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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 253 records · Page 14

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NASA NTRS1991

Neuromorphic learning of continuous-valued mappings from noise-corrupted data

The effect of noise on the learning performance of the backpropagation algorithm is analyzed. A selective sampling of the training set is proposed to maximize the learning of control laws by backpropagation, when the data have been corrupted by noise. The training scheme is applied to the nonlinear control of a cart-pole system in the presence of noise. The neural computation provides the neurocontroller with good noise-filtering properties. In the presence of plant noise, the neurocontroller is found to be more stable than the teacher. A novel perspective on the application of neural network technology to control engineering is presented.

Troudet, T.↗

NASA NTRS1992

Microwave radiometry for monitoring the diverse cloudiness regimes on Earth: A review

Recent work concerning the use of microwave radiometers in space to provide views of the water content of clouds is reported. Recently, theoretical algorithms were refined and the sampling by microwave radiometers for polar orbiting satellite became more commensurate in resolution and coverage with the scale of the meteorological phenomena. Parameters available from the Special Sensor Microwave/Imager (SSM/I) include total integrated water vapor (kg/sq m), integrated cloud liquid water (kg/sq m), rain rate (mm/hr), and an index for the presence and concentration of large ice particles; this so called scattering index can also be converted to a rain rate, although conversion is still rather uncertain. The hydrologic aspects of climatically important cloud systems on the Earth such as subtropical stratus decks, tropical convection, and midlatitude and polar cyclone can thus be monitored with the SSM/I parameters. The diagnostic as well as prognostic potential of these satellite derived water content properties of cloud systems are also discussed.

Katsaros, Kristina B.↗

NASA NTRS1993

Symmetric Galerkin boundary formulations employing curved elements

Accounts of the symmetric Galerkin approach to boundary element analysis (BEA) have recently been published. This paper attempts to add to the understanding of this method by addressing a series of fundamental issues associated with its potential computational efficiency. A new symmetric Galerkin theoretical formulation for both the (harmonic) heat conduction and the (biharmonic) elasticity problem that employs regularized singular and hypersingular boundary integral equations (BIEs) is presented. The novel use of regularized BIEs in the Galerkin context is shown to allow straightforward incorporation of curved, isoparametric elements. A symmetric reusable intrinsic sample point (RISP) numerical integration algorithm is shown to produce a Galerkin (i.e., double) integration strategy that is competitive with its counterpart (i.e., singular) integration procedure in the collocation BEA approach when the time saved in the symmetric equation solution phase is also taken into account. This new formulation is shown to be capable of employing hypersingular BIEs while obviating the requirement of C 1 continuity, a fact that allows the employment of the popular continuous element technology. The behavior of the symmetric Galerkin BEA method with regard to both direct and iterative equation solution operations is also addressed. A series of example problems are presented to quantify the performance of this symmetric approach, relative to the more conventional unsymmetric BEA, in terms of both accuracy and efficiency. It is concluded that appropriate implementations of the symmetric Galerkin approach to BEA indeed have the potential to be competitive with, if not superior to, collocation-based BEA, for large-scale problems.

Kane, J. H.↗

NASA NTRS1993

Microstrip Ring Resonator for Soil Moisture Measurements

Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (epsilon(sub soil)) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of epsilon(sub soil). In this paper a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of epsilon(sub soil) are determined from the changes in the resonant frequency and the quality factor of the resonator respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasi-static formulation in conjunction with experimental data obtained from reference dielectric samples. Also a simple inversion algorithm for epsilon(sub soil) = epsilon'(sub r) + j(epsilon"(sub r)) based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

Sarabandi, Kamal↗

NASA NTRS1998

SPARCLE: Validation of Observing System Simulations (SPace Readiness Coherent Lidar Experiment)

