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Results for “tensor completion”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2024

The Average Spectrum Norm and Near-Optimal Tensor Completion

We propose the average spectrum norm to study the minimum number of measurements required to approximate a multidimensional array (i.e., sample complexity) via low-rank tensor recovery. Our focus is on the tensor completion problem, where the aim is to estimate a multiway array using a subset of tensor entries corrupted by noise. Our average spectrum norm-based analysis provides near-optimal sample complexities, exhibiting dependence on the ambient dimensions and rank that do not suffer from exponential scaling as the order increases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A General Spatiotemporal Imputation Framework for Missing Sensor Data

Many applications from precision agriculture, environmental monitoring and transportation networks rely on data collected across space and time over a large geographic area. Missing data poses a significant challenge for any data-driven inference and control tasks. Data imputation or the estimation of missing data can help fill these gaps by utilizing inherent spatial relationships and temporal patterns. A variety of spatiotemporal imputation models have been developed to address missing data in spatiotemporal datasets. However, these classical methods rely on the assumption that the underlying data follows a smooth trend and fail to provide accurate estimates when there is a large number of missing points in the data. Even though there are machine learning driven tensor completion approaches such as convolutional neural network based tensor completion (CoSTCo) that capture the non-linear relationships in the dataset, the transductive nature makes the algorithm less scalable. Thus, existing approaches for estimating the missing information do not effectively capture all dimensions of the spatiotemporal data structure, resulting in erroneous predictions and poor performance. The main contributions of this paper are: (1) We propose a novel inductive framework (G-LSTM) for missing data imputation that integrates a graph neural network with LSTMs to effectively capture both spatial and temporal dependencies. (2) Experimental results on a traffic dataset demonstrate that the proposed GNN integrated with an LSTM framework achieves improved imputation and maintains steady performance even when there are extreme missing conditions in comparison with the state-of-the-art imputation framework (i.e, CoSTCo). (3) The simulation results on a traffic network show up to 69% reduction in mean absolute error and 61% reduction in root mean square error when compared to CoSTCo.

Tharzeen, Aabila↗
DOE OSTI2023

Zero-truncated Poisson regression for sparse multiway count data corrupted by false zeros

Abstract We propose a novel statistical inference methodology for multiway count data that is corrupted by false zeros that are indistinguishable from true zero counts. Our approach consists of zero-truncating the Poisson distribution to neglect all zero values. This simple truncated approach dispenses with the need to distinguish between true and false zero counts and reduces the amount of data to be processed. Inference is accomplished via tensor completion that imposes low-rank tensor structure on the Poisson parameter space. Our main result shows that an $N$-way rank-$R$ parametric tensor $\boldsymbol{\mathscr{M}}\in (0,\infty )^{I\times \cdots \times I}$ generating Poisson observations can be accurately estimated by zero-truncated Poisson regression from approximately $IR^2\log _2^2(I)$ non-zero counts under the nonnegative canonical polyadic decomposition. Our result also quantifies the error made by zero-truncating the Poisson distribution when the parameter is uniformly bounded from below. Therefore, under a low-rank multiparameter model, we propose an implementable approach guaranteed to achieve accurate regression in under-determined scenarios with substantial corruption by false zeros. Several numerical experiments are presented to explore the theoretical results.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Visualizing second order tensor fields with hyperstreamlines

Hyperstreamlines are a generalization to second order tensor fields of the conventional streamlines used in vector field visualization. As opposed to point icons commonly used in visualizing tensor fields, hyperstreamlines form a continuous representation of the complete tensor information along a three-dimensional path. This technique is useful in visulaizing both symmetric and unsymmetric three-dimensional tensor data. Several examples of tensor field visualization in solid materials and fluid flows are provided.

