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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Adjusting inhomogeneous daily temperature variability using wavelet analysis

A wavelet-analysis-based homogenization method (WHM) is developed for detecting and adjusting biases of variability in a daily climate observation series, which are influential in the estimation of climate extremes and relevant trends in the time series. WHM is applied to the Central England daily mean temperature series (CET, 1772–2010) and the daily mean temperature series at Henan station in mountainous western China (HNT, 1960–2008) in order to demonstrate the usefulness of the new technique. The changes of methods for calculating daily mean temperature for CET in 1878 caused significantly reduced daily variability (DV) in the subsequent sub-series of CET. The relocation of the Chinese station in 1981 to a higher mountainous site resulted in not only enhanced DV but also in weather (weekly) time-scale variability (WV) in the subsequent sub-series of HNT. The adjustments based on WHM in the present cases improve the estimates of the long-term trends of climate extremes such as hot days, cold days, heat waves, and cold surges. A few widely applied methods of homogenization such as multiple analysis of series for homogenization (MASH), higher-order moment (HOM), RHtestsV3 with quantile-matching (QM) adjustments and two-phase regression (TPR) are also applied to HNT for comparison. TPR is not aimed at improving the homogeneity of variability in the time series; MASH does not improve daily variability either; HOM improves it in a small way; and with RHtestsV3 with QM adjustments it is considerably improved, but biases remain. In contrast, WHM improves the homogeneity of the short-term variability in the time series, resulting in reasonable assessments of climate extremes and trends in the daily observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Interactive volumetric segmentation for textile micro-tomography data using wavelets and nonlocal means

This work addresses segmentation of volumetric images of woven carbon fiber textiles from micro-tomography data. We propose a semi-supervised algorithm to classify carbon fibers that requires sparse input as opposed to completely labeled images. The main contributions are: (a) design of effective discriminative classifiers, for three-dimensional textile samples, trained on wavelet features for segmentation; (b) coupling of previous step with nonlocal means as simple, efficient alternative to the Potts model; and (c) demonstration of reuse of classifier to diverse samples containing similar content. We evaluate our work by curating test sets of voxels in the absence of a complete ground truth mask. The algorithm obtains an average 0.95 F1 score on test sets and average F1 score of 0.93 on new samples. Finally, we conclude with discussion of failure cases and propose future directions toward analysis of spatiotemporal high-resolution micro-tomography images.

3D image processing↗
DOE OSTI2020

Protection Scheme for Multiterminal HVDC System Based on Wavelet Transform Modulus Maxima

Fault protection is a major issue in the development of multiterminal high‐voltage direct current (HVDC) system based on voltage‐source converter. Owing to the rapid increase in fault current under DC faults, protection requires a fast fault detection method to isolate the fault current. However, the selectivity and reliability of the fast protection scheme should be primarily guaranteed. Therefore, a new protection strategy based on modulus maximum under wavelet transform is proposed in this paper. Fault detection and discrimination are achieved using single‐end signals of fault current. The external and internal faults can be discriminated via local information. The reliability and robustness of the proposed scheme against potential factors are verified. Numerous simulation cases are performed in PSCAD/EMTDC under different fault scenarios, and signal data are analyzed in MATLAB to demonstrate the effectiveness of the proposed fault protection scheme. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Huai, Qing↗
DOE OSTI2024

Entanglement Renormalization for Quantum Field Theories with Discrete Wavelet Transforms

We propose an adaptation of Entanglement Renormalization for quantum field theories that, through the use of discrete wavelet transforms, strongly parallels the tensor network architecture of the Multiscale Entanglement Renormalization Ansatz (a.k.a. MERA). Our approach, called wMERA, has several advantages of over previous attempts to adapt MERA to continuum systems. In particular, (i) wMERA is formulated directly in position space, hence preserving the quasi-locality and sparsity of entanglers; and (ii) it enables a built-in RG flow in the implementation of real-time evolution and in computations of correlation functions, which is key for efficient numerical implementations. As examples, we describe in detail two concrete implementations of our wMERA algorithm for free scalar and fermionic theories in (1+1) spacetime dimensions. Possible avenues for constructing wMERAs for interacting field theories are also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Haar-Like Wavelets on Hierarchical Trees

