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Results for “Dynamic compressive sensing”

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At least 19 records

Dynamic compressed sensing for real-time tomographic reconstruction

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by ~3-fold while also reducing its error by 27% for a Au/SrTiO 3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within ~33% of completion and fine details are visible as early as ~66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, we report reconstruction parameters that tune data fidelity can be manipulated throughout the computation without re-running the entire process.

47 OTHER INSTRUMENTATION↗

Recursive Dynamic Compressive Sensing in Smart Distribution Systems

With a transition to a smarter grid, we are witnessing a significant growth in smart metering infrastructure and sensor deployment in the distribution system. The underlying communication infrastructure is stressed due to the large volume of data that is generated by the smart meters/sensors. Furthermore, real time operations such as state estimation and control are impaired due to the lack of reliable aggregation of the data. In this paper, we exploit the underlying sparsity in grid data to implement two recursive dynamic compressive sensing (CS) approaches-streaming modified weighted-`1 CS and Kalman filtered CS. These approaches aim to reconstruct the sparse signal using the current underdetermined measurements and the prior information about the sparse signal and its support set. Slow signal and support change is in distribution grid data is validated using Pecan Street data. Both the IEEE 34 node test feeder system and PecanStreet data are considered as two examples to validate the superior performance of the two recursive CS techniques relative to classic CS.

Karimi, Hazhar Sufi↗

Dynamic signal recovery in distribution grids using compressive lossy measurements

Distribution system state estimation requires reliable aggregation of the measured data. However, the large volume of the measured data imposes a significant stress on the underlying communication infrastructure. With the challenges associated with measurement availability, current distribution systems are typically unobservable. To cope with the unobservability issue, compressive sensing theory allows us to recover system state information from a small number of measurements provided the states of the distribution system exhibit sparsity. In this paper, we evaluate the robustness of an updated Kalman filtered modified compressive sensing (KF-ModCS) technique that dynamically estimates the grid states using a small fraction of measured data. In practice, measurements used for sparsity based state estimation may also be intermittent due to communication network induced losses. Further, to understand the effect of packet losses on KF-ModCS, we provide an upper bound for the expected variances of the state estimation error for a given rate of information loss. This upper bound is further improved if the support set of the sparse signal that characterizes the state dynamics does not change over time and/or the reduced model is observable. Simulations based on two practical data sets collected from actual customers in a distribution grid validate the theoretical results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Self‐gated, dynamic contrast‐enhanced magnetic resonance imaging with compressed‐sensing reconstruction for evaluating endothelial permeability in the aortic root of atherosclerotic mice

High‐risk atherosclerotic plaques are characterized by active inflammation and abundant leaky microvessels. We present a self‐gated, dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) acquisition with compressed sensing reconstruction and apply it to assess longitudinal changes in endothelial permeability in the aortic root of Apoe −/− atherosclerotic mice during natural disease progression. Twenty‐four, 8‐week‐old, female Apoe −/− mice were divided into four groups (n = 6 each) and imaged with self‐gated DCE‐MRI at 4, 8, 12, and 16 weeks after high‐fat diet initiation, and then euthanized for CD68 immunohistochemistry for macrophages. Eight additional mice were kept on a high‐fat diet and imaged longitudinally at the same time points. Aortic‐root pseudo‐concentration curves were analyzed using a validated piecewise linear model. Contrast agent wash‐in and washout slopes ( b 1 and b 2 ) were measured as surrogates of aortic root endothelial permeability and compared with macrophage density by immunohistochemistry. b 2 , indicating contrast agent washout, was significantly higher in mice kept on an high‐fat diet for longer periods of time ( p = 0.03). Group comparison revealed significant differences between mice on a high‐fat diet for 4 versus 16 weeks ( p = 0.03). Macrophage density also significantly increased with diet duration ( p = 0.009). Spearman correlation between b 2 from DCE‐MRI and macrophage density indicated a weak relationship between the two parameters (r = 0.28, p = 0.20). Validated piecewise linear modeling of the DCE‐MRI data showed that the aortic root contrast agent washout rate is significantly different during disease progression. Further development of this technique from a single‐slice to a 3D acquisition may enable better investigation of the relationship between in vivo imaging of endothelial permeability and atherosclerotic plaques' genetic, molecular, and cellular makeup in this important model of disease.