Delmarcelle, Thierry↗
DOE OSTI2025

Second‐ and Third‐Order Elastic Constants of Inert and Energetic Molecular Crystals From Density Functional Theory

Complete tensors of the second- and third-order elastic constants of the organic molecular crystals acetaminophen, pentaerythritol tetranitrate (PETN), cyclotrimethylene trinitramine (RDX), cyclotetramethylene tetranitramine (HMX), 1,1-diamino-2,2-dinitroethylene (FOX-7), hexanitrohexaazaisowurtzitane (CL-20), and erythritol tetranitrate (ETN) have been calculated using dispersion-corrected density functional theory. The sets of second- and third-order elastic constants are expected to provide a more accurate and reliable description of the behavior of these materials under nonhydrostatic loads than pressure- and volume-dependent second-order elastic constants. The tensors of second-order constants have been compared with experimental data and/or other calculations when possible, and with the exception of results for CL-20 from Brillouin scattering experiments, we find good agreement. The calculated third-order elastic constants of PETN are in very good agreement with the subset of third-order constants derived from experimental wave speed measurements. The elastic anisotropies of the crystals have been estimated using the universal elastic anisotropy index, which shows that the crystals fall into three groups with low anisotropy (PETN, RDX, and CL-20), moderate anisotropy (acetaminophen, HMX, and ETN), and high elastic anisotropy (FOX-7).

36 MATERIALS SCIENCE↗
NASA NTRS1981

An objective method for determining the generalized transport tensor for two-dimensional Eulerian models

An objective method for deriving the components of a generalized transport tensor for a two-dimensional model is presented. Representative meridional and vertical velocities and thermodynamic scalars at a uniform grid are used to reduce the problem to the solution of two flux equations for two unknowns. One unknown is the stream-function, coefficient of an antisymmetric tensor, which corrects the Eulerian mean motions for Stokes drift; the other is a time constant, which converts the deviatory velocity tensor to a symmetric transport tensor. The complete asymmetric tensor, called a transport tensor, has a divergence which yields both advection and diffusion by the deviatory velocities. Advantages and disadvantages of Lagrangian and Eulerian averages are discussed, and meridional-vertical velocity correlations are provided.

Danielsen, E. F.↗
NASA NTRS1974

Cosmic-ray streaming perpendicular to the mean magnetic field

Starting from a quasi-linear approximation for the ensemble-averaged particle distribution function in a random magnetic field, the complete diffusion tensor is derived. This is done by assuming a simple form for the ensemble-averaged distribution function, explicitly retaining all components of the streaming flux. This derivation obtains the antisymmetric terms in a natural manner. The necessary dropping of higher-order terms gives a criterion for the lower-energy limit of validity of the perpendicular and antisymmetric diffusion coefficients. The limit for the assumed distribution function is about 0.8 GV rigidity in the interplanetary field near 1 AU.

Forman, M. A.↗
NASA NTRS1997

Dibromine Monoxide, Br2O: The Rotational Spectrum and Molecular Properties

The rotational spectra of (79)Br2O, (79)BrO(81)Br, and Br2O in their ground vibrational states as well as (79)BrO(81)Br in its v (sub 2) = 1 state have been studied in selected regions between 90 and 523 GHz. Transitions involving a large range of quantum numbers, 6 less than or equal to J less than or equal to 123 and 0 less than or equal to K (sub a) less than or equal to 12, have been observed permitting precise rotational and a large set of centrifugal distortion constants to be determined. All isotopic species as well as the excited state data were fit simultaneously. Ground-state effective and average structural parameters as well as an estimate of the equilibrium structure have been derived. The quartic distortion constants were used for a calculation of the harmonic force field. The complete quadrupole tensor has been determined. Its diagonalization reveals a largely covalent BrO bond with little pi-bonding. The derived properties of Br2O are compared with those of related compounds such as Cl2O, HOBR, and HOCl.

Mueller, Holger S. P.↗
NASA NTRS2001

High Temperature Elastic Properties of Single Crystal Mullite (Approximately 2.5Al2O3.SiO2) by Brillouin Spectroscopy

The complete elastic tensor of mullite has been determined by brillouin spectroscopy at room temperature and elevated temperatures up to 1200C. Equivalent, isotropic moduli (bulk, shear, and Young's) have been calculated. The room temperature values obtained using Voigt-Reuss-Hill averaging are: K(sub VRH) = 173.5 + 6.9 GPa, G(sub VRH) = 88.0 + 3.5 GPa, E(sub VRH) = 225.9 + 9.0 GPa. All moduli show relatively gradual decreases with temperature. The temperature derivatives obtained for the equivalent, isotropic moduli are: dK(sub VRH)/dT = - 17.5 + 2.5 MPa/deg. C, dG(sub VRH)/dT = -8.8 + 1.4 MPa/deg. C, dE(sub VRH)/dT = -22.6 + 2.8 MPa/deg C. Substantial differences between bulk properties calculated from the single crystal measurements in this study and the properties reported in the literature for polycrystalline sintered mullite are identified, indicating the importance of factors such as microstructure, intergranular phases, and composition to the elasticity of mullite ceramics.

