A Reconstruction Method for the Flow Past an Open Cavity

2005 ◽  
Vol 128 (3) ◽  
pp. 531-540 ◽  
Author(s):  
B. Podvin ◽  
Y. Fraigneau ◽  
F. Lusseyran ◽  
P. Gougat
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Statistical Information ◽  
Orthogonal Decomposition ◽  
Open Cavity ◽  
Reconstruction Method ◽  
3D Flow ◽  
Flow Past ◽  
Pod Analysis ◽  
Proper Orthogonal

In this paper we propose a method to reconstruct the flow at a given time over a region of space using partial instantaneous measurements and full-space proper orthogonal decomposition (POD) statistical information. The procedure is tested for the flow past an open cavity. 3D and 2D POD analysis are used to characterize the physics of the flow. We show that the full 3D flow can be estimated from a 2D section at an instant in time provided that some 3D statistical information—i.e., the largest POD modes of the flow— is made available.

scholarly journals Rapid Reconstruction of Simulated and Experimental Temperature Fields Based on Proper Orthogonal Decomposition

2020 ◽  
Vol 10 (11) ◽  
pp. 3729
Author(s):  
Minxin Chen ◽  
Shi Liu ◽  
Shanxun Sun ◽  
Zhaoyu Liu ◽  
Yu Zhao
Keyword(s):  
Temperature Field ◽  
Numerical Methods ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Orthogonal Decomposition ◽  
Reconstruction Method ◽  
Gas Combustion ◽  
Field Reconstruction ◽  
Proper Orthogonal ◽  
Temperature Field Reconstruction

Temperature information has a certain significance in thermal energy systems, especially in gas combustion systems. Generally, measurements and numerical calculations are used to acquire temperature information, but both of these approaches have their limitations. Constrained by cost and conditions, measurement methods are difficult to use to reconstruct the temperature field. Numerical methods are able to estimate the temperature field; however, the calculation process in numerical methods is very complex, so these methods cannot be used in real time. For the purpose of solving these problems, a two-dimensional temperature field reconstruction method based on the proper orthogonal decomposition (POD) algorithm is proposed in this study. In the proposed method, the temperature field reconstruction task is transformed into an optimization problem. Theoretical analysis and simulations show that the proposed method is feasible. Gas combustion experiments were also performed to validate this method. Results indicate that the proposed method can yield a reliable reconstruction solution and can be applied to real-time applications.

Proper Orthogonal Decomposition and Extended- Proper Orthogonal Decomposition Analysis of Pressure Fluctuations and Vortex Structures Inside a Steam Turbine Control Valve

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Peng Wang ◽  
Hongyu Ma ◽  
Yingzheng Liu
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Steam Turbine ◽  
Pressure Fluctuation ◽  
Pressure Field ◽  
Pressure Fluctuations ◽  
Control Valve ◽  
Vortex Structures ◽  
Orthogonal Decomposition ◽  
Pod Analysis ◽  
Proper Orthogonal

In steam turbine control valves, pressure fluctuations coupled with vortex structures in highly unsteady three-dimensional flows are essential contributors to the aerodynamic forces on the valve components, and are major sources of flow-induced vibrations and acoustic emissions. Advanced turbulence models can capture the detailed flow information of the control valve; however, it is challenging to identify the primary flow structures, due to the massive flow database. In this study, state-of-the-art data-driven analyses, namely, proper orthogonal decomposition (POD) and extended-POD, were used to extract the energetic pressure fluctuations and dominant vortex structures of the control valve. To this end, the typical annular attachment flow inside a steam turbine control valve was investigated by carrying out a detached eddy simulation (DES). Thereafter, the energetic pressure fluctuation modes were determined by conducting POD analysis on the pressure field of the valve. The vortex structures contributing to the energetic pressure fluctuation modes were determined by conducting extended-POD analysis on the pressure–velocity coupling field. Finally, the dominant vortex structures were revealed conducting a direct POD analysis of the velocity field. The results revealed that the flow instabilities inside the control valve were mainly induced by oscillations of the annular wall-attached jet and the derivative flow separations and reattachments. Moreover, the POD analysis of the pressure field revealed that most of the pressure fluctuation intensity comprised the axial, antisymmetric, and asymmetric pressure modes. By conducting extended-POD analysis, the incorporation of the vortex structures with the energetic pressure modes was observed to coincide with the synchronous, alternating, and single-sided oscillation behaviors of the annular attachment flow. However, based on the POD analysis of the unsteady velocity fields, the vortex structures, buried in the dominant modes at St = 0.017, were found to result from the alternating oscillation behaviors of the annular attachment flow.

scholarly journals Proper Orthogonal Decomposition as Surrogate Model for Aerodynamic Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Valentina Dolci ◽  
Renzo Arina
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Parameter Space ◽  
Surrogate Model ◽  
Orthogonal Decomposition ◽  
High Fidelity ◽  
Aerodynamic Optimization ◽  
Model Based ◽  
Flow Past ◽  
First Case ◽  
Proper Orthogonal

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 based on an ensemble of high-fidelity computations. For the construction of the ensemble, fractional and full factorial planes together with central composite design-of-experiment strategies are applied. For the continuous representation of the projection coefficients in the parameter space, response surface methods are employed. Three case studies are presented. In the first case, the boundary shape of the problem is deformed and the flow past a backward facing step with variable step slope is studied. In the second case, a two-dimensional flow past a NACA 0012 airfoil is considered and the surrogate model is constructed in the (Mach, angle of attack) parameter space. In the last case, the aerodynamic optimization of an automotive shape is considered. The results demonstrate how a reduced-order model based on the proper orthogonal decomposition applied to a small number of high-fidelity solutions can be used to generate aerodynamic data with good accuracy at a low cost.

