The effect of non-linearities on optical correlation processing
Analytical method using series expansion to determine effect of nonlinearities on output of coherent optical correlator
CORRELATION FUNCTION↗
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Results for “Nonlinear processes”
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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Steepening of nonlinear waves in the solar wind.
Two shock-like structures (i.e., abrupt step-like increases in number density, bulk speed, and proton temperature) were found in the data from Mariner 5 at 0.98 AU on June 26 and at 0.85 AU on Aug. 29, 1967. The thickness of these 'structures' determined from the magnetic field data was more than 1000 proton Larmor radii. They were also observed by Explorer 33, 34, and 35 at 1 AU, where the thicknesses were much smaller than in the Mariner 5 data. It is suggested that these two structures were nonlinear magnetoacoustic waves that were in the processes of steepening. It is further suggested that shocks would be formed just beyond 1 AU. These structures were not associated with corotating streams, but they could be associated with impressive solar events in which a flare was followed by type 2 and type 4 radio emission and a rare chromospheric wave.
Chao, J. K.↗
Inversion of passive microwave remote sensing data from satellites
Global passive microwave observations from earth-orbiting satellites have mapped humidity and liquid water over ocean, temperature profiles, ice and snow, and other geophysical parameters. In most applications, the inversion problem is adequately approximated as linear with jointly Gaussian statistics, and, thus, a linear retrieval performs well. In some cases, the problem is typically factored into a decision process followed by appropriate linear or quasilinear processes. Certain problems, however, require more powerful nonlinear or nonstationary procedures, such as Kalman filtering.
Staelin, D. H.↗
A dual-processor multi-frequency implementation of the FINDS algorithm
This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance.
Godiwala, Pankaj M.↗
Minimum Weight Design of a Leaf Spring Tapered in Thickness and Width for the Hubble Space Telescope-Space Support Equipment
A linear elastic solution to the problem of minimum weight design of cantilever beams with variable width and depth is presented. The solution shown is for the specific application of the Hubble Space Telescope maintenance mission hardware. During these maintenance missions, delicate instruments must be isolated from the potentially damaging vibration environment of the space shuttle cargo bay during the ascent and descent phases. The leaf springs are designed to maintain the isolation system natural frequency at a level where load transmission to the instruments in a minimum. Nonlinear programming is used for the optimization process. The weight of the beams is the objective function with the deflection and allowable bending stress as the constraint equations. The design variables are the width and depth of the beams at both the free and the fixed ends.
Rodriguez, P. I.↗
Slot clock recovery in optical PPM communication systems with avalanche photodiode photodetectors
Slot timing recovery in a direct-detection optical PPM communication system can be achieved by processing the photodetector output waveform with a nonlinear device whose output forms the input to a phase-locked loop. The choice of a simple transition detector as the nonlinearity is shown to give satisfactory synchronization performance. The rms phase error of the recovered slot clock and the effect of slot timing jitter on the bit error probability were directly measured. The experimental system consisted of an AlGaAs laser diode (wavelength = 834 nm) and a silicon avalanche photodiode photodetector. The system used Q = 4 PPM signaling and operated at a source data rate of 25 Mbits/s. The mathematical model developed to compute the rms phase error of the recovered clock is shown to be in good agreement with results of actual measurements of phase errors. The use of the recovered slot clock in the receiver resulted in no significant degradation in receiver sensitivity compared to a system with perfect slot timing. The system achieved a bit error probability of 10 to the -6th at a received optical signal energy of 55 detected photons per information bit.
Davidson, Frederic M.↗
Reflexive Biodynamics for Immune Inspired Computing
Artificial Immune Systems is a rapidly growing field of information processing based upon immune inspired paradigms of nonlinear dynamics.