Calcagno, Claudia↗

Accelerating Ultrafast Spectroscopy with Compressive Sensing

We report ultrafast spectroscopy is an important tool for studying photoinduced dynamical processes in atoms, molecules, and nanostructures. Typically, the time to perform these experiments ranges from several minutes to hours depending on the choice of spectroscopic method. It is desirable to reduce this time overhead not only to shorten time and laboratory resources, but also to make it possible to examine fragile specimens that quickly degrade during long experiments. In this article, we motivate using compressive sensing to significantly shorten data acquisition time by reducing the total number of measurements in ultrafast spectroscopy. We apply this technique to experimental data from ultrafast transient absorption spectroscopy and ultrafast terahertz spectroscopy and show that good estimates can be obtained with as low as 15% of the total measurements, implying a sixfold reduction in the data acquisition time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation

This paper combines model-based and data-driven methods to develop a hierarchical, decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level and hence significantly speed up the computational time. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system, and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sparse and Random Sampling Techniques for High-Resolution, Full-Field, BSS-Based Structural Dynamics Identification from Video

Video-based techniques for identification of structural dynamics have the advantage that they are very inexpensive to deploy compared to conventional accelerometer or strain gauge techniques. When structural dynamics from video is accomplished using full-field, high-resolution analysis techniques utilizing algorithms on the pixel time series such as principal components analysis and solutions to blind source separation the added benefit of high-resolution, full-field modal identification is achieved. An important property of video of vibrating structures is that it is particularly sparse. Typically video of vibrating structures has a dimensionality consisting of many thousands or even millions of pixels and hundreds to thousands of frames. However the motion of the vibrating structure can be described using only a few mode shapes and their associated time series. As a result, emerging techniques for sparse and random sampling such as compressive sensing should be applicable to performing modal identification on video. This work presents how full-field, high-resolution, structural dynamics identification frameworks can be coupled with compressive sampling. The techniques described in this work are demonstrated to be able to recover mode shapes from experimental video of vibrating structures when 70% to 90% of the frames from a video captured in the conventional manner are removed.

47 OTHER INSTRUMENTATION↗

Century: Zap Energy’s 100-kW-Scale Repetitive Sheared-Flow-Stabilized Z -Pinch System with Liquid Metal Cooling

Zap Energy is developing the sheared-flow-stabilized (SFS) Z-pinch concept for commercial applications. The SFS Z pinch relies on plasma self-organization, in the sense that plasma dynamics play a critical role in confinement. Using plasma axial current for confinement and compression eliminates the need for external confinement or heating technologies. This compact magnetic confinement technology could, in turn, provide the basis for a cost-effective deuterium-tritium fusion power plant. In addition to a robust experimental program pushing plasma performance towards breakeven conditions, Zap Energy has parallel programs developing power handling systems suitable for future power plants. Technologies under development include high average-power repetitive pulsed power, high duty-cycle cathodes, and liquid metal wall systems. Century is the name of Zap Energy’s first effort to integrate these three components into an operational system capable of firing non-reacting hydrogen SFS Z-pinch plasmas into a liquid-metal-lined container at sustained repetition rates on the order of 0.1 Hz. Here, the pulsed power driver and liquid metal heat exchanger are both designed to sustain input powers of 100 kW. Construction and initial operations with an interim ~10 kW liquid metal heat exchanger are described.

Century↗

Fast wide-field upconversion luminescence lifetime thermometry enabled by single-shot compressed ultrahigh-speed imaging

Photoluminescence lifetime imaging of upconverting nanoparticles is increasingly featured in recent progress in optical thermometry. Despite remarkable advances in photoluminescent temperature indicators, existing optical instruments lack the ability of wide-field photoluminescence lifetime imaging in real time, thus falling short in dynamic temperature mapping. Here, we report video-rate upconversion temperature sensing in wide field using single-shot photoluminescence lifetime imaging thermometry (SPLIT). Developed from a compressed-sensing ultrahigh-speed imaging paradigm, SPLIT first records wide-field luminescence intensity decay compressively in two views in a single exposure. Then, an algorithm, built upon the plug-and-play alternating direction method of multipliers, is used to reconstruct the video, from which the extracted lifetime distribution is converted to a temperature map. Using the core/shell NaGdF 4 :Er 3+ ,Yb 3+ /NaGdF 4 upconverting nanoparticles as the lifetime-based temperature indicators, we apply SPLIT in longitudinal wide-field temperature monitoring beneath a thin scattering medium. SPLIT also enables video-rate temperature mapping of a moving biological sample at single-cell resolution.