NASA recently approved a mission to fly a Doppler Wind Lidar (DWL) on a U.S. Space Shuttle. SPARCLE, managed by Marshall Space Flight Center in Huntsville, AL, is targeted for launch in March 2001. This mission is viewed as a necessary demonstration of a solid state (2 micron) lidar using coherent detection before committing resources to a 3-5 year research or operational mission. While, to many, this shuttle mission is seen as the first step in a series leading to a fully operational wind observing system, to others, it is a chance to validate predictions of performance based upon theoretical models, analyses of airborne and ground-based data, and sophisticated observing system simulation experiments. This paper will be presented in two parts: first a brief overview of the SPARCLE mission and second, a summary of current performance predictions and key contributions from ground- based and airborne DWL research. The SPARCLE instrument is a 100 mJ, 6 Hz, diode-pumped 2-micron laser with a .25 m telescope using heterodyne mixing in a fiber and an InGaAs detector. A 25 cm silicon wedge scanner will be used in step-stare modes with dwells ranging from 60 seconds to .5 seconds. Pointing knowledge is achieved with a dedicated GPS/INS mounted close to the lidar. NASA's Hitchhiker program is providing the instrument enclosures (2 cans) and mission logistics support. An on-board data system is sized to record 150 Gbytes of raw signal from a two 400 MHZ A/D converters. On-board signal processing will be used to control the frequency of the Local Oscillator. SPARCLE is predicted to have a single shot backscatter sensitivity near 1x10(exp -6) m-1 sr-1, To achieve higher sensitivity, shot accumulation will be employed. Ground-based, 2 micron DWLs have been used to assess the benefits of shot accumulation (approximately SQRT for SNR). Airborne programs like MACAWS have provided good datasets for evaluating various sampling strategies and signal processing algorithms. Using these real data to calibrate our simulation models, we can describe when and how well SPARCLE is expected to preform. Outputs from these performance models will be presented.

Emmitt, G. D.↗

NASA NTRS2001

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

Blonksi, Slawomir↗

NASA NTRS2011

Jitter Correction

Jitter_Correct.m is a MATLAB function that automatically measures and corrects inter-frame jitter in an image sequence to a user-specified precision. In addition, the algorithm dynamically adjusts the image sample size to increase the accuracy of the measurement. The Jitter_Correct.m function takes an image sequence with unknown frame-to-frame jitter and computes the translations of each frame (column and row, in pixels) relative to a chosen reference frame with sub-pixel accuracy. The translations are measured using a Cross Correlation Fourier transformation method in which the relative phase of the two transformed images is fit to a plane. The measured translations are then used to correct the inter-frame jitter of the image sequence. The function also dynamically expands the image sample size over which the cross-correlation is measured to increase the accuracy of the measurement. This increases the robustness of the measurement to variable magnitudes of inter-frame jitter

Waegell, Mordecai J.↗

NASA NTRS2012

NASA Tech Briefs, June 2012

Topics covered include: iGlobe Interactive Visualization and Analysis of Spatial Data; Broad-Bandwidth FPGA-Based Digital Polyphase Spectrometer; Small Aircraft Data Distribution System; Earth Science Datacasting v2.0; Algorithm for Compressing Time-Series Data; Onboard Science and Applications Algorithm for Hyperspectral Data Reduction; Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data; Security Data Warehouse Application; Integrated Laser Characterization, Data Acquisition, and Command and Control Test System; Radiation-Hard SpaceWire/Gigabit Ethernet-Compatible Transponder; Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager; High-Voltage, Low-Power BNC Feedthrough Terminator; SpaceCube Mini; Dichroic Filter for Separating W-Band and Ka-Band; Active Mirror Predictive and Requirement Verification Software (AMP-ReVS); Navigation/Prop Software Suite; Personal Computer Transport Analysis Program; Pressure Ratio to Thermal Environments; Probabilistic Fatigue Damage Program (FATIG); ASCENT Program; JPL Genesis and Rapid Intensification Processes (GRIP) Portal; Data::Downloader; Fault Tolerance Middleware for a Multi-Core System; DspaceOgreTerrain 3D Terrain Visualization Tool; Trick Simulation Environment 07; Geometric Reasoning for Automated Planning; Water Detection Based on Color Variation; Single-Layer, All-Metal Patch Antenna Element with Wide Bandwidth; Scanning Laser Infrared Molecular Spectrometer (SLIMS); Next-Generation Microshutter Arrays for Large-Format Imaging and Spectroscopy; Detection of Carbon Monoxide Using Polymer-Composite Films with a Porphyrin-Functionalized Polypyrrole; Enhanced-Adhesion Multiwalled Carbon Nanotubes on Titanium Substrates for Stray Light Control; Three-Dimensional Porous Particles Composed of Curved, Two-Dimensional, Nano-Sized Layers for Li-Ion Batteries 23 Ultra-Lightweight; and Ultra-Lightweight Nanocomposite Foams and Sandwich Structures for Space Structure Applications.

