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At least 793 records · Page 44

Adaptive Online Multivariate Signal Extraction With Locally Weighted Robust Polynomial Regression

High-frequency, multivariate data collected in real-time and used to control or make decisions regarding a process’ operation often contain some noise and outliers. Thus, a method to extract the signal is needed in order to reduce the number and magnitude of control-based adjustments that are implemented. Such a method must be (i) online, depending only on past and current observations; (ii) fast, producing a smooth value more quickly than the measurement frequency; (iii) robust, ignoring brief bursts of erroneously measured values; (iv) multivariate, ignoring observations that are jointly unusual; (v) adaptive, adjusting to periods of rapid fluctuation in the signal versus periods of stability; and (vi) purely data-driven, not incorporating any information about the process from which the data are collected. Most existing methods are only able to address a subset of these six features. Furthermore, we also require the method to be nonlinear, providing a local nonlinear estimate of the signal. In this work, we propose a novel, real-time signal extraction method based on a local, robust polynomial fit. We demonstrate the performance of our method compared to a state-of-the-art competitor through simulation. For illustration, the methodology is applied to data collected from a reverse osmosis water treatment process.

97 MATHEMATICS AND COMPUTING↗

On the Possibility of Ill-Conditioned Covariance Matrices in the First-Order Two-Step Estimator

The first-order two-step nonlinear estimator, when applied to a problem of orbital navigation, is found to occasionally produce first step covariance matrices with very low eigenvalues at certain trajectory points. This anomaly is the result of the linear approximation to the first step covariance propagation. The study of this anomaly begins with expressing the propagation of the first and second step covariance matrices in terms of a single matrix. This matrix is shown to have a rank equal to the difference between the number of first step states and the number of second step states. Furthermore, under some simplifying assumptions, it is found that the basis of the column space of this matrix remains fixed once the filter has removed the large initial state error. A test matrix containing the basis of this column space and the partial derivative matrix relating first and second step states is derived. This square test matrix, which has dimensions equal to the number of first step states, numerically drops rank at the same locations that the first step covariance does. It is formulated in terms of a set of constant vectors (the basis) and a matrix which can be computed from a reference trajectory (the partial derivative matrix). A simple example problem involving dynamics which are described by two states and a range measurement illustrate the cause of this anomaly and the application of the aforementioned numerical test in more detail.

Garrison, James L.↗

Residual mode filters and adaptive control in large space structures

One of the most difficult problems in controlling large systems and structures is compensating for the destructive interaction which can occur between the reduced-order model (ROM) of the plant, which is used by the controller, and the unmodeled dynamics of the plant, often called the residual modes. The problem is more significant in the case of large space structures because their naturally light damping and high performance requirements lead to more frequent, destructive residual mode interaction (RMI). Using the design/compensation technique of residual mode filters (RMF's), effective compensation of RMI can be accomplished in a straightforward manner when using linear controllers. The use of RMF's has been shown to be effective for a variety of large structures, including a space-based laser and infinite dimensional systems. However, the dynamics of space structures is often uncertain and may even change over time due to on-orbit erosion from space debris and corrosive chemicals in the upper atmosphere. In this case, adaptive control can be extremely beneficial in meeting the performance requirements of the structure. Adaptive control for large structures is also based on ROM's and so destructive RMI may occur. Unfortunately, adaptive control is inherently nonlinear, and therefore the known results of RMF's cannot be applied. The purpose is to present the results of new research showing the effects of RMI when using adaptive control and the work which will hopefully lead to RMF compensation of this problem.