47 OTHER INSTRUMENTATION↗

Ways to Increase Launch Velocities of 2-Stage Gas Guns

The amount of space debris is rapidly increasing and the debris is distributed over a wide variety of orbits. Satellites, manned space vehicles and space stations will have to pay increasing attention to the dangers of impacts with space debris. Various armoring techniques (i.e., double or triple layer armor) will have to tested extensively to determine the most effective armor per unit weight. Intersecting near-earth orbits can lead to impact velocities up to 15 km/sec. Conventional two-stage light gas guns can launch intact, controlled-shape projectiles with a density of 1.2 gm/cc and length- to-diameter ratios of 0.5-1.0 at velocities up to 8-9 km/sec. Higher velocities (10-11 km/sec) can be obtained' for very light projectiles. The higher launch velocities tend to be very severe on the high pressure coupling and barrel of the gun and lead to short component lifetimes. Clearly, the ability to raise the launch velocity of a gun (for reasonably massive projectile shapes) from 8-9 km/sec to 11-13 km/sec (or higher), without reduction of component lifetimes, would have significant benefits. This would allow much better simulation of the higher velocity debris impacts as well as better simulation of high speed re-entry into planetary atmospheres. Several techniques for increasing the launcher muzzle velocity above 8-9 km/sec have been studied using CFD simulations and appear to offer the potential for significant gains. The first technique is to use multiple compressions, instead of a single compression, in the pump tube of the light gas gun. In a sense, this is a kind of pre-heating of the gas in the pump tube; other types of pre-heating have yielded disappointing results in the past. The dynamics of the multiple compression pump tube is very different, however, from the earlier techniques, where the pump tube was typically heated ohmically before the gun 2 cycle was started. In this paper, we present CFD calculations that show that significant increases in muzzle velocity can be obtained with multiple compressions in the pump tube. With a conventional two-stage gun, an important limitation to obtaining higher velocities is friction and heat transfer to the barrel, which typically has a length- to- diameter ratio of 200-400. These viscous losses greatly reduce the effectiveness of the regions of the barrel far removed from the second stage breech. We have studied computationally the effect of adding an additional breech (or breeches) along the barrel to reduce these viscous losses. Velocity increases from 6.5 to 7.2 km/sec have been obtained using the main breech and one additional breech. In these results, both breeches were operated with hydrogen, heated electrothermally. We have also studied a gun geometry where the main breech is operated in the conventional manner, using piston compression. The additional breech is operated either with electrothermal heating or heating by using a high explosive charge in a novel geometry. The latter option provides very effective compression, heating and acceleration of the hydrogen working gas and is fully reusable. Calculations are presented which show that very substantial increases in muzzle velocity can be obtained this way, without overstressing the projectile or the 'gun. The third technique studied is to add a section of ram accelerator tube after the barrel to further accelerate the projectile. The ram accelerator used here is not the conventional premixed gas ram accelerator, but a new technique using high explosive as the energy source and pure hydrogen as the working gas in a geometry which can be made fully reusable. Preliminary results with this new rain accelerator geometry were presented and showed that stable ram accelerator drive can be established. Herein, detailed calculations axe presented which show that substantial velocity increases can be obtained using this ram accelerator technique in tandem with a conventional light gas gun.

Bogdanoff, David W.↗

Constraining the Multiscale Structure of Geophysical Fields in Machine Learning: The Case of Precipitation

The use of deep-learning algorithms for estimating the value of geophysical variables from remotely sensed information is rapidly expanding. The typical objective function minimized in such algorithms is the mean square error (MSE), which is known to lead to smooth estimates with compressed dynamical range as compared to the true distribution of the variable of interest. Here, we introduce and evaluate alternative objective functions, focusing on the retrieval of precipitation rates from satellite passive microwave radiometric measurements using a deep convolutional neural network. For this testbed application, the results show that explicitly imposing the preservation of the statistical distribution and spatial wavelet power spectrum of the target variable allows to accurately reproduce extreme values and sharp gradients across multiple scales in this study.

58 GEOSCIENCES↗

Sparse adaptive basis set methods for solution of the time dependent Schrodinger equation

Scalable numerical solutions to the time dependent Schrodinger equation remain an outstanding goal in theoretical chemistry. Here we present a method which utilises recent breakthroughs in signal processing to consistently adapt a dictionary of basis functions to the dynamics of the system. Further, we show that for two low-dimensional model problems the size of the basis set does not grow quickly with time and appears only weakly dependent on dimensionality. The generality of this finding remains to be seen. The method primarily uses energies and gradients of the potential, opening the possibility for its use in on-the-fly ab initio quantum wavepacket dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Quantum mechanical closure of partial differential equations with symmetries

We develop a statistical framework for the dynamical closure of spatiotemporal dynamics governed by partial differential equations. Employing the mathematical framework of quantum mechanics to embed the original classical dynamics into a quantum mechanical representation, we use the space of quantum density operators to model the unresolved degrees of freedom of the original dynamics in a statistical sense, and the framework of quantum measurement to predict their contributions to the resolved dynamics. The embedded dynamics is discretized by a positivity preserving process, leading to a compressed representation that is invariant under the dynamical symmetries of the resolved dynamics. We present a data based formulation of the closure scheme and apply it to a closure problem for the shallow water equations. The numerical results demonstrate that our closure model can accurately predict the main features of the true dynamics, including for out of sample initial conditions.