Systematic Characterization of Coupled Structural-Acoustic Systems With the Aid of Temporal and Spectral (Complex) Proper Orthogonal Decomposition

2008 ◽  
Author(s):  
Christos I. Papadopoulos ◽  
Ioannis T. Georgiou
Keyword(s):  
Finite Element ◽  
Steady State ◽  
Proper Orthogonal Decomposition ◽  
Transient Response ◽  
Degrees Of Freedom ◽  
Sound Propagation ◽  
Orthogonal Decomposition ◽  
Pod Analysis ◽  
Proper Orthogonal ◽  
Spectral Complex

We extend the application of temporal and spectral Proper Orthogonal Decomposition (POD) to study the sound propagation and sound-structure interaction of systems combined of acoustic and structural subsystems. We consider a prototypical system consisted of two adjacent rooms separated by a sound insulating plate. Approximation to the steady-state and transient response is obtained with the aid of the finite element method. We define the temporal (real) and spectral (complex) variations of POD to tackle acoustical and structural degrees of freedom. We apply the method to process the numerical databases of the finite element solutions. It is shown that the steady-state and transient response may be represented by a small number of dominant POD modes. The extracted frequencies and spatial shapes are evaluated and linked to the modal properties of the system. It is shown that POD analysis may provide significant insight on the properties of coupled structural-acoustic systems.

scholarly journals On the Application of Proper Orthogonal Decomposition (POD) for In-Cylinder Flow Analysis

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2261 ◽  
Author(s):  
Mohammed El-Adawy ◽  
Morgan Heikal ◽  
A. A. Aziz ◽  
Ibrahim Adam ◽  
Mhadi Ismael ◽  
...  
Keyword(s):  
Physical Properties ◽  
Proper Orthogonal Decomposition ◽  
Pressure Difference ◽  
Velocity Vector ◽  
Vector Fields ◽  
Orthogonal Decomposition ◽  
Stereoscopic Particle Image Velocimetry ◽  
Pod Analysis ◽  
Cylinder Flow ◽  
Proper Orthogonal

Proper orthogonal decomposition (POD) is a coherent structure identification technique based on either measured or computed data sets. Recently, POD has been adopted for the analysis of the in-cylinder flows inside internal combustion engines. In this study, stereoscopic particle image velocimetry (Stereo-PIV) measurements were carried out at the central vertical tumble plane inside an engine cylinder to acquire the velocity vector fields for the in-cylinder flow under different experimental conditions. Afterwards, the POD analysis were performed firstly on synthetic velocity vector fields with known characteristics in order to extract some fundamental properties of the POD technique. These data were used to reveal how the physical properties of coherent structures were captured and distributed among the POD modes, in addition to illustrate the difference between subtracting and non-subtracting the ensemble average prior to conducting POD on datasets. Moreover, two case studies for the in-cylinder flow at different valve lifts and different pressure differences across the air intake valves were presented and discussed as the effect of both valve lifts and pressure difference have not been investigated before using phase-invariant POD analysis. The results demonstrated that for repeatable flow pattern, only the first mode was sufficient to reconstruct the physical properties of the flow. Furthermore, POD analysis confirmed the negligible effect of pressure difference and subsequently the effect of engine speed on flow structures.

scholarly journals Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1660
Author(s):  
Tanmoy Chatterjee ◽  
Yulia T. Peet
Keyword(s):  
Power Generation ◽  
Proper Orthogonal Decomposition ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Orthogonal Decomposition ◽  
Large Scale Structures ◽  
Scale Structures ◽  
Pod Analysis ◽  
Proper Orthogonal

Large scale coherent structures in the atmospheric boundary layer (ABL) are known to contribute to the power generation in wind farms. In order to understand the dynamics of large scale structures, we perform proper orthogonal decomposition (POD) analysis of a finite sized wind turbine array canopy in the current paper. The POD analysis sheds light on the dynamics of large scale coherent modes as well as on the scaling of the eigenspectra in the heterogeneous wind farm. We also propose adapting a novel Fourier-POD (FPOD) modal decomposition which performs POD analysis of spanwise Fourier-transformed velocity. The FPOD methodology helps us in decoupling the length scales in the spanwise and streamwise direction when studying the 3D energetic coherent modes. Additionally, the FPOD eigenspectra also provide deeper insights for understanding the scaling trends of the three-dimensional POD eigenspectra and its convergence, which is inherently tied to turbulent dynamics. Understanding the behaviour of large scale structures in wind farm flows would not only help better assess reduced order models (ROM) for forecasting the flow and power generation but would also play a vital role in improving the decision making abilities in wind farm optimization algorithms in future. Additionally, this study also provides guidance for better understanding of the POD analysis in the turbulence and wind farm community.

Sign in / Sign up

Export Citation Format

Share Document