Results 61 to 70 of about 51,908 (255)
This paper proposes a methodology to automatically choose the measurement locations of a nonlinear structure/equipment that needs to be monitored while operating.
T. G. Ritto
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Extraction of the mode shapes of a segmented ship model with a hydroelastic response
The mode shapes of a segmented hull model towed in a model basin were predicted using both the Proper Orthogonal Decomposition (POD) and cross random decrement technique.
Yooil Kim, In-Gyu Ahn, Sung-Gun Park
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Impinging jets on plates with specific geometries, found in habitable enclosures, require a fundamental knowledge of the flow topology in order to reduce any acoustic or aeraulic discomfort.
Jana Hamdi +5 more
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Comparison of Flow Behavior in Saccular Aneurysm Models Using Proper Orthogonal Decomposition
Aneurysms are abnormal ballooning of a blood vessel. Previous studies have shown presence of complex flow structures in aneurysms. The objective of this study was to quantify the flow features observed in two selected saccular aneurysm geometries over a ...
Paulo Yu, Vibhav Durgesh
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Proper Orthogonal Decomposition Based Turbulence Modeling [PDF]
An analysis of the near-wall behavior of the proper orthogonal decomposition (POD) eigenfunctions derived from direct numerical simulation (DNS) of channel flow is performed. Consistent with previous studies, a low order multi-mode reconstruction of the kinetic energy and Reynolds shear stress suffices.
T. B. Gatski, M. N. Glauser
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On the Wake Dynamics of an Oscillating Cylinder via Proper Orthogonal Decomposition
The coherent structures and wake dynamics of a two-degree-of-freedom vibrating cylinder with a low mass ratio at Re=5300 are investigated by means of proper orthogonal decomposition (POD) of a numerical database generated using large-eddy simulations ...
Benet Eiximeno +4 more
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Mahalanobis-Taguchi System (MTS) is an effective algorithm for dimensionality reduction, feature extraction and classification of data in a multidimensional system.
Ting Mao +3 more
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Thermal field reconstruction and compressive sensing using proper orthogonal decomposition
Model order reduction allows critical information about sensor placement and experiment design to be distilled from raw fluid mechanics simulation data.
John Matulis, Hitesh Bindra
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PySPOD: A Python package for Spectral Proper Orthogonal Decomposition (SPOD)
Large unstructured datasets may contain complex coherent patterns that evolve in time and space, and that the human eye cannot grasp. These patterns are frequently essential to unlock our understanding of complex systems that can arise in nature, such as
G. Mengaldo, R. Maulik
semanticscholar +1 more source
Robust spectral proper orthogonal decomposition
Experimental measurements often present corrupted data and outliers that can strongly affect the main coherent structures extracted with the classical modal analysis techniques. This effect is amplified at high frequencies, whose corresponding modes are more susceptible to contamination from measurement noise and uncertainties.
Colanera A., Schmidt O. T., Chiatto M.
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