Here, discrete wavelet methods, originally formulated in the setting of regularly sampled signals, can be adapted to data defined on a point cloud if some multiresolution structure is imposed on the cloud. A wide variety of hierarchical clustering algorithms can be used for this purpose, and the multiresolution structure obtained can be encoded by a hierarchical tree of subsets of the cloud. Prior work introduced the use of Haar-like bases defined with respect to such trees for approximation and learning tasks on unstructured data. This paper builds on that work in two directions. First, we present an algorithm for constructing Haar-like bases on general discrete hierarchical trees. Second, with an eye towards data compression, we present thresholding techniques for data defined on a point cloud with error controlled in the $L$ $\infty$ norm and in a Hölder-type norm. In a concluding trio of numerical examples, we apply our methods to compress a point cloud dataset, study the tightness of the $L$ $\infty$ error bound, and use thresholding to identify MNIST classifiers with good generalizability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Integer Realization of Spline-Wavelet Decomposition

We consider integer spline-wavelet algorithms for processing digital flows. We obtain integer variants of the decomposition and reconstruction formulas and give an example demonstrating the practical realizability of the proposed algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Adaptive Wavelet Decomposition of Matrix Flows

Adaptive algorithms for constructing spline-wavelet decompositions of matrix flows from a linear space of matrices over a normed field are presented. The algorithms suggested provides for an a priori prescribed estimate of the deviation of the basic flow from the initial one. Comparative bounds of the volumes of data in the basic flow for various irregularity characteristics of the initial flow are obtained in the cases of pseudo-equidistant and adaptive grids. Limit characteristics of the above-mentioned volumes are given in the cases where the initial flow is generated by differentiable functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On Biorthogonal p-Adic Wavelet Bases

Dual p-adic multiresolution analyses (MRAs) generated by scaling test functions are studied. It is proved that if two MRAs are dual, then each of them is the Haar MRA. A characterization of all biorthogonal wavelet systems associated with the Haar MRA is given for the case p = 2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The use of Jacobi wavelets for constrained approximation of rational Bézier curves

This paper presents an efficient method to solve the approximation problem of the rational Bézier curve by continuous piecewise polynomial curve in L{sub 2}-norm. For this purpose, extended Jacobi wavelets together with the Gauss–Jacobi quadrature rules are employed. The proposed technique has some advantages such as: simplicity, high accuracy and fast computation. Also, the method in the paper performs multi-degree reduction at one time and does not need the stepwise computing. Several examples are given to illustrate the effectiveness of the algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A semi-discrete scheme for solving fourth-order partial integro-differential equation with a weakly singular kernel using Legendre wavelets method

In this paper, a semi-discrete scheme is presented for solving fourth-order partial integro-differential equations with a weakly singular kernel. The second-order backward difference formula is used to discretize the temporal derivatives. After discretizing the temporal derivatives, the considered problems are converted into a set of ordinary differential equations which are solved by using Legendre wavelets collocation method. The stability and convergence properties related to the time discretization are discussed and theoretically proven. Several numerical examples are included to demonstrate the accuracy and efficiency of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Identifying geochemical hot moments and their controls on a contaminated river floodplain system using wavelet and entropy approaches

Geochemical hot moments are defined here as short periods of time that are associated with disproportionally high levels of concentrations (biogeochemically-driven or transport-related) relative to longer intervening time periods. We used entropy and wavelet techniques to identify temporal variability in geochemical constituents and their controls along three transects within a contaminated floodplain system near Rifle CO. Results indicated that transport-dominated hot moments drove overall geochemical processing in the contaminated groundwater and seep zones. These hot moments were associated with seasonal hydrologic variability (~4 months) in the contaminated aquifer and with annual hydrologic cycle and residence times in the seep zone. Hot moments associated with a naturally reduced zone within the aquifer were found to be biogeochemically-driven, with a different dominant frequency (~3 months) and no correlation to hydrologic or weather variations, in contrast to what is observed in other regions of the floodplain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A space-time smooth artificial viscosity method with wavelet noise indicator and shock collision scheme, Part 2: The 2-D case