Reflexive Biodynamics↗
Aeroelasticity Benchmark Assessment: Subsonic Fixed Wing Program
The fundamental technical challenge in computational aeroelasticity is the accurate prediction of unsteady aerodynamic phenomena and the effect on the aeroelastic response of a vehicle. Currently, a benchmarking standard for use in validating the accuracy of computational aeroelasticity codes does not exist. Many aeroelastic data sets have been obtained in wind-tunnel and flight testing throughout the world; however, none have been globally presented or accepted as an ideal data set. There are numerous reasons for this. One reason is that often, such aeroelastic data sets focus on the aeroelastic phenomena alone (flutter, for example) and do not contain associated information such as unsteady pressures and time-correlated structural dynamic deflections. Other available data sets focus solely on the unsteady pressures and do not address the aeroelastic phenomena. Other discrepancies can include omission of relevant data, such as flutter frequency and / or the acquisition of only qualitative deflection data. In addition to these content deficiencies, all of the available data sets present both experimental and computational technical challenges. Experimental issues include facility influences, nonlinearities beyond those being modeled, and data processing. From the computational perspective, technical challenges include modeling geometric complexities, coupling between the flow and the structure, grid issues, and boundary conditions. The Aeroelasticity Benchmark Assessment task seeks to examine the existing potential experimental data sets and ultimately choose the one that is viewed as the most suitable for computational benchmarking. An initial computational evaluation of that configuration will then be performed using the Langley-developed computational fluid dynamics (CFD) software FUN3D1 as part of its code validation process. In addition to the benchmarking activity, this task also includes an examination of future research directions. Researchers within the Aeroelasticity Branch will examine other experimental efforts within the Subsonic Fixed Wing (SFW) program (such as testing of the NASA Common Research Model (CRM)) and other NASA programs and assess aeroelasticity issues and research topics.
Florance, Jennifer P.↗
Precomputing Process Noise Covariance for Onboard Sequential Filters
Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.
onboard↗
Satellite Constellation Orbit Design to Enable a Space-Based Radio Interferometer
Two different design methods for a networked constellation of N small satellites are presented. In the first method, the (linear) Clohessy-Wilthsire equations are used as an initial design tool, followed by conversion to a two-body model. Discrepancies between the linear and nonlinear solutions are minimized in the conversion process. The second method utilizes invariant manifold theory, by perturbing a reference trajectory in different directions along the center eigenvectors. Both methods require 5N parameters to fully define a constellation. In a relative, rotating frame of the reference path, the spacecraft appear as periodic ellipses of varying sizes. Deployment, reconfiguration using propulsive maneuvers, and station keeping costs for an example mission scenario are addressed.
Chien, Steve A.↗
A hybrid neurocomputing/numerical strategy for nonlinear structural analysis
A hybrid neurocomputing/numerical strategy is presented for geometrically nonlinear analysis of structures. The strategy combines model-free data processing capabilities of computational neural networks with a Pade approximants-based perturbation technique to predict partial information about the nonlinear response of structures. In the hybrid strategy, multilayer feedforward neural networks are used to extend the validity of solutions by using training samples produced by Pade approximations to the Taylor series expansion of the response function. The range of validity of the training samples is taken to be the radius of convergence of Pade approximants and is estimated by setting a tolerance on the diverging approximants. The norm of residual vector of unbalanced forces in a given element is used as a measure to assess the quality of network predictions. To further increase the accuracy and the range of network predictions, additional training data are generated by either applying linear regression to weight matrices or expanding the training data by using predicted coefficients in a Taylor series. The effectiveness of the hybrid strategy is assessed by performing large-deflection analysis of a doubly-curved composite panel with a circular cutout, and postbuckling analyses of stiffened composite panels subjected to an in-plane edge shear load. In all the problems considered, the hybrid strategy is used to predict selective information about the structural response, namely the total strain energy and the maximum displacement components only.
Szewczyk, Z. Peter↗
EEG and chaos: Description of underlying dynamics and its relation to dissociative states
The goal of this work is the identification of states especially as related to the process of error production and lapses of awareness as might be experienced during aviation. Given the need for further articulation of the characteristics of 'error prone state' or 'hazardous state of awareness,' this NASA grant focused on basic ground work for the study of the psychophysiology of these states. In specific, the purpose of this grant was to establish the necessary methodology for addressing three broad questions. The first is how the error prone state should be conceptualized, and whether it is similar to a dissociative state, a hypnotic state, or absent mindedness. Over 1200 subjects completed a variety of psychometric measures reflecting internal states and proneness to mental lapses and absent mindedness; the study suggests that there exists a consistency of patterns displayed by individuals who self-report dissociative experiences such that those individuals who score high on measures of dissociation also score high on measures of absent mindedness, errors, and absorption, but not on scales of hypnotizability. The second broad question is whether some individuals are more prone to enter these states than others. A study of 14 young adults who scored either high or low on the dissociation experiences scale performed a series of six tasks. This study suggests that high and low dissociative individuals arrive at the experiment in similar electrocortical states and perform cognitive tasks (e.g., mental math) in a similar manner; it is in the processing of internal emotional states that differences begin to emerge. The third question to be answered is whether recent research in nonlinear dynamics, i.e., chaos, offer an addition and/or alternative to traditional signal processing methods, i.e., fast Fourier transforms, and whether chaos procedures can be modified to offer additional information useful in identifying brain states. A preliminary review suggests that current nonlinear dynamical techniques such as dimensional analysis can be successfully applied to electrocortical activity. Using the data set developed in the study of the young adults, chaos analyses using the Farmer algorithm were performed; it is concluded that dimensionality measures reflect information not contained in traditional EEG Fourier analysis.
