Effects of Outlier Flow Field on the Characteristics of In-Cylinder Coherent Structures Identified by Proper Orthogonal Decomposition-Based Conditional Averaging and Quadruple Proper Orthogonal Decomposition

2019 ◽  
Vol 141 (8) ◽  
Author(s):  
Rui Gao ◽  
Li Shen ◽  
Kwee-Yan Teh ◽  
Penghui Ge ◽  
Fengnian Zhao ◽  
...  
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Coherent Structures ◽  
Large Scale ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Engine Cylinder ◽  
Conditional Averaging ◽  
Proper Orthogonal ◽  
Engine Cycle

Proper orthogonal decomposition (POD) offers an approach to quantify cycle-to-cycle variation (CCV) of the flow field inside the internal combustion engine cylinder. POD decomposes instantaneous flow fields (also called snapshots) into a series of orthonormal flow patterns (called POD modes) and the corresponding mode coefficients. The POD modes are rank-ordered by decreasing kinetic energy content, and the low-order, high-energy modes are interpreted as constituting the large-scale coherent flow structure that varies from engine cycle to engine cycle. Various POD-based analysis techniques have thus been proposed to characterize engine flow field CCV using these low-order modes. The validity of such POD-based analyses rests, as a matter of course, on the reliability of the underlying POD results (modes and coefficients). Yet a POD mode can be disproportionately skewed by a single outlier snapshot within a large data set, and an algorithm exists to define and identify such outliers. In this paper, the effects of a candidate outlier snapshot on the results of POD-based conditional averaging and quadruple POD analyses are examined for two sets of crank angle-resolved flow fields on the midtumble plane of an optical engine cylinder recorded by high-speed particle image velocimetry (PIV). The results with and without the candidate outlier are compared and contrasted. In the case of POD-based conditional averaging, the presence of the outlier scrambles the composition of snapshot subsets that define large-scale flow pattern variations, and thus substantially alters the coherent flow structures that are identified; for quadruple POD, the shape of coherent structures and the number of modes to define them are not significantly affected by the outlier.

Effects of Outlier Flow Field on the Characteristics of In-Cylinder Coherent Structures Identified by POD-Based Conditional Averaging and Quadruple POD

2018 ◽  
Author(s):  
Rui Gao ◽  
Li Shen ◽  
Kwee-Yan Teh ◽  
Penghui Ge ◽  
Fengnian Zhao ◽  
...  
Keyword(s):  
Flow Field ◽  
Coherent Structures ◽  
Large Scale ◽  
Flow Fields ◽  
High Energy ◽  
Data Set ◽  
Engine Cylinder ◽  
Conditional Averaging ◽  
Engine Cycle ◽  
Low Order

Proper Orthogonal Decomposition (POD) offers an approach to quantify cycle-to-cycle variation (CCV) of the flow field inside the internal combustion engine cylinder. POD decomposes instantaneous flow fields (also called snapshots) into a series of orthonormal flow patterns (called POD modes) and the corresponding mode coefficients. The POD modes are rank-ordered by decreasing kinetic energy content, and the low-order, high-energy modes are interpreted as constituting the large-scale coherent flow structure that varies from engine cycle to engine cycle. Various POD-based analysis techniques have thus been proposed to characterize engine flow field CCV using these low-order modes. The validity of such POD-based analyses rests, as a matter of course, on the reliability of the underlying POD results (modes and coefficients). Yet a POD mode can be disproportionately skewed by a single outlier snapshot within a large data set, and an algorithm exists to define and identify such outliers. In this paper, the effects of a candidate outlier snapshot on the results of POD-based conditional averaging and quadruple POD analyses are examined for two sets of crank angle-resolved flow fields on the mid-tumble plane of an optical engine cylinder recorded by high-speed particle image velocimetry. The results with and without the candidate outlier are compared and contrasted. In the case of POD-based conditional averaging, the presence of the outlier scrambles the composition of snapshot subsets that define large-scale flow pattern variations, and thus substantially alters the coherent flow structures that are identified; for quadruple POD, the shape of coherent structures as well as the number of modes to define them are not significantly affected by the outlier.

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.

