Adaptive Periodic-Correlation Algorithm for Extended-Scene Shack-Hartmann Wavefront Sensing
No abstract available
phase retrieval↗
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Results for “adaptive algorithm”
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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Pulsar identification method based on adaptive grey wolf optimization algorithm in X-ray pulsar-based navigations
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Hongyang Zhao↗
In Situ Adaptive Battery Parameter Estimation Algorithm with Cross-Validation and Observer.
Abstract not provided.
Dutta, Oindrilla↗
Toward implementing autonomous adaptive data acquisition for scanning hyperspectral imaging of biological systems
Autonomous experimentation is an emerging area of research, primarily related to autonomous vehicles, scientific combinatorial discovery approaches in materials science and drug discovery, and iterative research loops of planning, experimentation, and analysis. However, autonomous approaches developed in these contexts are difficult to apply to high-dimensional mapping technologies, such as scanning hyperspectral imaging of biological systems, due to sample complexity and heterogeneity. We briefly cover the history of adaptive sampling algorithms and surrogate modeling in order to define autonomous adaptive data acquisition as an objective-based, flexible building block for future biological imaging experimentation driven by intelligent infrastructure. We subsequently summarize the recent implementations of autonomous adaptive data acquisition (AADA) for scanning hyperspectral imaging, assess how these address the difficulties of autonomous approaches in hyperspectral imaging, and highlight the AADA design variation from a goal-oriented perspective. Finally, we present a modular AADA architecture that embeds AADA-driven flexible building blocks to address the challenge of time resolution for high-dimensional scanning hyperspectral imaging of nonequilibrium dynamical systems. In our example research-driven experimental design case, we propose an AADA infrastructure for time-resolved, noninvasive, and label-free scanning hyperspectral imaging of living biological systems. This AADA infrastructure can accurately target the correct state of the system for experimental workflows that utilize subsequent expensive, high-information-content analytical techniques.
59 BASIC BIOLOGICAL SCIENCES↗
Statistical Study of the Properties of Magnetosheath Lion Roars
Lion roars are narrowband whistler wave emissions that have been observed in several environments, such as planetary magnetosheaths, the Earth's magnetosphere, the solar wind, downstream of interplanetary shocks, and the cusp region. We present measurements of more than 30,000 such emissions observed by the Magnetospheric Multiscale spacecraft with high‐cadence (8,192 samples/s) search coil magnetometer data. A semiautomatic algorithm was used to identify the emissions, and an adaptive interval algorithm in conjunction with minimum variance analysis was used to determine their wave vector. The properties of the waves are determined in both the spacecraft and plasma rest frame. The mean wave normal angle, with respect to the background magnetic field (B(sub 0)), plasma bulk flow velocity (V(sub b)), and the coplanarity plane (V(sub b) × B(sub 0)) are 23°, 56°, and 0°, respectively. The average peak frequencies were ∼31% of the electron gyrofrequency (ω(sub ce)) observed in the spacecraft frame and ∼18% of ω(sub ce) in the plasma rest frame. In the spacecraft frame, ∼99% of the emissions had a frequency <ω(sub ce), while 98% had a peak frequency <0.72 ω(sub ce) in the plasma rest frame. None of the waves had frequencies lower than the lower hybrid frequency, ω. From the probability density function of the electron plasma β(sub e), the ratio between the electron thermal and magnetic pressure, ∼99.6% of the waves were observed with β(sub e)<4 with a large narrow peak at 0.07 and two smaller, but wider, peaks at 1.26 and 2.28, while the average value was ∼1.25.
Magnetosheath emissions↗
Recursive algorithm for the calculation of the adaptive Kalman filter weighting coefficients.
Weighting coefficients calculations by recursive algorithm for designing optimal discrete adaptive Kalman filter
Lainiotis, D. G.↗
Development and application of computational aerothermodynamics flowfield computer codes
Research was performed in the area of computational modeling and application of hypersonic, high-enthalpy, thermo-chemical nonequilibrium flow (Aerothermodynamics) problems. A number of computational fluid dynamic (CFD) codes were developed and applied to simulate high altitude rocket-plume, the Aeroassist Flight Experiment (AFE), hypersonic base flow for planetary probes, the single expansion ramp model (SERN) connected with the National Aerospace Plane, hypersonic drag devices, hypersonic ramp flows, ballistic range models, shock tunnel facility nozzles, transient and steady flows in the shock tunnel facility, arc-jet flows, thermochemical nonequilibrium flows around simple and complex bodies, axisymmetric ionized flows of interest to re-entry, unsteady shock induced combustion phenomena, high enthalpy pulsed facility simulations, and unsteady shock boundary layer interactions in shock tunnels. Computational modeling involved developing appropriate numerical schemes for the flows on interest and developing, applying, and validating appropriate thermochemical processes. As part of improving the accuracy of the numerical predictions, adaptive grid algorithms were explored, and a user-friendly, self-adaptive code (SAGE) was developed. Aerothermodynamic flows of interest included energy transfer due to strong radiation, and a significant level of effort was spent in developing computational codes for calculating radiation and radiation modeling. In addition, computational tools were developed and applied to predict the radiative heat flux and spectra that reach the model surface.