Davidson, Roger A.↗

NASA Tech Briefs, September 2012

Topics covered include: Beat-to-Beat Blood Pressure Monitor; Measurement Techniques for Clock Jitter; Lightweight, Miniature Inertial Measurement System; Optical Density Analysis of X-Rays Utilizing Calibration Tooling to Estimate Thickness of Parts; Fuel Cell/Electrochemical Cell Voltage Monitor; Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor; Measuring Air Leaks into the Vacuum Space of Large Liquid Hydrogen Tanks; Antenna Calibration and Measurement Equipment; Glass Solder Approach for Robust, Low-Loss, Fiber-to-Waveguide Coupling; Lightweight Metal Matrix Composite Segmented for Manufacturing High-Precision Mirrors; Plasma Treatment to Remove Carbon from Indium UV Filters; Telerobotics Workstation (TRWS) for Deep Space Habitats; Single-Pole Double-Throw MMIC Switches for a Microwave Radiometer; On Shaft Data Acquisition System (OSDAS); ASIC Readout Circuit Architecture for Large Geiger Photodiode Arrays; Flexible Architecture for FPGAs in Embedded Systems; Polyurea-Based Aerogel Monoliths and Composites; Resin-Impregnated Carbon Ablator: A New Ablative Material for Hyperbolic Entry Speeds; Self-Cleaning Particulate Prefilter Media; Modular, Rapid Propellant Loading System/Cryogenic Testbed; Compact, Low-Force, Low-Noise Linear Actuator; Loop Heat Pipe with Thermal Control Valve as a Variable Thermal Link; Process for Measuring Over-Center Distances; Hands-Free Transcranial Color Doppler Probe; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; PMA-Linked Fluorescence for Rapid Detection of Viable Bacterial Endospores; Portable Intravenous Fluid Production Device for Ground Use; Adaptation of a Filter Assembly to Assess Microbial Bioburden of Pressurant Within a Propulsion System; Multiplexed Force and Deflection Sensing Shell Membranes for Robotic Manipulators; Whispering Gallery Mode Optomechanical Resonator; Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles; Self-Sealing Wet Chemistry Cell for Field Analysis; General MACOS Interface for Modeling and Analysis for Controlled Optical Systems; Mars Technology Rover with Arm-Mounted Percussive Coring Tool, Microimager, and Sample-Handling Encapsulation Containerization Subsystem; Fault-Tolerant, Real-Time, Multi-Core Computer System; Water Detection Based on Object Reflections; SATPLOT for Analysis of SECCHI Heliospheric Imager Data; Plug-in Plan Tool v3.0.3.1; Frequency Correction for MIRO Chirp Transformation Spectroscopy Spectrum; Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images; Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications; Low-Cost Telemetry System for Small/Micro Satellites; Operator Interface and Control Software for the Reconfigurable Surface System Tri-ATHLETE; and Algorithms for Determining Physical Responses of Structures Under Load.

Source record↗

Pseudodiagonalization Method for Accelerating Nonlinear Subspace Diagonalization in Density Functional Theory

In density functional theory, each self-consistent field (SCF) nonlinear step updates the discretized Kohn-Sham orbitals by solving a linear eigenvalue problem. The concept of pseudodiagonalization is to solve this linear eigenvalue problem approximately, and specifically utilizing a method involving a small number of Jacobi rotations that takes advantage of the good initial guess to the solution given by the approximation to the orbitals from the previous SCF iteration. The approximate solution to the linear eigenvalue problem can be very rapid, particularly for those steps near SCF convergence. Here, we adapt pseudodiagonalization to finite-temperature and metallic systems, where partially-occupied orbitals must be individually resolved with some accuracy. We apply pseudodiagonalization to the subspace eigenvalue problem that arises in Chebyshev-filtered subspace iteration. In tests on metallic and other systems for a range of temperatures, we show that pseudodiagonalization achieves similar rates of SCF convergence to exact diagonalization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative Analysis of Thrombin Calibration Algorithms and Correction for Thrombin-α2macroglobulin Activity

