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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Advanced techniques and technology for efficient data storage, access, and transfer

Advanced techniques for efficiently representing most forms of data are being implemented in practical hardware and software form through the joint efforts of three NASA centers. These techniques adapt to local statistical variations to continually provide near optimum code efficiency when representing data without error. Demonstrated in several earlier space applications, these techniques are the basis of initial NASA data compression standards specifications. Since the techniques clearly apply to most NASA science data, NASA invested in the development of both hardware and software implementations for general use. This investment includes high-speed single-chip very large scale integration (VLSI) coding and decoding modules as well as machine-transferrable software routines. The hardware chips were tested in the laboratory at data rates as high as 700 Mbits/s. A coding module's definition includes a predictive preprocessing stage and a powerful adaptive coding stage. The function of the preprocessor is to optimally process incoming data into a standard form data source that the second stage can handle.The built-in preprocessor of the VLSI coder chips is ideal for high-speed sampled data applications such as imaging and high-quality audio, but additionally, the second stage adaptive coder can be used separately with any source that can be externally preprocessed into the 'standard form'. This generic functionality assures that the applicability of these techniques and their recent high-speed implementations should be equally broad outside of NASA.

Rice, Robert F.↗

Efficient distributed continual learning for steering experiments in real-time

Deep learning has emerged as a powerful method for extracting valuable information from large volumes of data. However, when new training data arrives continuously (i.e., is not fully available from the beginning), incremental training suffers from catastrophic forgetting (i.e., new patterns are reinforced at the expense of previously acquired knowledge). Training from scratch each time new training data becomes available would result in extremely long training times and massive data accumulation. Rehearsal-based continual learning has shown promise for addressing the catastrophic forgetting challenge, but research to date has not addressed performance and scalability. To fill this gap, we propose an approach based on a distributed rehearsal buffer that efficiently complements data-parallel training on multiple GPUs to achieve high accuracy, short runtime, and scalability. It leverages a set of buffers (local to each GPU) and uses several asynchronous techniques for updating these local buffers in an embarrassingly parallel fashion, all while handling the communication overheads necessary to augment input minibatches using unbiased, global sampling. We further propose a generalization of rehearsal buffers to support both classification and generative learning tasks, as well as more advanced rehearsal strategies (notably Dark Experience Replay, leveraging knowledge distillation). We illustrate this approach with a real-life HPC streaming application from the domain of ptychographic image reconstruction. Furthermore, we run extensive experiments on up to 128 GPUs of the ThetaGPU supercomputer to compare our approach with baselines representative of training-from-scratch (the upper bound in terms of accuracy) and incremental training (the lower bound). Results show that rehearsal-based continual learning achieves a top-5 validation accuracy close to the upper bound, while simultaneously exhibiting a runtime close to the lower bound.

Asynchronous data management↗

Multiresolution representation and numerical algorithms: A brief review

In this paper we review recent developments in techniques to represent data in terms of its local scale components. These techniques enable us to obtain data compression by eliminating scale-coefficients which are sufficiently small. This capability for data compression can be used to reduce the cost of many numerical solution algorithms by either applying it to the numerical solution operator in order to get an approximate sparse representation, or by applying it to the numerical solution itself in order to reduce the number of quantities that need to be computed.

Harten, Amiram↗

Statistical Challenges in Modern Astronomy II

Wavelets are the central idea of a broad framework for thinking about displaying, and analyzing data - not just a new specialized technique. They are localized basis functions that provide an extremely flexible and efficient representation of time series. Current developments in the theory and application of wavelets are yielding powerful multiresolution techniques for the analysis of time series and image data. Wavelet methods can effect noise removal. characterization of stochastic behavior, depiction of power spectrum time-variations, and data compression - for time series data, image data, and data of higher dimensions. I review published applications of wavelets in astronomy.

Scargle, Jeffrey D.↗

X-Ray And Acoustic Measurements Yield Stiffnesses

Analytical technique combines ultrasonic scanning measurements of local velocity of sound in specimen of material with x-ray computed tomographic measurements of local mass density to compute local stiffness of material. Stiffnesses at various locations in specimen then used in finite-element mathematical model of elastic behavior of specimen to compute local stresses, local strains, and overall deformations. Technique enhances value of quantitative nondestructive x-ray and ultrasonic measurements. Especially useful in characterization of carbon/carbon composites and other advanced materials not homogeneous and for which customary simplifying assumption of constant density and/or constant stiffness not valid.