Venkatapathy, Ethiraj↗
Software for Generating Strip Maps from SAR Data
Jurassicprok is a computer program that generates strip-map digital elevation models and other data products from raw data acquired by an airborne synthetic-aperture radar (SAR) system. This software can process data from a variety of airborne SAR systems but is designed especially for the GeoSAR system, which is a dual-frequency (P- and X-band), single-pass interferometric SAR system for measuring elevation both at the bare ground surface and top of the vegetation canopy. Jurassicprok is a modified version of software developed previously for airborne-interferometric- SAR applications. The modifications were made to accommodate P-band interferometric processing, remove approximations that are not generally valid, and reduce processor-induced mapping errors to the centimeter level. Major additions and other improvements over the prior software include the following: a) A new, highly efficient multi-stage-modified wave-domain processing algorithm for accurately motion compensating ultra-wideband data; b) Adaptive regridding algorithms based on estimated noise and actual measured topography to reduce noise while maintaining spatial resolution; c) Exact expressions for height determination from interferogram data; d) Fully calibrated volumetric correlation data based on rigorous removal of geometric and signal-to-noise decorrelation terms; e) Strip range-Doppler image output in user-specified Doppler coordinates; f) An improved phase-unwrapping and absolute-phase-determination algorithm; g) A more flexible user interface with many additional processing options; h) Increased interferogram filtering options; and i) Ability to use disk space instead of random- access memory for some processing steps.
Hensley, Scott↗
A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes
The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.
Adaptive mesh refinement↗
Some design guidelines for discrete-time adaptive controllers
There have been many algorithms proposed for adaptive control which will provide globally asymptotically stable controllers if some stringent conditions on the plant are met. The conditions on the plant cannot be met in practice as all plants will contain high frequency unmolded dynamics therefore, blind implementation of the published algorithms can lead to disastrous results. This paper uses a linearization analysis of a non-linear adaptive controller to demonstrate analytically design guidelines which aleviate some of the problems associated with adaptive control in the presence of unmodeled dynamics.
Rohrs, C. E.↗
Adaptive Control of Small Outboard-Powered Boats for Survey Applications
Four autopilot controllers have been developed in this work that can both hold a desired heading and follow a straight line. These PID, adaptive PID, neuro-adaptive, and adaptive augmenting control algorithms have all been implemented into a numerical simulation of a 33-foot center console vessel with wind, waves, and current disturbances acting in the perpendicular (across-track) direction of the boat s desired trajectory. Each controller is tested for its ability to follow a desired heading in the presence of these disturbances and then to follow a straight line at two different throttle settings for the same disturbances. These controllers were tuned for an input thrust of 2000 N and all four controllers showed good performance with none of the controllers significantly outperforming the others when holding a constant heading and following a straight line at this engine thrust. Each controller was then tested for a reduced engine thrust of 1200 N per engine where each of the three adaptive controllers reduced heading error and across-track error by approximately 50% after a 300 second tuning period when compared to the fixed gain PID, showing that significant robustness to changes in throttle setting was gained by using an adaptive algorithm.
VanZwieten, T.S.↗
Compression of multispectral Landsat imagery using the Embedded Zerotree Wavelet (EZW) algorithm
The Embedded Zerotree Wavelet (EZW) algorithm has proven to be an extremely efficient and flexible compression algorithm for low bit rate image coding. The embedding algorithm attempts to order the bits in the bit stream in numerical importance and thus a given code contains all lower rate encodings of the same algorithm. Therefore, precise bit rate control is achievable and a target rate or distortion metric can be met exactly. Furthermore, the technique is fully image adaptive. An algorithm for multispectral image compression which combines the spectral redundancy removal properties of the image-dependent Karhunen-Loeve Transform (KLT) with the efficiency, controllability, and adaptivity of the embedded zerotree wavelet algorithm is presented. Results are shown which illustrate the advantage of jointly encoding spectral components using the KLT and EZW.
