorithm to the constrained optimum value. This algorithm is then applied to the nonlinear problem of automatically making an array of detectors form a beam in a desired direction in space when unknown interfering noise is present so as to maximize the signal-to-noise ratio subject to a constraint on the supergain ratio.

Winkler, L. P.↗
NASA NTRS2017

Dynamic Leading-Edge Stagnation Point Determination Utilizing an Array of Hot-Film Sensors with Unknown Calibration

During flight-testing of the National Aeronautics and Space Administration (NASA) Gulfstream III (G-III) airplane (Gulfstream Aerospace Corporation, Savannah, Georgia) SubsoniC Research Aircraft Testbed (SCRAT) between March 2013 and April 2015 it became evident that the sensor array used for stagnation point detection was not functioning as expected. The stagnation point detection system is a self calibrating hot-film array; the calibration was unknown and varied between flights, however, the channel with the lowest power consumption was expected to correspond with the point of least surface shear. While individual channels showed the expected behavior for the hot-film sensors, more often than not the lowest power consumption occurred at a single sensor (despite in-flight maneuvering) in the array located far from the expected stagnation point. An algorithm was developed to process the available system output and determine the stagnation point location. After multiple updates and refinements, the final algorithm was not sensitive to the failure of a single sensor in the array, but adjacent failures beneath the stagnation point crippled the algorithm.

aerodynamic characteristics↗
NASA NTRS1992

Laser power beams obtained by the dynamic selection of emitting elements in an array

A method for partially correcting the spatial coherence of an array of laser beams is discussed. The method trades far-field intensity for simplistic implementation and array lifetime extension, resulting in a quasi-coherent array with features of adaptive optics. An algorithm for implementing the method is described and feasible options for improvement are presented. A computer experiment used the algorithm and fast Fourier transforms to calculate typical far-field intensity distributions of such arrays. The far-field distributions illustrate beam power concentration, beam steering, and (indirectly) extended lifetime of the array.

Williams, M. D.↗
NASA NTRS1990

Reliable and Efficient Parallel Processing Algorithms and Architectures for Modern Signal Processing

Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.

Liu, Kuojuey Ray↗
NASA NTRS1992

An Analog Processor for Image Compression

This paper describes a novel analog Vector Array Processor (VAP) that was designed for use in real-time and ultra-low power image compression applications. This custom CMOS processor is based architectually on the Vector Quantization (VQ) algorithm in image coding, and the hardware implementation fully exploits the inherent parallelism built-in the VQ algorithm.

Vector Array Processor VAP analog processor image ↗
NASA NTRS1988

A multistage linear array assignment problem

The implementation of certain algorithms on parallel processing computing architectures can involve partitioning contiguous elements into a fixed number of groups, each of which is to be handled by a single processor. It is desired to find an assignment of elements to processors that minimizes the sum of the maximum workloads experienced at each stage. This problem can be viewed as a multi-objective network optimization problem. Polynomially-bounded algorithms are developed for the case of two stages, whereas the associated decision problem (for an arbitrary number of stages) is shown to be NP-complete. Heuristic procedures are therefore proposed and analyzed for the general problem. Computational experience with one of the exact problems, incorporating certain pruning rules, is presented with one of the exact problems. Empirical results also demonstrate that one of the heuristic procedures is especially effective in practice.

Nicol, David M.↗
NASA NTRS1994

FFT Computation with Systolic Arrays, A New Architecture

The use of the Cooley-Tukey algorithm for computing the l-d FFT lends itself to a particular matrix factorization which suggests direct implementation by linearly-connected systolic arrays. Here we present a new systolic architecture that embodies this algorithm. This implementation requires a smaller number of processors and a smaller number of memory cells than other recent implementations, as well as having all the advantages of systolic arrays. For the implementation of the decimation-in-frequency case, word-serial data input allows continuous real-time operation without the need of a serial-to-parallel conversion device. No control or data stream switching is necessary. Computer simulation of this architecture was done in the context of a 1024 point DFT with a fixed point processor, and CMOS processor implementation has started.

Boriakoff, Valentin↗
DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

On realizations of least-squares estimation and Kalman filtering by systolic arrays

Least-squares (LS) estimation is a basic operation in many signal processing problems. Given y = Ax + v, where A is a m x n coefficient matrix, y is a m x 1 observation vector, and v is a m x 1 zero mean white noise vector, a simple least-squares solution is finding the estimated vector x which minimizes the norm of /Ax-y/. It is well known that for an ill-conditioned matrix A, solving least-squares problems by orthogonal triangular (QR) decomposition and back substitution has robust numerical properties under finite word length effect since 2-norm is preserved. Many fast algorithms have been proposed and applied to systolic arrays. Gentleman-Kung (1981) first presented the trianglular systolic array for a basic Givens reduction. McWhirter (1983) used this array structure to find the least-squares estimation errors. Then by geometric approach, several different systolic array realizations of the recursive least-squares estimation algorithms of Lee et al (1981) were derived by Kalson-Yao (1985). Basic QR decomposition algorithms are considered in this paper and it is found that under a one-row time updating situation, the Householder transformation degenerates to a simple Givens reduction. Next, an improved least-squares estimation algorithm is derived by considering a modified version of fast Givens reduction. From this approach, the basic relationship between Givens reduction and Modified-Gram-Schmidt transformation can easily be understood. This improved algorithm also has simpler computational and inter-cell connection complexities while compared with other known least-squares algorithms and is more realistic for systolic array implementation.