Background: The thrombin generation (TG) test is useful for characterizing global hemostasis potential, but fluorescence substrate artifacts, such as thrombin-α2macroglobulin (T-α2MG) signal, inner filter effect (IFE), substrate consumption, and calibration algorithms have been suggested as sources of intra- and inter-laboratory variance, which may limit its clinical utility. Methods: Effects of internal vs. external normalization, IFE and T-α2MG on TG curves in normal plasma supplemented with coagulation factors, thrombomodulin, and tissue factor were studied using the Calibrated Automated Thrombinography (CAT; Diagnostica Stago, Parsippany, NJ, USA) and in-house software. Results: The various calibration methods demonstrated no significant difference in producing TG curves, nor increased the robustness of the TG assay. Several TG parameters, including thrombin peak height (TPH), produced from internal linear calibration did not differ significantly from uncalibrated TG parameters. Further, TPH values from internal linear and nonlinear calibration with or without T-α2MG correction correlated well with TPH from external calibration. Higher coefficients of variation (CVs) for TPH values were observed in both platelet-free and platelet-rich plasma with added thrombomodulin. Conclusions: Our work suggests minimal differences between distinct computational approaches toward calibrating and correcting fluorescence signals into TG levels, with most samples returning similar or equivalent TPH results.

59 BASIC BIOLOGICAL SCIENCES↗

Methods of sequential estimation for determining initial data in numerical weather prediction

Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the initial time must therefore be supplemented by data available prior to the initial time, a problem known as meteorological data assimilation. A further complication in NWP is that solutions of the governing equations evolve on two different time scales, a fast one and a slow one, whereas fast scale motions in the atmosphere are not reliably observed. This leads to the so called initialization problem: initial values must be constrained to result in a slowly evolving forecast. The theory of estimation of stochastic dynamic systems provides a natural approach to such problems. For linear stochastic dynamic models, the Kalman-Bucy (KB) sequential filter is the optimal data assimilation method, for linear models, the optimal combined data assimilation-initialization method is a modified version of the KB filter.

Cohn, S. E.↗

Diabatic dynamic initialization

A generalized dynamical adjustment procedure was applied to a diabatic model to produce balanced initial conditions. Namely, backward adiabatic model integration is followed by forward diabatic model integration, with a high frequency (low pass) filter in the form of the Euler-backward time differencing scheme being applied throughout the whole integration. As a result of the application of such a diabatic dynamic initialization procedure within the Goddard Laboratory for Atmospheres (GLA) 4-D data assimilation system, the following properties of forecasts from initialized fields are achieved right from the beginning of the usual forecast integration: (1) the forecast tendencies (and fields) are free of any noise due to imbalance in initial conditions; (2) the shocks related to an initial imbalance between model physics and dynamics, and especially the substantial initial imbalance of precipitation and evaporation fields, or the initial spin-up effect, are practically removed. Diabatic dynamic initialization has been compared with implicit nonlinear normal mode initialization, and found to be superior in removing the initial spin-up effect, and also in improving the tropical structure. The diabatic dynamic initialization procedure was successfully tested for the GLA system with the use of all conventional data and the GLA satellite data retrievals. It allows a smooth data insertion without any shocks or imbalances, which is highly desirable for efficient functioning of 4-D data assimilation systems. The developed initialization procedure is computationally efficient and in principle easily applicable to different forecast models.

Fox-Rabinovitz, Michael S.↗

Numerical methods for the weakly compressible Generalized Langevin Model in Eulerian reference frame

A well established approach for the computation of turbulent flow without resolving all turbulent flow scales is to solve a filtered or averaged set of equations, and to model non-resolved scales by closures derived from transported probability density functions (PDF) for velocity fluctuations. Effective numerical methods for PDF transport employ the equivalence between the Fokker–Planck equation for the PDF and a Generalized Langevin Model (GLM), and compute the PDF by transporting a set of sampling particles by GLM (Pope (1985) [1]). The natural representation of GLM is a system of stochastic differential equations in a Lagrangian reference frame, typically solved by particle methods. A representation in a Eulerian reference frame, however, has the potential to significantly reduce computational effort and to allow for the seamless integration into a Eulerian-frame numerical flow solver. GLM in a Eulerian frame (GLMEF) formally corresponds to the nonlinear fluctuating hydrodynamic equations derived by Nakamura and Yoshimori (2009) [12]. Unlike the more common Landau–Lifshitz Navier–Stokes (LLNS) equations these equations are derived from the underdamped Langevin equation and are not based on a local equilibrium assumption. Similarly to LLNS equations the numerical solution of GLMEF requires special considerations. In this paper we investigate different numerical approaches to solving GLMEF with respect to the correct representation of stochastic properties of the solution. We find that a discretely conservative staggered finite-difference scheme, adapted from a scheme originally proposed for turbulent incompressible flow, in conjunction with a strongly stable (for non-stochastic PDE) Runge–Kutta method performs better for GLMEF than schemes adopted from those proposed previously for the LLNS. We show that equilibrium stochastic fluctuations are correctly reproduced.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Specular reflectance of optical-black coatings in the far infrared