Shapiro, Jerome M.↗
An investigation of adaptive control techniques for space stations
The present paper is concerned with control problems which arise in connection with the establishment and maintenance of space stations. Some of the arising problems are related to great changes in mass and an intensive shock load accompanying Shuttle docking. Such problems can be solved by making use of a robust adaptive control system. Space station configurations developed by NASA and the corresponding mass properties are discussed along with dynamic models for space stations, aspects of problem formulation and control architecture, adaptive control algorithms, a performance analysis, and practical considerations. Attention is given to adaptive regulator control with initial transient, adaptive control during Shuttle docking, and cases involving Shuttle hard docking with model switching and disturbance modeling.
Ih, C.-H. C.↗
Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals
A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.
Combustion↗
Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module
MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.
97 MATHEMATICS AND COMPUTING↗
High Frequency Adaptive Instability Suppression Controls in a Liquid-Fueled Combustor
This effort extends into high frequency (>500 Hz), an earlier developed adaptive control algorithm for the suppression of thermo-acoustic instabilities in a liquidfueled combustor. The earlier work covered the development of a controls algorithm for the suppression of a low frequency (~280 Hz) combustion instability based on simulations, with no hardware testing involved. The work described here includes changes to the simulation and controller design necessary to control the high frequency instability, augmentations to the control algorithm to improve its performance, and finally hardware testing and results with an experimental combustor rig developed for the high frequency case. The Adaptive Sliding Phasor Averaged Control (ASPAC) algorithm modulates the fuel flow in the combustor with a control phase that continuously slides back and forth within the phase region that reduces the amplitude of the instability. The results demonstrate the power of the method - that it can identify and suppress the instability even when the instability amplitude is buried in the noise of the combustor pressure. The successful testing of the ASPAC approach helped complete an important NASA milestone to demonstrate advanced technologies for low-emission combustors.
Kopasakis, George↗
Thermal and Cycle-Life Behavior of Commercial Li-ion and Li-Polymer Cells
Accelerated and real-time LEO cycle-life test data will be presented for a range of commercial Li-ion and Li-polymer (gel type) cells indicating the ranges of performance that can be obtained, and the performance screening tests that must be done to assure long life. The data show large performance variability between cells, as well as a highly variable degradation signature during non-cycling periods within the life tests. High-resolution Dynamic Calorimetry data will be presented showing the complex series of reactions occurring within these Li cells as they are cycled. Data will also be presented for cells being tested using an Adaptive Charge Control Algorithm (ACCA) that continuously adapts itself to changes in cell performance, operation, or environment to both find and maintain the optimum recharge over life. The ACCA has been used to prevent all unneeded overcharge for Li cells, NiCd cells and NiH2 cells. While this is important for all these cell types, it is most critical for Li-ion cells, which are not designed with electrochemical tolerance for overcharge.
Zimmerman, Albert H.↗
Remote Sensing of Daytime Water Leaving Reflectances of Oceans and Large Inland Lakes from EPIC onboard the DSCOVR Spacecraft at Lagrange-1 Point
The NASA’s Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) satellite has been making multiple observations of the entire sunlit Earth in a given day from the Sun-Earth Lagrangian L1 point since the summer of 2015. EPIC contains 10 narrow channels in the 317–780 nm solar spectral range. The data acquired with EPIC have already been used in a variety of scientific investigations, including the study of the global ozone levels, aerosol index and aerosol optical depth, UV reflectivity of clouds over land and ocean, cloud height over land and ocean, and vegetation indices. In this article, we report that EPIC data, particularly for the data measured with narrow channels centered near 443, 551, and 680 nm, can also have important applications in remote sensing of ocean color in different geographical regions. We have modified a version of a multi-channel atmospheric correction algorithm for Moderate Resolution Imaging Spectro Radiometer (MODIS) ocean color applications and adapted the algorithm for processing EPIC data. We present three case studies on water leaving reflectance retrievals from EPIC data acquired over a large turbid river, inland lakes, and oceans. We conclude that a future ocean color instrument on board a satellite at the L1 point, which provides continuous view of the full sunlit disk of the Earth, will complement and extend ocean color observations with the low Earth observing polar orbital and geostationary satellite instruments in both the spatial and time domains.
remote sensing↗