Chen, M. J.↗
DOE OSTI2023

Machine learning results and code

Results for all the Four MLP-NN, RF, XGBR, and RF algorithms for each of geophysical array`s and machine learning python code is provided.

58 GEOSCIENCES↗
NASA NTRS1985

A cluster analysis method for identification of subpopulations of cells in flow cytometric list-mode arrays

A specialized program was developed for flow cytometric list-mode data using an heirarchical tree method for identifying and enumerating individual subpopulations, the method of principal components for a two-dimensional display of 6-parameter data array, and a standard sorting algorithm for characterizing subpopulations. The program was tested against a published data set subjected to cluster analysis and experimental data sets from controlled flow cytometry experiments using a Coulter Electronics EPICS V Cell Sorter. A version of the program in compiled BASIC is usable on a 16-bit microcomputer with the MS-DOS operating system. It is specialized for 6 parameters and up to 20,000 cells. Its two-dimensional display of Euclidean distances reveals clusters clearly, as does its 1-dimensional display. The identified subpopulations can, in suitable experiments, be related to functional subpopulations of cells.

Li, Z. K.↗
NASA NTRS1997

Determination of Aerosol Optical Depth and Land Surface Directional Reflectances Using Multiangle Imagery

Spectral aerosol optical depths, surface hemispherical-directional reflectance factors, and bihemispherical reflectances (albedos) are retrieved for an area of Glacier National Park using spectral, multiangle imagery obtained with the airborne advanced solid state array spectroradiometer (ASAS). The retrieval algorithms are described and are identical in principle to those being devised for use by the multiangle imaging spectroradiometer (MISR) which will fly on the EOS-AMI spacecraft in 1998. As part of its science mission, MISR will produce global coverage of both aerosol amounts an an surface reflection properties. The results in this paper represent the initial effort in applying the MISR algorithms to real data. These algorithms will undergo additional testing and validation as more multiangle data become available.

Martonchik, John V.↗
NASA NTRS2009

Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation

When setting out to model and/or simulate a complex mechanical or electrical system, a modeler is faced with a vast array of tools, software, equations, algorithms and techniques that may individually or in concert aid in the development of the model. Mature requirements and a well understood purpose for the model may considerably shrink the field of possible tools and algorithms that will suit the modeling solution. Is the model intended to be used in an offline fashion or in real-time? On what platform does it need to execute? How long will the model be allowed to run before it outputs the desired parameters? What resolution is desired? Do the parameters need to be qualitative or quantitative? Is it more important to capture the physics or the function of the system in the model? Does the model need to produce simulated data? All these questions and more will drive the selection of the appropriate tools and algorithms, but the modeler must be diligent to bear in mind the final application throughout the modeling process to ensure the model meets its requirements without needless iterations of the design. The purpose of this paper is to describe the considerations and techniques used in the process of creating a functional fault model of a liquid hydrogen (LH2) system that will be used in a real-time environment to automatically detect and isolate failures.

Ferrell, Bob↗
NASA NTRS2016

Correcting GOES-R Magnetometer Data for Stray Fields

Time-varying spacecraft magnetic fields or stray fields are a problem for magnetometer systems. While constant fields can be removed with zero offset calibration, stray fields are difficult to distinguish from ambient field variations. Putting two magnetometers on a long boom and solving for both the ambient and stray fields can be a good idea, but this gradiometer solution is even more susceptible to noise than a single magnetometer. Unless the stray fields are larger than the magnetometer noise, simply averaging the two measurements is a more accurate approach. If averaging is used, it may be worthwhile to explicitly estimate and remove stray fields. Models and estimation algorithms are provided for solar array, arcjet and reaction wheel fields.

Magnetometers↗
NASA NTRS1991

High resolution decoding of Multi-Anode Microchannel Array detectors

The Multi-Anode Microchannel Array (MAMA) is a photon counting detector which utilizes a photocathode for photon to electron conversion, a microchannel plate (MCP) for signal amplification and a proximity focused anode array for position sensitivity. The detector electronics decode the position of an event through coincidence discrimination. The decoding algorithm which associates a given event with the appropriate pixel is determined by the geometry of the array. A new algorithm incorporated into a CMOS Application Specific Integrated Circuit (ASIC) decoder which improves the pixel spatial resolution is described. The new algorithm does not degrade the detector throughput and does not require any modifications to the detector tube. The standard MAMA detector has a pixel size of 25 x 25 square microns, but with the new decoder circuit the pixel size is reduced to 12.5 x 12.5 square microns. We have built the first set of decode electronics utilizing the new ASIC chips and report here on the first imaging tests of this system.

Kasle, David B.↗
NASA NTRS1972

Gyro and accelerometer failure detection and identification in redundant sensor systems

Algorithms for failure detection and identification for redundant noncolinear arrays of single degree of freedom gyros and accelerometers are described. These algorithms are optimum in the sense that detection occurs as soon as it is no longer possible to account for the instrument outputs as the outputs of good instruments operating within their noise tolerances, and identification occurs as soon as it is true that only a particular instrument failure could account for the actual instrument outputs within the noise tolerance of good instruments. An estimation algorithm is described which minimizes the maximum possible estimation error magnitude for the given set of instrument outputs. Monte Carlo simulation results are presented for the application of the algorithms to an inertial reference unit consisting of six gyros and six accelerometers in two alternate configurations.

Potter, J. E.↗