Far-infrared specular reflectance spectra of seven optically black coatings near normal incidence are presented. Seven photometric spectra were obtained using eleven bandpass transmission filters in the wavelength range between 12 and 500 microns, and three interferometric spectra were obtained for corroboration. Data on the construction, thickness, and rms surface roughness of the coatings are also presented. The chemical composition of three coatings can be distinguished from that of the others by a strong absorption feature between 20 and 40 microns, which can be largely attributed to amorphous silicate material. At 100 microns, the most and least reflective coatings differ by nearly 3 orders of magnitude. Inverse relationships observed between the spectra and the roughness and thickness of the coatings led to development of a reflecting-layer model for the measured reflectance. The model successfully describes the spectra at wavelengths outside the silicate absorption, and optical constants are deduced from a nonlinear least squares fit to the data. Parametric errors are estimated by chi-square analysis, and sensitivity tests are performed to determine which parameters control reflectance in different spectral regions.

Smith, S. M.↗

The design of a turboshaft speed governor using modern control techniques

The objectives of this program were: to verify the model of off schedule compressor variable geometry in the T700 turboshaft engine nonlinear model; to evaluate the use of the pseudo-random binary noise (PRBN) technique for obtaining engine frequency response data; and to design a high performance power turbine speed governor using modern control methods. Reduction of T700 engine test data generated at NASA-Lewis indicated that the off schedule variable geometry effects were accurate as modeled. Analysis also showed that the PRBN technique combined with the maximum likelihood model identification method produced a Bode frequency response that was as accurate as the response obtained from standard sinewave testing methods. The frequency response verified the accuracy of linear models consisting of engine partial derivatives and used for design. A power turbine governor was designed using the Linear Quadratic Regulator (LQR) method of full state feedback control. A Kalman filter observer was used to estimate helicopter main rotor blade velocity. Compared to the baseline T700 power turbine speed governor, the LQR governor reduced droop up to 25 percent for a 490 shaft horsepower transient in 0.1 sec simulating a wind gust, and up to 85 percent for a 700 shaft horsepower transient in 0.5 sec simulating a large collective pitch angle transient.

Delosreyes, G.↗

Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors

Purpose: In using flat panel detectors (FPD) for cone beam computed tomography (CBCT), pixel gain variations may lead to structured nonuniformities in projections and ring artifacts in CBCT images. Such gain variations can be caused by change in detector entrance exposure levels or beam hardening, and they are not accounted by conventional flat field correction methods. In this work, the authors presented a method to identify isolated pixel clusters that exhibit gain variations and proposed a pixel gain correction (PGC) method to suppress both beam hardening and exposure level dependent gain variations. Methods: To modulate both beam spectrum and entrance exposure, flood field FPD projections were acquired using beam filters with varying thicknesses. “Ideal” pixel values were estimated by performing polynomial fits in both raw and flat field corrected projections. Residuals were calculated by taking the difference between measured and ideal pixel values to identify clustered image and FPD artifacts in flat field corrected and raw images, respectively. To correct clustered image artifacts, the ratio of ideal to measured pixel values in filtered images were utilized as pixel-specific gain correction factors, referred as PGC method, and they were tabulated as a function of pixel value in a look-up table. Results: 0.035% of detector pixels lead to clustered image artifacts in flat field corrected projections, where 80% of these pixels were traced back and linked to artifacts in the FPD. The performance of PGC method was tested in variety of imaging conditions and phantoms. The PGC method reduced clustered image artifacts and fixed pattern noise in projections, and ring artifacts in CBCT images. Conclusions: Clustered projection image artifacts that lead to ring artifacts in CBCT can be better identified with our artifact detection approach. When compared to the conventional flat field correction method, the proposed PGC method enables characterization of nonlinear pixel gain variations as a function of change in x-ray spectrum and intensity. Hence, it can better suppress image artifacts due to beam hardening as well as artifacts that arise from detector entrance exposure variation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Application of the Hilbert-Huang Transform to Financial Data