Palko, James W.↗
DOE OSTI2025

Direct measurement of the quantum metric tensor in solids

The quantum metric tensor is a central geometric quantity in modern physics that is defined as the distance between nearby quantum states. Despite numerous studies highlighting its relevance to fundamental physical phenomena in solids, measuring the complete quantum metric tensors in real solid-state materials is challenging. In this work, we report a direct measurement of the full quantum metric tensors of Bloch electrons in solids using black phosphorus as a representative material. We extracted the momentum space distribution of the pseudospin texture of the valence band from the polarization dependence of angle-resolved photoemission spectroscopy measurement. Our approach is poised to advance our understanding of quantum geometric responses in a wide class of crystalline systems.

Kim, Sunje↗
NASA NTRS1991

Experimental investigation of turbulent flow through a circular-to-rectangular transition duct

Steady, incompressible, turbulent, swirl-free flow through a circular-to-rectangular transition duck was studied experimentally. The cross-sectional area remains the same at the exit as at the inlet, but varies through the transition section to a maximum value approximately 15 percent above the inlet value. The cross-sectional geometry everywhere along the duct is defined by the equation of a superellipse. Mean and turbulence data were accumulated utilizing pressure and hot-wire instrumentation at five stations along the test section. Data are presented for operating bulk Reynolds numbers of 88,000 and 390,000. Measured quantities include total and static pressure, the three components of the mean velocity vector, and the six components of the Reynolds stress tensor. In addition to the transition duct measurements, a hot-wire technique which relies on the sequential use of single rotatable normal and slant-wire probes was proposed. The technique is applicable for measurement of the total mean velocity vector and the complete Reynolds stress tensor when the primary flow is arbitrarily skewed relative to a plane which lies normal to the probe axis of rotation.

Davis, David O.↗
NASA NTRS1983

Single-wire swirl flow turbulence measurements

A six-orientation, single wire hot wire technique is used to investigate nonswirling and swirling nonreacting flow in an axisymmetric test section with expansion ratio (test section/inlet nozzle diameter) = 2, which may be equipped with a strong contraction nozzle of area ratio 4 at a contraction nozzle downstream distance/test section diameter value = 2. The flowfield contains corner and central recirculation zones typical of gas turbine and ramjet combustion chambers. Swirl may be imparted to the incoming flow by means of a variable angle vane swirler. The effect of swirl on time mean velocities and complete Reynolds stress tensor is investigated, and extensive results are given for swirl vane angles of zero (swirler removed), 38, 45, 60 and 70 deg. The data are being used to aid in the evolution of turbulence models for these complex flow situations. A directional sensitivity analysis is included, which determines the relative accuracy of the measurement technique to approach velocity orientation.

Lilley, D. G.↗
NASA NTRS1996

Development of the Tensoral Computer Language

The research scientist or engineer wishing to perform large scale simulations or to extract useful information from existing databases is required to have expertise in the details of the particular database, the numerical methods and the computer architecture to be used. This poses a significant practical barrier to the use of simulation data. The goal of this research was to develop a high-level computer language called Tensoral, designed to remove this barrier. The Tensoral language provides a framework in which efficient generic data manipulations can be easily coded and implemented. First of all, Tensoral is general. The fundamental objects in Tensoral represent tensor fields and the operators that act on them. The numerical implementation of these tensors and operators is completely and flexibly programmable. New mathematical constructs and operators can be easily added to the Tensoral system. Tensoral is compatible with existing languages. Tensoral tensor operations co-exist in a natural way with a host language, which may be any sufficiently powerful computer language such as Fortran, C, or Vectoral. Tensoral is very-high-level. Tensor operations in Tensoral typically act on entire databases (i.e., arrays) at one time and may, therefore, correspond to many lines of code in a conventional language. Tensoral is efficient. Tensoral is a compiled language. Database manipulations are simplified optimized and scheduled by the compiler eventually resulting in efficient machine code to implement them.

Ferziger, Joel↗