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Results for “Singular value decomposition”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Eigenvector derivatives of repeated eigenvalues using singular value decomposition

An explicit formula is obtained for the first-order eigenvector derivative that corresponds to the eigenvector of a repeated eigenvalue, in the case of the nonself-adjoint eigenvalue problem. This method applies to the class of nondefective problems whose first eigenvalue derivatives of the repeated eigenvalues are distinct. A singular-value decomposition approach is used to compute four requisite bases for eigenspaces, as well as to keep track of the dimensions of state variables and the conditioning of the state equations.

Lim, Kyong B.↗
DOE OSTI2014

Signal evaluations using singular value decomposition for Thomson scattering diagnostics

This paper provides a novel method for evaluating signal intensities in incoherent Thomson scattering diagnostics. A double-pass Thomson scattering system, where a laser passes through the plasma twice, generates two scattering pulses from the plasma. Evaluations of the signal intensities in the spectrometer are sometimes difficult due to noise and stray light. We apply the singular value decomposition method to Thomson scattering data with strong noise components. Results show that the average accuracy of the measured electron temperature (T{sub e}) is superior to that of temperature obtained using a low-pass filter (<20 MHz) or without any filters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Assaying Used Nuclear Fuel Assemblies Using Lead Slowing-Down Spectroscopy and Singular Value Decomposition

This study investigates the use of a Lead Slowing-Down Spectrometer (LSDS) for the direct and independent measurement of fissile isotopes in light-water nuclear reactor fuel assemblies. The current study applies MCNPX, a Monte Carlo radiation transport code, to simulate the measurement of the assay of the used nuclear fuel assemblies in the LSDS. An empirical model has been developed based on the calibration of the LSDS to responses generated from the simulated assay of six well-characterized fuel assemblies. The effects of self-shielding are taken into account by using empirical basis vectors calculated from the singular value decomposition (SVD) of a matrix containing the self-shielding functions from the assay of assemblies in the calibration set. The performance of the empirical algorithm was tested on version 1 of the Next-Generation Safeguards Initiative (NGSI) used fuel library consisting of 64 assemblies, as well as a set of 27 diversion assemblies, both of which were developed by Los Alamos National Laboratory. The potential for direct and independent assay of the sum of the masses of Pu-239 and Pu-241 to within 2%, on average, has been demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Quantum Solver Using Singular Value Decomposition for Computational Fluid Dynamics

Numerical solutions for fluid flow problems are challenging and have been focus of Computational Fluid Dynamics (CFD) research for past several decades. The advent of quantum computing promises exponential speedup in comparison to existing classical methods and alleviate computational constraints posed by CFD problems. Although solutions for most problems of interest in fluid dynamics using quantum computing are distant, recent advances in algorithms, software and hardware provide a path towards realizing this goal. Quantum linear solver algorithms (QLSA) such as Harrow–Hassidim–Lloyd (HHL) and Variational Quantum Linear Solver (VQLS) have been successfully implemented to solve for canonical problems such as Hele-Shaw flow. However, these algorithms still suffer to scale and address problems with ill-conditioned Jacobians. In the current paper, we alleviate these restrictions with a new quantum solver based on Singular Value Decomposition (SVD) and simulate flow past a 2D cylinder. The fidelity of the SVD based quantum solver in predicting the flow past 2D cylinder is computed along with an assessment of errors. Classical and quantum solutions for the flow are compared for different resolutions. Finally, we discuss variation in the solutions based on number of shots used.

Gottiparthi, Kalyan [ORNL] (ORCID:0000000213540255↗
NASA NTRS1988

Efficient load measurements using singular value decomposition

Various basic research was performed on efficient load measurement estimation techniques for aircraft structure analysis. An overview is presented of the load measurement problem. Two basic equivalent approaches to load measurement evaluations were considered. Under approach 1, the load values are modeled as depending linearly on the measured values. Under approach 2, the measured values depend linearly on the load values. By using the modern Singular Value Decomposition method, it was shown that under all conditions of the number of loads and number of gages, approach 1 is equivalent to approach 2. By using the conventional normal equation (linear regression) approach, approach 1 is only valid when the number of loads is equal to or greater than the number of gages, while approach 2 is the reverse. Furthermore, except for the case of the number of loads equals the number of gages, the load prediction formulas under the two approaches are not equivalent.

Yao, Kung↗
NASA NTRS1989

A multi-point force appropriation method based upon a singular value decomposition approach

Force appropriation methods aim to provide an estimate for the force pattern required to excite a 'pure' normal mode in a vibration test where multiple exciters are available. In this paper, a new method based upon a Singular Value Decompositon approach is presented. The appropriated force vector which minimizes the in-plane response components while maximizing the required quadrature components is found, subject to a fixed force norm. The method can accommodate more transducers than exciters and also more exciters than effective degrees of freedom. The method is demonstrated upon a six degree of freedom theoretical model and it is shown that an estimate for the effective degrees of freedom can be obtained.