Madaras, Eric Irvine↗

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

A relative performance analysis of atmospheric Laser Doppler Velocimeter methods.

Evaluation of the effectiveness of atmospheric applications of a Laser Doppler Velocimeter (LDV) at a wavelength of about 0.5 micrometer in conjunction with dual scatter LDV illuminating techniques, or at a wavelength of 10.6 micrometer with local oscillator LDV illuminating techniques. Equations and examples are given to provide a quantitative basis for LDV system selection and performance criteria in atmospheric research. The comparative study shows that specific ranges and conditions exist where performance of one of the methods is superior to that of the other. It is also pointed out that great care must be exercised in choosing system parameters that optimize a particular LDV designed for atmospheric applications.

Farmer, W. M.↗

Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

Shen, Han-Wei↗

GOME Total Ozone and Calibration Error Derived Usign Version 8 TOMS Algorithm

The Global Ozone Monitoring Experiment (GOME) is a hyper-spectral satellite instrument measuring the ultraviolet backscatter at relatively high spectral resolution. GOME radiances have been slit averaged to emulate measurements of the Total Ozone Mapping Spectrometer (TOMS) made at discrete wavelengths and processed using the new TOMS Version 8 Ozone Algorithm. Compared to Differential Optical Absorption Spectroscopy (DOAS) techniques based on local structure in the Huggins Bands, the TOMS uses differential absorption between a pair of wavelengths including the local stiucture as well as the background continuum. This makes the TOMS Algorithm more sensitive to ozone, but it also makes the algorithm more sensitive to instrument calibration errors. While calibration adjustments are not needed for the fitting techniques like the DOAS employed in GOME algorithms, some adjustment is necessary when applying the TOMS Algorithm to GOME. Using spectral discrimination at near ultraviolet wavelength channels unabsorbed by ozone, the GOME wavelength dependent calibration drift is estimated and then checked using pair justification. In addition, the day one calibration offset is estimated based on the residuals of the Version 8 TOMS Algorithm. The estimated drift in the 2b detector of GOME is small through the first four years and then increases rapidly to +5% in normalized radiance at 331 nm relative to 385 nm by mid 2000. The lb detector appears to be quite well behaved throughout this time period.

Gleason, J.↗

Measurements of the boundary layer and near wake of a supercritical airfoil at cruise conditions

The flow behavior within the upper-surface boundary layer and near wake of a supercritical airfoil operating at cruise conditions is discussed. Experimental results obtained from wind-tunnel tests are presented which provide a more detailed description of the flow in these regions than was previously available. Mean streamwise velocity profiles measured by pitot-pressure-probe and laser-velocimeter techniques were found to be in excellent agreement. Other mean-flow properties obtained by the laser-velocimeter technique were the local flow angles in the viscous layers and the static pressures at the edges of the boundary layer and wake. The data set also includes measurements of the turbulence intensity and turbulent Reynolds-stress distributions as obtained by the laser-velocimeter technique. To assess the effects of the shock wave, a less extensive set of measurements was realized at a subcritical test condition. The two test conditions (Mach number at free-stream conditions = 0.72, airfoil section lift coefficient = 0.76 and Mach number of free-stream conditions = 0.5, airfoil section lift coefficient = 0.75) provide a good test for state-of-the-art prediction methods because the upper-surface-boundary layer is separated just upstream of the trailing edge in both cases.