A paper discusses the application of the Hilbert-Huang transform (HHT) method to time-series financial-market data. The method was described, variously without and with the HHT name, in several prior NASA Tech Briefs articles and supporting documents. To recapitulate: The method is especially suitable for analyzing time-series data that represent nonstationary and nonlinear phenomena including physical phenomena and, in the present case, financial-market processes. The method involves the empirical mode decomposition (EMD), in which a complicated signal is decomposed into a finite number of functions, called "intrinsic mode functions" (IMFs), that admit well-behaved Hilbert transforms. The HHT consists of the combination of EMD and Hilbert spectral analysis. The local energies and the instantaneous frequencies derived from the IMFs through Hilbert transforms can be used to construct an energy-frequency-time distribution, denoted a Hilbert spectrum. The instant paper begins with a discussion of prior approaches to quantification of market volatility, summarizes the HHT method, then describes the application of the method in performing time-frequency analysis of mortgage-market data from the years 1972 through 2000. Filtering by use of the EMD is shown to be useful for quantifying market volatility.

Huang, Norden↗

A memory-distributed quasi-Newton solver for nonlinear programming problems with a small number of general constraints

We approach the problem of parallelizing state-of-the-art nonlinear programming optimization algorithms.Specifically, we focus on parallelizing quasi-Newton interior-point methods that use limited-memory secant Hessian approximations. Such interior-point methods are known to have better convergence properties and to be more effective on large-scale problems than gradient-based and derivative-free optimization algorithms. We target nonlinear and potentially nonconvex optimization problems with an arbitrary number of bound constraints and a small number of general equality and inequality constraints on the optimization variables. These problems occur for example in the form of optimal control, optimal design, and inverse problems governed by ordinary or partial differential equations, whenever they are expressed in a “reduced-space” optimization approach. We introduce and analyze the time and space complexity of a decomposition method for solving the quasi-Newton linear systems that leverages the fact that the quasi-Newton Hessian matrix has a small number of dense blocks that border a low-rank update of a diagonal matrix. This enables an efficient parallelization on memory-distributed computers of the iterations of the optimization algorithm, a state-of-the-art filter line-search interior-point algorithm by Wächter et. al. We illustrate the efficiency of the proposed method by solving structural topology optimization problems on up to 4608 cores on a parallel machine.

97 MATHEMATICS AND COMPUTING↗

Streak camera based SLR receiver for two color atmospheric measurements

To realize accurate two-color differential measurements, an image digitizing system with variable spatial resolution was designed, built, and integrated to a photon-counting picosecond streak camera, yielding a temporal scan resolution better than 300 femtosecond/pixel. The streak camera is configured to operate with 3 spatial channels; two of these support green (532 nm) and uv (355 nm) while the third accommodates reference pulses (764 nm) for real-time calibration. Critical parameters affecting differential timing accuracy such as pulse width and shape, number of received photons, streak camera/imaging system nonlinearities, dynamic range, and noise characteristics were investigated to optimize the system for accurate differential delay measurements. The streak camera output image consists of three image fields, each field is 1024 pixels along the time axis and 16 pixels across the spatial axis. Each of the image fields may be independently positioned across the spatial axis. Two of the image fields are used for the two wavelengths used in the experiment; the third window measures the temporal separation of a pair of diode laser pulses which verify the streak camera sweep speed for each data frame. The sum of the 16 pixel intensities across each of the 1024 temporal positions for the three data windows is used to extract the three waveforms. The waveform data is processed using an iterative three-point running average filter (10 to 30 iterations are used) to remove high-frequency structure. The pulse pair separations are determined using the half-max and centroid type analysis. Rigorous experimental verification has demonstrated that this simplified process provides the best measurement accuracy. To calibrate the receiver system sweep, two laser pulses with precisely known temporal separation are scanned along the full length of the sweep axis. The experimental measurements are then modeled using polynomial regression to obtain a best fit to the data. Data aggregation using normal point approach has provided accurate data fitting techniques and is found to be much more convenient than using the full rate single shot data. The systematic errors from this model have been found to be less than 3 ps for normal points.

