Results 41 to 50 of about 1,753,791 (268)
Analysis of Multi-Stream Fuel Injector Flow Using Zonal Proper Orthogonal Decomposition
The 3-component velocity distribution of two lean-burn gas turbine fuel injectors are measured at a planar location near and parallel to the injector outlet.
Daniel Butcher, Adrian Spencer
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Proper Orthogonal Decomposition as Surrogate Model for Aerodynamic Optimization
A surrogate model based on the proper orthogonal decomposition is developed in order to enable fast and reliable evaluations of aerodynamic fields. The proposed method is applied to subsonic turbulent flows and the proper orthogonal decomposition is ...
Valentina Dolci, Renzo Arina
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Artificial viscosity proper orthogonal decomposition
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Jeff Borggaard +2 more
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Acceleration of Gas Reservoir Simulation Using Proper Orthogonal Decomposition
High-precision and high-speed reservoir simulation is important in engineering. Proper orthogonal decomposition (POD) is introduced to accelerate the reservoir simulation of gas flow in single-continuum porous media via establishing a reduced-order model
Yi Wang, Bo Yu, Ye Wang
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Lagrangian proper orthogonal decomposition
We introduce a modal representation for Lagrangian trajectories in turbulence, termed Lagrangian proper orthogonal decomposition. An ensemble of particle trajectories is used to construct velocity time series, which are normalized independently for each trajectory to isolate fluctuations.
Stefano Brizzolara, Ron Shnapp
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Combined proper orthogonal decompositions of orthogonal subspaces
9 pages, 3 ...
Olesen, Peder J. +2 more
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A common interpretation is presented for four powerful modal decomposition techniques: “proper orthogonal decomposition,” “smooth orthogonal decomposition,” “state-variable decomposition,” and “dynamic mode decomposition.” It is shown that, in certain ...
Arham Amin Khan +2 more
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Localised Proper Orthogonal Decomposition
Proper Orthogonal Decomposition (POD) extracts an optimal orthonormal basis for reconstructing a sequence of data. This technique is widely used in fluid mechanics to construct reduced-order models for physical analysis, modelling, estimation, and control.
Elhaddad, Dyhia +3 more
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Investigation of proper orthogonal decomposition for echo state networks
Echo State Networks (ESN) are a type of Recurrent Neural Network that yields promising results in representing time series and nonlinear dynamic systems. Although they are equipped with a very efficient training procedure, Reservoir Computing strategies, such as the ESN, require high-order networks, i.e., many neurons, resulting in a large number of ...
Jean Panaioti Jordanou +3 more
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Understanding Cavity Flows Using Proper Orthogonal Decomposition and Signal Processing
Computational Fluid Dynamics (CFD) is increasingly being used to analyse complex flows. However, to perform a comprehensive analysis over a given time period, a large amount of data is provided and therefore a method for reducing the storage requirements
S.J. Lawson, G.N. Barakos, A. Simpson
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