Juang, Jer-Nan↗
DOE OSTI2019

Automatic Partition of Orbital Spaces Based on Singular Value Decomposition in the Context of Embedding Theories

Here, we present a simple approach for orbital space partitioning to be employed in the projection-based embedding theory developed by Goodpaster and co-workers [Manby et al. J. Chem. Theory Comput. 2012, 8, 2564]. Once the atoms are assigned to the desired subspaces, the molecular orbitals are projected onto the atomic orbitals centered on active atoms and then singular value decomposed. The right singular vectors are used to rotate the initial molecular orbitals, taking the largest gap in the singular values spectrum to define the most suitable partition of the occupied orbital space. This scheme is free from numerical parameters, contrary to the Mulliken charge threshold or the completeness criterion previously used. The performance of this new prescription is assessed in a test set of several distinct reactions, the deprotonation of decanoic acid, the Diels-Alder reaction of 1,3-butadiene and octadecanonaene, the torsional potential of a retinal derivative, and the critical points along the reaction coordinate of an instance of the Menshutkin S N2 reaction inside a carbon nanotube.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Regularizing the satellite temperature-retrieval problem through singular-value decomposition of the radiative transfer physics

A new technique is derived for retrieving atmospheric temperature profiles from satellite-measured spectral radiance that appears, in first tests, to effectively circumvent certain difficulties of other well-known and implemented techniques. This method provides an effective manner to avoid numerical instability without having to force the algorithm toward adherence to a priori statistics not dependent on the radiance measurements. This provides the opportunity to obtain more information from satellite sounding instruments, without encountering instabilities owing to overlapping weighting functions.

Thompson, Owen E.↗
NASA NTRS2003

Evaluation of a Singular Value Decomposition Approach for Impact Dynamic Data Correlation

Impact dynamic tests are used in the automobile and aircraft industries to assess survivability of occupants during crash, to assert adequacy of the design, and to gain federal certification. Although there is no substitute for experimental tests, analytical models are often developed and used to study alternate test conditions, to conduct trade-off studies, and to improve designs. To validate results from analytical predictions, test and analysis results must be compared to determine the model adequacy. The mathematical approach evaluated in this paper decomposes observed time responses into dominant deformation shapes and their corresponding contribution to the measured response. To correlate results, orthogonality of test and analysis shapes is used as a criterion. Data from an impact test of a composite fuselage is used and compared to finite element predictions. In this example, the impact response was decomposed into multiple shapes but only two dominant shapes explained over 85% of the measured response

Horta, Lucas G.↗
NASA NTRS1991

Applications of singular value analysis and partial-step algorithm for nonlinear orbit determination

An adaptive method in which cruise and nonlinear orbit determination problems can be solved using a single program is presented. It involves singular value decomposition augmented with an extended partial step algorithm. The extended partial step algorithm constrains the size of the correction to the spacecraft state and other solve-for parameters. The correction is controlled by an a priori covariance and a user-supplied bounds parameter. The extended partial step method is an extension of the update portion of the singular value decomposition algorithm. It thus preserves the numerical stability of the singular value decomposition method, while extending the region over which it converges. In linear cases, this method reduces to the singular value decomposition algorithm with the full rank solution. Two examples are presented to illustrate the method's utility.

Ryne, Mark S.↗
NASA NTRS2018

Spreading Sequence System for Full Connectivity Relay Network

Fully connected uplink and downlink fully connected relay network systems using pseudo-noise spreading and despreading sequences subjected to maximizing the signal-to-interference-plus-noise ratio. The relay network systems comprise one or more transmitting units, relays, and receiving units connected via a communication network. The transmitting units, relays, and receiving units each may include a computer for performing the methods and steps described herein and transceivers for transmitting and/or receiving signals. The computer encodes and/or decodes communication signals via optimum adaptive PN sequences found by employing Cholesky decompositions and singular value decompositions (SVD). The PN sequences employ channel state information (CSI) to more effectively and more securely computing the optimal sequences.

Kwon, Hyuck M.↗
DOE OSTI2020

Computationally Efficient Decompositions of Oblique Projection Matrices

Oblique projection matrices arise in problems in weighted least squares, signal processing, and optimization. While these matrices can be potentially very large, their low-rank structure can be exploited for efficient computation. Here, we propose fast and scalable algorithms for computing their eigendecomposition and singular value decomposition (SVD). Numerical experiments that compare our proposed approaches to existing methods, including randomized SVD, are presented. In addition, we test their accuracy on linear systems from equality constrained optimization problems.

97 MATHEMATICS AND COMPUTING↗