Johnson, D. A.↗

Imaging local discharge cascades for correlated electrons in WS 2 /WSe 2 moiré superlattices

Transition metal dichalcogenide moiré heterostructures provide an ideal platform to explore the extended Hubbard model, where long-range Coulomb interactions play a critical role in determining strongly correlated electron states. This has led to experimental observations of Mott insulator states at half filling as well as a variety of extended Wigner crystal states at different fractional fillings. However, a microscopic understanding of these emerging quantum phases is still lacking. Here we describe a scanning tunnelling microscopy (STM) technique for the local sensing and manipulation of correlated electrons in a gated WS 2 /WSe 2 moiré superlattice, which enables the experimental extraction of fundamental extended Hubbard model parameters. We demonstrate that the charge state of the local moiré sites can be imaged by their influence on the STM tunnelling current. In addition to imaging, we are also able to manipulate the charge state of correlated electrons. When we ramp the bias on the STM tip, there is a local discharge cascade of correlated electrons in the moiré superlattice, which allows us to estimate the nearest-neighbour Coulomb interaction. Two-dimensional mapping of the moiré electron charge states also enables us to determine the on-site energy fluctuations at different moiré sites. Furthermore, our technique should be broadly applicable to many semiconductor moiré systems, offering a powerful tool for the microscopic characterization and control of strongly correlated states in moiré superlattices.

36 MATERIALS SCIENCE↗

A Robust Locally Preconditioned Semi-Coarsening Multigrid Algorithm for the 2-D Navier-Stokes Equations

The goal of this thesis is to develop an efficient and robust locally preconditioned semi-coarsening multigrid algorithm for the two-dimensional Navier-Stokes equations. This thesis examines the performance of the multigrid algorithm with local preconditioning for an upwind-discretization of the Navier-Stokes equations. A block Jacobi iterative scheme is used because of its high frequency error mode damping ability. At low Mach numbers, the performance of a flux preconditioner is investigated. The flux preconditioner utilizes a new limiting technique based on local information that was developed by Siu. Full-coarsening and-semi-coarsening are examined as well as the multigrid V-cycle and full multigrid. The numerical tests were performed on a NACA 0012 airfoil at a range of Mach numbers. The tests show that semi-coarsening with flux preconditioning is the most efficient and robust combination of coarsening strategy, and iterative scheme - especially at low Mach numbers.

Cain, Michael D.↗

On the local measurement of electric currents and magnetic fields using Thomson scattering in Weibel-unstable plasmas

Here, we demonstrate the capability of the Thomson Scattering (TS) diagnostic to measure locally the microscopic electron and ion currents in counter-streaming plasmas unstable to the Weibel or current-filamentation instability. Synthetic TS spectra are calculated with particle distribution functions obtained from particle-in-cell simulations and used to accurately reproduce the simulated currents. We show that this technique allows accurate local measurements of the magnetic field, thus opening the way for the complete experimental characterization of the growth rate, saturation, and nonlinear dynamics of electromagnetic instabilities in plasmas. We illustrate the application of this diagnostic to experimental TS data, which yields local measurements of the magnetic field in Weibel-unstable plasmas and indicates that the magnetic energy density reaches ~1% of the kinetic energy density of the flows, in agreement with previous numerical studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Surface tension-driven convection phenomena

The techniques for measuring surface tension-driven flow are reported. In addition to the fairly standard crossed beam LDV method, methods using ripplon scattering which do not require seeding of the fluid were developed. These methods can be used to determine thermophysical properties of the surface, such as surface tension, viscosity, and local temperature. This technique was utilized to observe the change in surface tension associated with the nematic to isotropic phase transition of para-azoxydianisole at 134 C. The ripplon scattering methods become difficult for surface velocities below 1 mm/sec because of the overlapping spectra. Careful analysis procedures could extend this to smaller flows, but the more conventional LDV techniques with seeded flows are the method of choice for slow flows.

Mann, J. A., Jr.↗

Improvement of modal scaling factors using mass additive technique

A general investigation into the improvement of modal scaling factors of an experimental modal model using additive technique is discussed. Data base required by the proposed method consists of an experimental modal model (a set of complex eigenvalues and eigenvectors) of the original structure and a corresponding set of complex eigenvalues of the mass-added structure. Three analytical methods,i.e., first order and second order perturbation methods, and local eigenvalue modification technique, are proposed to predict the improved modal scaling factors. Difficulties encountered in scaling closely spaced modes are discussed. Methods to compute the necessary rotational modal vectors at the mass additive points are also proposed to increase the accuracy of the analytical prediction.

Zhang, Qiang↗