Results 11 to 20 of about 136,878 (263)
Proper Orthogonal Decomposition of Solar Photospheric Motions
Physical Review Letters, 2005 The spatio-temporal dynamics of the solar photosphere is studied by performing a Proper Orthogonal Decomposition (POD) of line of sight velocity fields computed from high resolution data coming from the MDI/SOHO instrument. Using this technique, we are able to identify and characterize the different dynamical regimes acting in the system. Low frequency
VECCHIO A. +7 more
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Guide to Spectral Proper Orthogonal Decomposition [PDF]
AIAA Journal, 2020 This paper discusses the spectral proper orthogonal decomposition and its use in identifying modes, or structures, in flow data.
Schmidt, Oliver T., Colonius, Tim
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Sparse sensor-based flow estimation with spectral proper orthogonal decomposition
AIP Advances, 2022 The application of Artificial Neural Networks (ANNs) in developing sensor-based estimators for unsteady flows has become an active area of research over the last decade.
Henrique Gambassi +2 more
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A randomized proper orthogonal decomposition technique [PDF]
2015 American Control Conference (ACC), 2015 In this paper, we consider the problem of model reduction of large scale systems, such as those obtained through the discretization of PDEs. We propose a randomized proper orthogonal decomposition (RPOD) technique to obtain the reduced order models by randomly choosing a subset of the inputs/outputs of the system to construct a suitable small sized ...
Yu, Dan, Chakravorty, Suman
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Comparative Study on Modal Decomposition Methods of Unsteady Separated Flow in Compressor Cascade
Xibei Gongye Daxue Xuebao, 2020 The present work investigated the vortex structure and fluctuation frequency characteristics generated by boundary layer separation of a high-load compressor cascade using modal decomposition methods.
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Proper orthogonal decomposition method for Schrödinger equation
Lietuvos Matematikos Rinkinys, 2013 In this paper we consider the proper orthogonal decomposition (POD) method for one-dimensional Schrödinger equation. We begin of the review of basic ideas of POD. Later this method is applied to study the linear Schrödinger equation.
Raimondas Čiegis +2 more
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Proper orthogonal decomposition method for some parabolic type equations
Lietuvos Matematikos Rinkinys, 2012 In this paper proper orthogonal decomposition method for 1D parabolic type equations is described. First basic ideas of method are presented and application scheme for compiutations is derived.
Gerda Jankevičiūtė +2 more
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MODULO: A software for Multiscale Proper Orthogonal Decomposition of data
SoftwareX, 2020 In the era of the Big Data revolution, methods for the automatic discovery of regularities in large datasets are becoming essential tools in applied sciences. This article presents an open software package, named MODULO (MODal mULtiscale pOd), to perform
Davide Ninni, Miguel A. Mendez
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Combined proper orthogonal decompositions of orthogonal subspaces
, 2023 9 pages, 3 ...
Olesen, Peder J. +2 more
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Uncertainty Analysis of Neutron Diffusion Eigenvalue Problem Based on Reduced-order Model
Yuanzineng kexue jishu, 2023 In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model ...
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model based on POD-Galerkin method in core physical uncertainty analysis. The two-dimensional two group TWIGL benchmark question was taken as the research object, the key variation characteristics of the core flux distribution were extracted under the finite perturbation of the group constants of each material region, and the full-order neutron diffusion problem was projected on the variation characteristics to establish a reduced-order neutron diffusion model. The reduced-order model was used to replace the full-order model to carry out the uncertainty analysis of the group constants of the material region. The results show that the bias of the mathematical expectation of keff calculated by reduced-order and full-order models is close to 1 pcm. In addition, compared with the calculation time required for uncertainty analysis of full-order model, the analysis time of reduced-order model (including the calculation time of the full-order model required for the construction of reduced-order model) is only 11.48%, which greatly improves the efficiency of uncertainty analysis. The biases of mathematical expectation of keff calculated by reduced-order and full-order models based on Latin hypercube sampling and simple random sampling are less than 8 pcm, and under the same sample size, the bias from the Latin hypercube sampling result is smaller. From the TWIGL benchmark test results, under the same sample size, Latin hypercube sampling method is more recommended for POD-Galerkin reduced-order model.
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