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.

Temporal evolution analysis of in-cylinder flow by means of proper orthogonal decomposition

2020 ◽  
pp. 146808742091724
Author(s):  
Li Shen ◽  
Kwee-Yan Teh ◽  
Penghui Ge ◽  
Fengnian Zhao ◽  
David LS Hung
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Internal Combustion Engines ◽  
Temporal Evolution ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Temporal Behavior ◽  
Decomposition Approach ◽  
Cylinder Flow ◽  
Proper Orthogonal ◽  
Low Order

In-cylinder flow fields and their temporal evolution have strong effect on the combustion dynamics of internal combustion engines. Proper orthogonal decomposition is a statistical tool to analyze these flow fields by decomposing them into flow patterns (known as proper orthogonal decomposition modes) and corresponding coefficients with their contribution to the ensemble flow kinetic energy successively maximized. However, neither of the two prevailing proper orthogonal decomposition approaches satisfactorily describes the temporal behavior of the flow fields. The phase-dependent proper orthogonal decomposition approach is limited to analyzing spatial flow structures at a certain engine phase. The phase-invariant proper orthogonal decomposition approach attempts to account for both spatial and temporal variations, but at the expense of diminished statistical and physical significance. In this article, we seek to understand the temporal behavior of tumble flow fields by analyzing the evolution of low-order phase-dependent proper orthogonal decomposition modes over multiple crank angles. The concept of relevance index is first generalized to enable comparison between two vectorial fields of different sizes. This metric is then used to quantify the directional similarities between the two lowest proper orthogonal decomposition modes obtained at sequential crank angles. The mode shapes are observed to evolve gradually and naturally over most crank angles, but change significantly at certain crank angles during intake. The results indicate that each of the low-order modes features strong velocity fluctuations in different regions of the tumble plane, and different numbers of modes are needed to represent the dominant features of tumble flow at different engine phases. Based on this understanding, we propose to use the partial sum of those proper orthogonal decomposition modes and their coefficients to form a low-order approximation model of the in-cylinder tumble flow, in order to reduce flow field complexity and noise while retaining its major spatial and temporal features.

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.

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 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.

Proper Orthogonal Decomposition Analysis of Non-Swirling Turbulent Stratified and Premixed Methane/Air Flames

2014 ◽  
Author(s):  
M. Mustafa Kamal ◽  
Christophe Duwig ◽  
Saravanan Balusamy ◽  
Ruigang Zhou ◽  
Simone Hochgreb
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
High Speed ◽  
Large Scale ◽  
Bluff Body ◽  
Decomposition Analysis ◽  
Orthogonal Decomposition ◽  
Stereoscopic Particle Image Velocimetry ◽  
Large Scale Flow ◽  
Proper Orthogonal

This paper reports proper orthogonal decomposition (POD) analyses for the velocity fields measured in a test burner. The Cambridge/Sandia Stratified Swirl Burner has been used in various studies as a benchmark for high resolution scalar and velocity measurements, for comparison with numerical model prediction. Flow field data was collected for a series of bluff-body stabilized premixed and stratified methane/air flames at turbulent, globally lean conditions (ϕ = 0.75) using high speed stereoscopic particle image velocimetry (HS-SPIV). In this paper, a modal analysis was performed to identify the large scale flow structures and their impact on the flame dynamics. The high speed PIV system was operated at 3 kHz to acquire a series of 4096 sequential flow field images both for reactive and non-reactive cases, sufficient to follow the large-scale spatial and temporal evolution of flame and flow dynamics. The POD analysis allows identification of vortical structures, created by the bluff body, and in the shear layers surrounding the stabilization point. In addition, the analysis reveals that dominant structures are a strong function of the mixture stratification in the flow field. The dominant energetic modes of reactive and non-reactive flows are very different, as the expansion of gases and the high temperatures alter the unstable modes and their survival in the flow.

Stereoscopic Particle Image Velocimetry Measurements and Proper Orthogonal Decomposition Analysis of the In-Cylinder Flow of Gasoline Direct Injection Engine

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Mohammed El-Adawy ◽  
M. R. Heikal ◽  
A. Rashid A. Aziz
Keyword(s):  
Particle Image Velocimetry ◽  
Proper Orthogonal Decomposition ◽  
Particle Image ◽  
Direct Injection ◽  
Orthogonal Decomposition ◽  
Stereoscopic Particle Image Velocimetry ◽  
Gasoline Direct Injection ◽  
Image Velocimetry ◽  
Gdi Engine ◽  
Proper Orthogonal

Intake generated flows are known to have a fundamental influence on the combustion both in spark ignition (SI) and compression ignition engines. This study experimentally investigated the tumble flow structures inside a cylinder of gasoline direct injection (GDI) engine utilizing a stereoscopic time-resolved particle image velocimetry (PIV). The experiments were conducted in a GDI engine head for a number of fixed valve lifts and 150 mmH2O pressure difference across the intake valves. A tumble flow analysis was carried out considering different vertical tumble planes. In addition, the proper orthogonal decomposition (POD) identification technique was applied on the PIV data in order to spatially analyze the structures embedded in the instantaneous velocity data sets. The results showed that the flow was dominated by a strong tumble motion in the middle of cylinder at high valve lifts (8–10 mm). Moreover, it is worth pointing out that, because of the complexity of the flow at the high valve lifts, the flow energy was distributed over a higher number of POD modes. This was confirmed by the need of a higher number of POD modes needed to reconstruct the original velocity field to the same level of fidelity.

scholarly journals Analysis of Multi-Stream Fuel Injector Flow Using Zonal Proper Orthogonal Decomposition

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1789
Author(s):  
Daniel Butcher ◽  
Adrian Spencer
Keyword(s):  
Velocity Field ◽  
Proper Orthogonal Decomposition ◽  
Significant Proportion ◽  
Flow Region ◽  
Orthogonal Decomposition ◽  
Stereoscopic Particle Image Velocimetry ◽  
Fuel Injector ◽  
Velocity Data ◽  
Lean Burn ◽  
Proper Orthogonal

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. The two injectors are nominally the same design, but one features blocked central passages to study the effects of the presence of multi-streams and reveal the single stream characteristics embedded within the multi-stream configuration. Stereoscopic particle image velocimetry is used in an isothermal, non-reacting water analogue flow facility at an engine relevant Reynolds number. The velocity data is analysed using proper orthogonal decomposition (POD) and the work introduces the concept of Zonal POD. This is the splitting of the velocity field into zones prior to the calculation of POD modes to better identify prominent structures and features associated with each zone. Because modes are sorted by the area averaged energy contribution, zoning of a velocity field of interest may change the individual modes and will almost certainly change their order for anything other than trivial flow fields. Analysis of ensemble average and velocity fluctuation profiles reveals a radial shift outboard of the mains flow with the presence of the pilot as well as a general increase in RMS across the intermediate region between the pilot and mains flows. Analysis of POD temporal coefficients in the frequency domain reveals a low-frequency peak is evident in the mains flow region, but which may be affected by the presence of pilot flow. Furthermore, application of the ZPOD technique results in a closer representation of the velocity data for a given number of modes. This shows the behaviour of the unsteady pilot flow and reveals that a significant proportion of the fluctuating energy, RMS, is caused by this characteristic.

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