Delay embedding↗

Better Pictures in a Snap

Retinex Imaging Processing, winner of NASA's 1999 Space Act Award, is commercially available through TruView Imaging Company. With this technology, amateur photographers use their personal computers to improve the brightness, scene contrast, detail, and overall sharpness of images with increased ease. The process was originally developed for remote sensing of the Earth by researchers at Langley Research Center and Science and Technology Corporation (STC). It automatically enhances a digital image in terms of dynamic range compression, color independence from the spectral distribution of the scene illuminant, and color/lightness rendition. As a result, the enhanced digital image is much closer to the scene perceived by the human visual system, under all kinds and levels of lighting variations. TruView believes there are other applications for the software in medical imaging, forensics, security, recognizance, mining, assembly, and other industrial areas.

Source record↗

Sparse optimization of two-dimensional terahertz spectroscopy

Two-dimensional terahertz spectroscopy (2DTS) is a low-frequency analog of two-dimensional optical spectroscopy that is rapidly maturing as a probe of a wide variety of condensed matter systems. However, a persistent problem with 2DTS is the long experimental acquisition times, which prevent its broader adoption. A potential solution, requiring no increase in experimental complexity, is signal reconstruction via compressive sensing. In this work, we apply the sparse exponential mode analysis (SEMA) technique to 2DTS of a cuprate superconductor. We benchmark the performance of the algorithm in reconstructing terahertz nonlinearities and find that SEMA reproduces the asymmetric photon echo line shapes at sampling rates as low as 10%, reaching the reconstruction noise floor at sampling rates beyond 20%–30%. The success of SEMA in reproducing such subtle, asymmetric line shapes confirms compressive sensing as a general method to accelerate 2DTS and multidimensional spectroscopies more broadly.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters

A large depth-of-field particle image velocimeter (PIV) is designed to characterize dynamic dust environments on planetary surfaces. This instrument detects lofted dust particles, and senses the number of particles per unit volume, measuring their sizes, velocities (both speed and direction), and shape factors when the particles are large. To measure these particle characteristics in-flight, the instrument gathers two-dimensional image data at a high frame rate, typically >4,000 Hz, generating large amounts of data for every second of operation, approximately 6 GB/s. To characterize a planetary dust environment that is dynamic, the instrument would have to operate for at least several minutes during an observation period, easily producing more than a terabyte of data per observation. Given current technology, this amount of data would be very difficult to store onboard a spacecraft, and downlink to Earth. Since 2007, innovators have been developing an autonomous image analysis algorithm architecture for the PIV instrument to greatly reduce the amount of data that it has to store and downlink. The algorithm analyzes PIV images and automatically reduces the image information down to only the particle measurement data that is of interest, reducing the amount of data that is handled by more than 10(exp 3). The state of development for this innovation is now fairly mature, with a functional algorithm architecture, along with several key pieces of algorithm logic, that has been proven through field test data acquired with a proof-of-concept PIV instrument.

Bos, Brent↗

Alfven Waves in the Solar Wind, Magnetosheath, and Outer Magnetosphere

Alfven waves Propagating outward from the Sun are ubiquitous in the solar wind and play a major role in the solar wind-magnetosphere interaction. The passage of the waves generally occurs in the form of a series of discrete steepened discontinuities, each of which results in an abrupt change in the interplanetary magnetic field direction. Some orientations of the magnetic field permit particles energized at the Earth's bow shock to gain access to the foreshock region immediately upstream from the Earth's bow shock. The thermal pressure associated with these particles can greatly perturb solar wind plasma and magnetic field parameters shortly prior to their interaction with the Earth's bow shock and magnetosphere. The corresponding dynamic pressure variations batter the magnetosphere, driving magnetopause motion and transient compressions of the magnetospheric magnetic field. Alfven waves transmit information concerning the dynamic pressure variations applied to the magnetosphere to the ionosphere, where they generate the traveling convection vortices (TCVs) seen in high-latitude ground magnetograms. Finally, the sense of Alfvenic perturbations transmitted into the magnetosheath reverses across local noon because magnetosheath magnetic field lines drape against the magnetopause. The corresponding change in velocity perturbations must apply a weak torque to the Earth's magnetosphere.

Sibeck, D. G.↗