This is the second part to our companion paper. Herein, we generalize to two space dimensions the C-method developed in for adding localized, space-time smooth artificial viscosity to nonlinear systems of conservation laws that propagate shock waves, rarefaction waves, and contact discontinuities. For gas dynamics, the C-method couples the Euler equations to scalar reaction-diffusion equations, which we call C-equations, whose solutions serve as space-time smooth artificial viscosity indicators for shocks and contacts. We develop a high-order numerical algorithm for gas dynamics in 2-D which can accurately simulate the Rayleigh-Taylor (RT) instability with Kelvin-Helmholtz (KH) roll-up of the contact discontinuity, as well as shock collision and bounce-back. Solutions to our C-equations not only indicate the location of the shocks and contacts, but also track the geometry of the evolving fronts. This allows us to implement both directionally isotropic and anisotropic artificial viscosity schemes, the latter adding diffusion only in directions tangential to the evolving front. We additionally produce a novel shock collision indicator function, which naturally activates during shock collision, and then smoothly deactivates. Moreover, we implement a high-frequency 2-D wavelet-based noise detector together with an efficient and localized noise removal algorithm. To test the methodology, we use a highly simplified WENO-based discretization scheme. We provide numerical results for some classical 2-D test problems, including the RT problem, the Noh problem, a circular explosion problem from the Liska & Wendroff [13] review paper, the Sedov blast wave problem, the double Mach 10 reflection test, and a shock-wall collision problem. In particular, we show that our artificial viscosity method can eliminate the wall-heating phenomenon for the Noh problem, and thereby produce an accurate, non-oscillatory solution, even though our simplified WENO-type scheme fails to run for this problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A space-time smooth artificial viscosity method with wavelet noise indicator and shock collision scheme, Part 1: The 1-D case

In this first part of two papers, we extend the C-method developed in for adding localized, space-time smooth artificial viscosity to nonlinear systems of conservation laws that propagate shock waves, rarefaction waves, and contact discontinuities in one space dimension. For gas dynamics, the C-method couples the Euler equations to a scalar reaction-diffusion equation, whose solution C serves as a space-time smooth artificial viscosity indicator. The purpose of this paper is the development of a high-order numerical algorithm for shock-wall collision and bounce-back. Specifically, we generalize the original C-method by adding a new collision indicator, which naturally activates during shock-wall collision. Additionally, we implement a new high-frequency wavelet-based noise detector together with an efficient and localized noise removal algorithm. To test the methodology, we use a highly simplified WENO-based discretization scheme. We show that our scheme improves the order of accuracy of our WENO algorithm, handles extremely strong discontinuities (ranging up to nine orders of magnitude), allows for shock collision and bounce back, and removes high frequency noise. The causes of the well-known “wall heating” phenomenon are discussed, and we demonstrate that this particular pathology can be effectively treated in the framework of the C-method. This method is generalized to two space dimensions in the second part of this work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Structural Differentiation between Layered Single (Ni) and Double Metal Hydroxides (Ni–Al LDHs) Using Wavelet Transformation

Layered double hydroxides (LDHs) are anionic clays important in disciplines such as environmental chemistry, geochemistry, and materials science. Developments in signal processing of extended X-ray absorption fine structure (EXAFS) data, such as wavelet transformation (WT), have been used to identify transition metals and Al present in the hydroxide sheets of LDHs. The WT plots of LDHs should be distinct from those of isostructural single metal hydroxides. However, no direct comparison of these minerals appears in the literature using WT. This work systematically analyzes a suite of Ni-rich mineral standards, including Ni–Al LDHs, single metal Ni hydroxides, and Ni-rich silicates using WT. The results illustrate that the WT plots for α-Ni(OH)2 and Ni–Al LDHs are often indistinguishable from each other, with similar two-component plots for the different mineral types. This demonstrates that the WT of the first metal shell often cannot be used to differentiate an LDH from a single metal hydroxide. Interlayer anions adsorbed to the hydroxide sheet of α-Ni(OH)2 affect the EXAFS spectra and are not visible in the FT but are clearly resolved and discrete in the WT.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Wavelet Analysis of Properties of Marine Boundary Layer Mesoscale Cells Observed From AMSR–E