Ray, William J.↗
Design of intelligent mesoscale periodic array structures utilizing smart hydrogel
Mesoscale Periodic Array Structures (MPAS, also known as crystalline colloidal arrays), composed of aqueous or nonaqueous dispersions of self-assembled submicron colloidal spheres are emerging toward the development of advanced optical devices for technological applications. This is because of their unique optical diffraction properties and the ease with which these intriguing properties can be modulated experimentally. Moreover our recent advancements in this area which include 'locking' the liquid MPAS into solid or semisolid polymer matrices for greater stability with longer life span, and incorporation of CdS quantum dots and laser dyes into colloidal spheres to obtain nonlinear optical (NLO) responses further corroborate the use of MPAS in optical technology. Our long term goal is fabrication of all-optical and electro-optical devices such as spatial light modulators for optical signal processing and flat panel display devices by utilizing intelligent nonlinear periodic array structural materials. Here we show further progress in the design of novel linear MPAS which have the ability to sense and respond to an external source such as temperature. This is achieved by combining the self-assembly properties of polymer colloidal spheres and thermoshrinking properties of smart polymer gels. At selected temperatures the periodic array efficiently Bragg diffracts light and transmits most of the light at other temperatures. Hence these intelligent systems are of potential use as fixed notch filters optical switches or limiters to protect delicate optical sensors from high intensity laser radiation.
Sunkara, H. B.↗
Twist Model Development and Results from the Active Aeroelastic Wing F/A-18 Aircraft
Understanding the wing twist of the active aeroelastic wing (AAW) F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption. This technique produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.
Lizotte, Andrew M.↗
Performances Of Fixed-Lag Phase-Smoothing Algorithms
Report discusses performances of fixed-lag nonlinear smoothing algorithms applied to estimation of phase and frequency of sinusoidal carrier signal with process phase noise and additive observation phase noise. Algorithm of type considered functions as suboptimal filter operating on received signal. Algorithm developed for system in which signal sampled at discrete times. Process noise assumed to be Gaussian with zero mean and independent of observation noise. Nonlinear smoothing equations derived in customary matrix-and-vector forms.
Kumar, Rajendra↗
Twist Model Development and Results From the Active Aeroelastic Wing F/A-18 Aircraft
Understanding the wing twist of the active aeroelastic wing F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption and by using neural networks. These techniques produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.
Lizotte, Andrew↗
Assessing Nonlinear Polarization in Electrochemical Cells using AC Impedance Spectroscopy
AC impedance spectroscopy is widely used to evaluate performance limitations in energy storage and conversion devices (e.g., batteries, supercapacitors, and fuel cells). This work shows that integrating the resistive elements in an equivalent circuit as functions of steady-state current enables one to recover overpotentials associated with different processes (e.g., ion migration, charge transfer, and diffusion) in nonlinear electrochemical power supplies. Closed form expressions for diffusion overpotentials are derived using this method for transmissive and reflective boundary conditions and three electrode symmetries (planar, cylindrical, and spherical). Discussion is also extended to macroscopically homogenous porous electrodes which are relevant for most real-world devices. Overall, the approach described herein is a powerful tool to identify rate-limiting steps and guide material/component design.
25 ENERGY STORAGE↗
Observational and theoretical analyses of polar cap/auroral region f(sub p) and 2 f(sub p) emissions using the polar and DE 1 satellites
The objective of this proposal was to conduct a comprehensive observational and theoretical investigation, including 2-D numerical simulations of emissions that occur near f(sub p) and 2 f(sub p) as observed by the Dynamics Explorer 1 (DE 1) spacecraft in the mid-altitude polar magnetosphere. Electrostatic electron plasma waves (or Langmuir waves) and associated electromagnetic (ETD) radiation near f(sub p) and 2 f(sub p) have previously been observed associated with the Earth's foreshock and in coronal/solar wind type II and III solar radio bursts. The observations of similar emissions in the terrestrial polar magnetosphere have not been previously reported and are important for a better understanding of the range of generation processes. We have been cataloging the location, electric and magnetic intensity, polarization, bandwidth, etc. of the emissions. The theoretical analysis included linear and nonlinear plasma theory. The goal was to fully describe the generation processes for both the f(sub p) (PF component) and 2 f(sub p) (H component) emissions. Although this goal was not completely accomplished, we have made significant advances in our understanding of these emissions.
Menietti, J. D.↗