Source record↗

NASA NTRS2018

Recent Advances in SMAP RFI Processing

The measurements made by the Soil Moisture Active/Passive (SMAP) mission are affected by the presence of Radio Frequency Interference (RFI) in the protected 1400-1427 MHz band. In SMAP data processing, the main protection against RFI is a sophisticated RFI detection algorithm which flags sub-samples in time and frequency that are contaminated by RFI and removes them before estimating the brightness temperature. This contribution presents two additional approaches that have been developed to address the RFI concern in SMAP. The first consists in locating sources of RFI; once located, it becomes possible to report RFI sources to spectrum management authorities, which can lead to less RFI being experienced by SMAP in the future. The second is a new RFI detection method that is based on detecting outliers in the spatial distribution of measured antenna temperatures.

Radio Frequency Interference↗

NASA NTRS2021

Single-Turnover Variable Chlorophyll Fluorescence as a Tool for Assessing Phytoplankton Photosynthesis and Primary Productivity: Opportunities, Caveats and Recommendations

Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms.

variable chlorophyll fluorescence↗

NASA NTRS1987

Fast and stable recursive algorithms for continuous-time and discrete-time model conversions

Based on the Newton-Raphson method, this paper presents recursive algorithms that are rapidly convergent and more stable for modeling the equivalent continuous-time (discrete-time) model from the available discrete-time (continuous-time) model for a fixed sampling period. The newly developed recursive algorithms relax the constraints imposed upon the existing model conversion algorithms, and, thus, enhance the applications of microprocessors and associated microelectronics to digital control systems. A practical example is presented to demonstrate the effectiveness of the proposed procedures.

Shieh, L. S.↗

NASA NTRS2003

How Sample Completeness Affects Gamma-Ray Burst Classification

Unsupervised pattern-recognition algorithms support the existence of three gamma-ray burst classes: class 1 (long, large-fluence bursts of intermediate spectral hardness), class 2 (short, small-fluence, hard bursts), and class 3 (soft bursts of intermediate durations and fluences). The algorithms surprisingly assign larger membership to class 3 than to either of the other two classes. A known systematic bias has been previously used to explain the existence of class 3 in terms of class 1 ; this bias allows the fluences and durations of some bursts to be underestimated, as recently shown by Hakkila et al. We show that this bias primarily affects only the longest bursts and cannot explain the bulk of the class 3 properties. We resolve the question of class 3's existence by demonstrating how samples obtained using standard trigger mechanisms fail to preserve the duration characteristics of small-peak flux bursts. Sample incompleteness is thus primarily responsible for the existence of class 3. In order to avoid this incompleteness, we show how a new, dual-timescale peak flux can be defined in terms of peak flux and fluence. The dual-timescale peak flux preserves the duration distribution of faint bursts and correlates better with spectral hardness (and presumably redshift) than either peak flux or fluence. The techniques presented here are generic and have applicability to the studies of other transient events. The results also indicate that pattern recognition algorithms are sensitive to sample completeness; this can influence the study of large astronomical databases, such as those found in a virtual observatory.