Marine boundary layer clouds tend to organize into closed or open mesoscale cellular convection (MCC). Here, two-dimensional wavelet analysis is applied for the first time to passive microwave retrievals of cloud water path (CWP), water vapor path (WVP), and rain rate (RR) from Advanced Microwave Scanning Radiometer for Earth Observing System in 2008 over the Northeast and Southeast Pacific, and the Southeast Atlantic subtropical stratocumulus to cumulus transition regions. The (co-)variability between CWP, WVP, and RR in 160 × 160 km 2 analysis boxes is partitioned between four mesoscale wavelength octaves (20, 40, 80, and 160 km). The cell scale is identified as the wavelength of the peak CWP variance. Together with a machine-learning classification of cell type, this allows the statistical characteristics of open and closed MCC of various scales, and its relation to WVP, RR, and potential environmental controlling factors to be analyzed across a very large set of cases. Here, the results show that the cell wavelength is most commonly 40–80 km. Cell-scale CWP perturbations are good predictors of the WVP and RR perturbations. For cells larger than 20 km, there is no obvious dependence of cell scale on the environmental controlling factors tested, suggesting that the cell scale may depend more on its historical evolution than the current environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗
DOE OSTI2011

Intermittency and geometrical statistics of three-dimensional homogeneous magnetohydrodynamic turbulence: A wavelet viewpoint

Scale-dependent and geometrical statistics of three-dimensional incompressible homogeneous magnetohydrodynamic turbulence without mean magnetic field are examined by means of the orthogonal wavelet decomposition. The flow is computed by direct numerical simulation with a Fourier spectral method at resolution 512{sup 3} and a unit magnetic Prandtl number. Scale-dependent second and higher order statistics of the velocity and magnetic fields allow to quantify their intermittency in terms of spatial fluctuations of the energy spectra, the flatness, and the probability distribution functions at different scales. Different scale-dependent relative helicities, e.g., kinetic, cross, and magnetic relative helicities, yield geometrical information on alignment between the different scale-dependent fields. At each scale, the alignment between the velocity and magnetic field is found to be more pronounced than the other alignments considered here, i.e., the scale-dependent alignment between the velocity and vorticity, the scale-dependent alignment between the magnetic field and its vector potential, and the scale-dependent alignment between the magnetic field and the current density. Finally, statistical scale-dependent analyses of both Eulerian and Lagrangian accelerations and the corresponding time-derivatives of the magnetic field are performed. It is found that the Lagrangian acceleration does not exhibit substantially stronger intermittency compared to the Eulerian acceleration, in contrast to hydrodynamic turbulence where the Lagrangian acceleration shows much stronger intermittency than the Eulerian acceleration. The Eulerian time-derivative of the magnetic field is more intermittent than the Lagrangian time-derivative of the magnetic field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

A wavelet analysis for the X-ray absorption spectra of molecules

We present a Wavelet transform analysis for the X-ray absorption spectra of molecules. In contrast to the traditionally used Fourier transform approach, this analysis yields a 2D correlation plot in both R- and k-space. As a consequence, it is possible to distinguish between different scattering pathways at the same distance from the absorbing atom and between the contributions of single and multiple scattering events, making an unambiguous assignment of the fine structure oscillations for complex systems possible. We apply this to two previously studied transition metal complexes, namely iron hexacyanide in both its ferric and ferrous form, and a rhenium diimine complex, [ReX(CO){sub 3}(bpy)], where X = Br, Cl, or ethyl pyridine (Etpy). Our results demonstrate the potential advantages of using this approach and they highlight the importance of multiple scattering, and specifically the focusing phenomenon to the extended X-ray absorption fine structure (EXAFS) spectra of these complexes. We also shed light on the low sensitivity of the EXAFS spectrum to the Re-X scattering pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