Spatio-Temporal Analysis of Photospheric Turbulent Velocity Fields Using the Proper Orthogonal Decomposition

Solar Physics ◽  
2008 ◽  
Vol 251 (1-2) ◽  
pp. 163-178 ◽  
Author(s):  
A. Vecchio ◽  
V. Carbone ◽  
F. Lepreti ◽  
L. Primavera ◽  
L. Sorriso-Valvo ◽  
...  
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Temporal Analysis ◽  
Velocity Fields ◽  
Orthogonal Decomposition ◽  
Turbulent Velocity ◽  
Spatio Temporal ◽  
Proper Orthogonal

On Proper Orthogonal Decomposition or K-L Expansion to Analyze Transient Sound Pressure Fields in Linear Acoustics

2003 ◽  
Author(s):  
Ioannis T. Georgiou ◽  
Christos I. Papadopoulos
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Sound Pressure ◽  
Pressure Field ◽  
Low Frequency ◽  
Temporal Patterns ◽  
Orthogonal Decomposition ◽  
Noise Sources ◽  
Air Cavity ◽  
Spatio Temporal ◽  
Proper Orthogonal

Identification of the most energetic spatio-temporal patterns that govern the low-frequency dynamics of an air cavity excited by noise sources could lead to significant design improvements of enclosures for noise reduction / isolation and / or sound quality. In this work we show how the Proper Orthogonal Decomposition (POD) method can be applied to identify optimum spatio-temporal patterns governing the dynamics of the sound pressure field developed inside an air cavity. The novel feature of this approach resides into the fact that the POD technique is utilized to process databases for acoustic variables produced by state of the art computational methods in acoustics, such as the finite element method. For a cavity with rigid walls and excited by a harmonic point source, the POD technique reveals that the sound pressure field is composed of a very small number of Proper Orthogonal Modes, which are unique since they are optimum by construction. The POD technique identifies the shapes or patterns of these modes.

scholarly journals Spatio-temporal proper orthogonal decomposition of turbulent channel flow

2019 ◽  
Vol 864 ◽  
pp. 614-639 ◽  
Author(s):  
Srikanth Derebail Muralidhar ◽  
Bérengère Podvin ◽  
Lionel Mathelin ◽  
Yann Fraigneau
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Channel Flow ◽  
Nonlinear Effects ◽  
Turbulent Channel Flow ◽  
Wall Layer ◽  
Orthogonal Decomposition ◽  
Closed Form Expression ◽  
Temporal Decomposition ◽  
Spatio Temporal ◽  
Proper Orthogonal

An extension of proper orthogonal decomposition is applied to the wall layer of a turbulent channel flow ($Re_{\unicode[STIX]{x1D70F}}=590$), so that empirical eigenfunctions are defined in both space and time. Due to the statistical symmetries of the flow, the eigenfunctions are associated with individual wavenumbers and frequencies. Self-similarity of the dominant eigenfunctions, consistent with wall-attached structures transferring energy into the core region, is established. The most energetic modes are characterized by a fundamental time scale in the range 200–300 viscous wall units. The full spatio-temporal decomposition provides a natural measure of the convection velocity of structures, with a characteristic value of 12$u_{\unicode[STIX]{x1D70F}}$ in the wall layer. Finally, we show that the energy budget can be split into specific contributions for each mode, which provides a closed-form expression for nonlinear effects.

Proper Orthogonal Decomposition of HUSIR’s Temperature and Velocity Fields

2011 ◽  
Author(s):  
Kimberly H. Chung ◽  
Anthony A. DiCarlo
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Velocity Fields ◽  
Orthogonal Decomposition ◽  
Thermal Distortion ◽  
Design Consideration ◽  
Antenna Performance ◽  
W Band ◽  
Dynamics Models ◽  
Proper Orthogonal ◽  
Temperature And Velocity Fields

Thermal distortion is a critical design consideration for the Haystack Ultrawide-band Satellite Imaging Radar (HUSIR) with respect to its performance at W-band. This design consideration is needed due to the thermal distortion effects on the surface accuracy of a parabolic reflector. For example, a tight surface tolerance of ∼100 microns root-mean-squared is required to obtain 85 percent antenna performance efficiency for the 37 meter (120 foot) diameter reflector. An understanding of the temperature and velocity fields aids compensation of these losses. Computational fluid dynamics models (CFD) are too computationally expensive to implement in a control algorithm. Therefore, this work applies proper orthogonal decomposition (POD) to simulated CFD data and creates a reduced order model of the fluid system that characterizes the dominant features of both the temperature and velocity fields. A case study of the HUSIR’s convective flow inside a dome is illustrated.

Sign in / Sign up

Export Citation Format

Share Document