Hakkila, Jon↗

NASA NTRS2012

Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery

The Iterative Transform Phase Diversity algorithm is designed to solve the problem of recovering the wavefront in the exit pupil of an optical system and the object being imaged. This algorithm builds upon the robust convergence capability of Variable Sampling Mapping (VSM), in combination with the known success of various deconvolution algorithms. VSM is an alternative method for enforcing the amplitude constraints of a Misell-Gerchberg-Saxton (MGS) algorithm. When provided the object and additional optical parameters, VSM can accurately recover the exit pupil wavefront. By combining VSM and deconvolution, one is able to simultaneously recover the wavefront and the object.

Smith, Jeffrey↗

NASA NTRS1990

Multirate sampled-data yaw-damper and modal suppression system design

A multirate control law synthesized algorithm based on an infinite-time quadratic cost function, was developed along with a method for analyzing the robustness of multirate systems. A generalized multirate sampled-data control law structure (GMCLS) was introduced. A new infinite-time-based parameter optimization multirate sampled-data control law synthesis method and solution algorithm were developed. A singular-value-based method for determining gain and phase margins for multirate systems was also developed. The finite-time-based parameter optimization multirate sampled-data control law synthesis algorithm originally intended to be applied to the aircraft problem was instead demonstrated by application to a simpler problem involving the control of the tip position of a two-link robot arm. The GMCLS, the infinite-time-based parameter optimization multirate control law synthesis method and solution algorithm, and the singular-value based method for determining gain and phase margins were all demonstrated by application to the aircraft control problem originally proposed for this project.

Berg, Martin C.↗

NASA NTRS1994

Software for Data Analysis with Graphical Models

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Buntine, Wray L.↗

DOE OSTI2025

Randomized Federated Learning Methods for Nonsmooth, Nonconvex, and Hierarchical Optimization (Final Technical Report)

This final technical report summarizes the outcomes of a DOE-funded project on federated scientific machine learning (FL) under nonsmooth, nonconvex, and hierarchical optimization settings. The project develops new mathematical models, algorithms, and theoretical guarantees for decentralized stochastic, bilevel, and minimax optimization problems arising in DOE mission-relevant applications. A unified framework of randomized and zeroth-order federated optimization methods is introduced, providing provable convergence, communication efficiency, and sample-complexity guarantees. The report documents algorithmic design, theoretical analysis, and empirical validation of the proposed federated learning methods. The project also contributes to workforce development through graduate training and dissemination of results via publications and seminars.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1976

DHARMA - Discriminant hyperplane abstracting residuals minimization algorithm for separating clusters with fuzzy boundaries

Learning of discriminant hyperplanes in imperfectly supervised or unsupervised training sample sets with unreliably labeled samples along the fuzzy joint boundaries between sample clusters is discussed, with the discriminant hyperplane designed to be a least-squares fit to the unreliably labeled data points. (Samples along the fuzzy boundary jump back and forth from one cluster to the other in recursive cluster stabilization and are considered unreliably labeled.) Minimization of the distances of these unreliably labeled samples from the hyperplanes does not sacrifice the ability to discriminate between classes represented by reliably labeled subsets of samples. An equivalent unconstrained linear inequality problem is formulated and algorithms for its solution are indicated. Landsat earth sensing data were used in confirming the validity and computational feasibility of the approach, which should be useful in deriving discriminant hyperplanes separating clusters with fuzzy boundaries, given supervised training sample sets with unreliably labeled boundary samples.

Dasarathy, B. V.↗

NASA NTRS1981

A modified adaptive delta modulator

This paper presents the results of a study in data compression of adaptive delta modulated video signals. The Song mode ADM is first investigated at a sampling rate of 16 Mbits/s and shown not to produce enough redundancy to warrant entropy encoding. A modified adaptive delta modulator algorithm is presented that operates at a sampling rate of 16 Mbits/s and does produce sufficient redundancy to yield a 40-50 percent data compression by using a simple code on 4 bit data blocks. Other techniques such as field interpolation and direct substitution are shown to increase the possible data compression further without noticeable degradation in the two input images used in this investigation. The effects of channel errors in the transmission of packet video over a computer network are considered. A leaky integrator is used to reduce the effects of channel errors in the data bits. It is shown that the effects of channel errors can be reduced by field interpolating those packets that can be shown to contain errors.

Barba, J.↗