Varghese, Thomas K.↗

Electrically interfaced Brillouin-active waveguide for microwave photonic measurements

New strategies for converting signals between optical and microwave domains could play a pivotal role in advancing both classical and quantum technologies. Traditional approaches to optical-to-microwave transduction typically perturb or destroy the information encoded on intensity of the light field, eliminating the possibility for further processing or distribution of these signals. In this paper, we introduce an optical-to-microwave conversion method that allows for both detection and spectral analysis of microwave photonic signals without degradation of their information content. This functionality is demonstrated using an optomechanical waveguide integrated with a piezoelectric transducer. Efficient electromechanical and optomechanical coupling within this system permits bidirectional optical-to-microwave conversion with a quantum efficiency of up to -54.16 dB. Leveraging the preservation of the optical field envelope in intramodal Brillouin scattering, we demonstrate a multi-channel microwave photonic filter by transmitting an optical signal through a series of electro-optomechanical waveguide segments, each with distinct resonance frequencies. Such electro-optomechanical systems could offer flexible strategies for remote sensing, channelization, and spectrum analysis in microwave photonics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Statistical analysis of SSME system data

A statistical methodology to enhance the Space Shuttle Main Engine (SSME) performance prediction accuracy is proposed. This methodology was to be used in conjunction with existing SSME performance prediction computer codes to improve parameter prediction accuracy and to quantify that accuracy. However, after a review of related literature, researchers concluded that the proposed problem required a coverage of areas such as linear and nonlinear system theory, measurement theory, statistics, and stochastic estimation. Since state space theory is the foundation for a more complete study of each of the before mentioned areas, these researchers chose to refocus emphasis to cover the more specialized topic of state vector estimation procedures. State vector estimation was also selected because of current and future concerns by NASA for SSME performance evaluation; i.e., there is a current interest in an improved evaluation procedure for actual SSME post flight performance as well as for post static test performance of a single SSME. A current investigation of analytical methods may be used to improve test stand failure detection. This paper considers the issue of post flight/test state variable reconstruction through the application of observations made on the output of the Space Shuttle propulsion system. Rogers used the Kalman filtering procedure to reconstruct the state variables of the Space Shuttle propulsion system. An objective of this paper is to give the general setup of the Kalman filter and its connection to linear regression. A second objective is to examine the reconstruction methodology for application to the reconstruction of the state vector of a single Space Shuttle Main Engine (SSME) by using static test firing data.

Temple, Enoch C.↗

Performance analysis of a fault inferring nonlinear detection system algorithm with integrated avionics flight data

This paper presents the performance analysis results of a fault inferring nonlinear detection system (FINDS) using integrated avionics sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. First, an overview of the FINDS algorithm structure is given. Then, aircraft state estimate time histories and statistics for the flight data sensors are discussed. This is followed by an explanation of modifications made to the detection and decision functions in FINDS to improve false alarm and failure detection performance. Next, the failure detection and false alarm performance of the FINDS algorithm are analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minutes of flight data. Results indicate that the detection speed, failure level estimation, and false alarm performance show a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed is faster for filter measurement sensors such as MLS than for filter input sensors such as flight control accelerometers. Finally, the progress in modifications of the FINDS algorithm design to accommodate flight computer constraints is discussed.

Caglayan, A. K.↗