Analysis of In-Cylinder Turbulent Flows in a DISI Gasoline Engine With a Proper Orthogonal Decomposition Quadruple Decomposition

2014 ◽  
Vol 136 (11) ◽  
Author(s):  
Wenjin Qin ◽  
Maozhao Xie ◽  
Ming Jia ◽  
Tianyou Wang ◽  
Daming Liu
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Turbulent Flows ◽  
Gasoline Engine ◽  
Measurement Data ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Coherent Field ◽  
Piv Measurement ◽  
Proper Orthogonal

The proper orthogonal decomposition (POD) method is applied to analyze the particle image velocimetry (PIV) measurement data and large eddy simulation (LES) result from an in-cylinder turbulence flow field in a four-valve direct injection spark ignition (DISI) engine. The instantaneous flow fields are decomposed into four parts, namely, mean field, coherent field, transition field and turbulent field, respectively, by the POD quadruple decomposition. The filtering method for separating the four flow parts is based on examining the relevance and correlations between different flow fields reconstructed with various POD mode numbers, and the corresponding reconstructed fields have been verified by their statistical properties. Then, the in-cylinder flow evolution and cycle-to-cycle variations (CCV) are studied separately upon the four field parts. Results indicate that each one of the four field parts exhibits its own flow characteristics and has close connection with others. Furthermore, the mean part contains the most kinetic energy of the entire flow field and represents the bulk flow of the original in-cylinder velocity field; the CCV in this part could almost be neglected, while the coherent field part contains larger scale structures and the most fluctuating energy, and possesses the highest CCV level among the four parts.

Study of Time-Resolved Vortex Structure of In-Cylinder Engine Flow Fields Using Proper Orthogonal Decomposition Technique

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Hanyang Zhuang ◽  
David L.S. Hung ◽  
Hao Chen
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Vortex Structure ◽  
High Speed ◽  
Internal Combustion Engines ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Vortex Center ◽  
Time Resolved ◽  
Proper Orthogonal

The structure of in-cylinder flow field makes significant impacts on the processes of fuel injection, air–fuel interactions, and flame development in internal combustion engines. In this study, the implementation of time-resolved particle image velocimetry (PIV) in an optical engine is presented. Flow field PIV images at different crank angles have been taken using a high-speed double-pulsed laser and a high-speed camera with seeding particles mixed with the intake air. This study is focused on measuring the flow fields on the swirl plane at 30 mm below the injector tip under various intake air swirl ratios. A simple algorithm is developed to identify the vortex structure and to track the location and motion of vortex center at different crank angles. Proper orthogonal decomposition (POD) has been used to extract the ensemble and variation information of the vortex structure. Experimental results reveal that strong cycle-to-cycle variations exist in almost all test conditions. The vortex center is difficult to identify since multiple, but small scale, vortices exist during the early stage of the intake stroke. However, during the compression stroke when only one vortex center exists in most cycles, the motion of vortex center is found to be quite similar at different intake swirl ratios and engine speeds. This is due to the dominant driving force exerted by the piston’s upward motion on the in-cylinder air.

Large eddy simulation study of flow field characteristics of a combustor with two coaxial swirlers

2019 ◽  
Vol 234 (5) ◽  
pp. 625-642
Author(s):  
Qun Zhang ◽  
Peng Zhang ◽  
Shun-li Sun ◽  
Ya-heng Song ◽  
Yi-fei Li ◽  
...  
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Vortex Core ◽  
Large Scale ◽  
Recirculation Zone ◽  
Swirling Flow ◽  
Orthogonal Decomposition ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Proper Orthogonal

The cold and reaction flow fields of a combustor with two coaxial swirlers are investigated by means of large eddy simulation. Effective data processing methods such as proper orthogonal decomposition and fast Fourier transform are employed for analysis. The complex flow phenomena such as swirling jet, shear layer, recirculation zone, and precession vortex core are observed and their characteristics are analyzed. The dynamics of the flame and its interactions with the complex swirling flows and large-scale eddies are characterized. The precession vortex core structures and its influences on the combustion process are emphatically explored. It is found that the outer shear layer produces spiral precession vortex core cantilever structures and the change of structural characteristics of the PVC determines the pressure pulsation frequency of the combustor. The results also indicate precession vortex core accelerates the mixing of unburned and burned mixture, leading to the ignition. The principal structures are studied by determining the highest energy modes via proper orthogonal decomposition. The modes are classified according to energy size. By means of proper orthogonal decomposition four-decomposition method, the vortexes of different energy and scales in swirling flow field are classified and analyzed in detail, the flow field is reconstructed, and the large-scale coherent structures and small energy flow structures are obtained. A spectral map of the turbulent kinetic energy density exhibits the −5/3 slope given by the Kolmogorov–Obukhov law. Based on the analysis of the vortex structures and their evolution, and the analysis of the transports and distributions of flow field characteristic parameters, a novel unsteady swirling flow combustion organization mechanism is proposed. It is found that combustion mainly occurs in low-energy small-scale vortexes, releasing a large amount of heat. High-temperature gas enters the recirculation zone and continues to provide energy for the precession vortex cores.

Study on flow field and aerodynamic noise of electric vehicle rearview mirror

2021 ◽  
pp. 095440702110228
Author(s):  
Xiaowei Hao ◽  
Zhigang Yang ◽  
Qiliang Li
Keyword(s):  
Flow Field ◽  
Proper Orthogonal Decomposition ◽  
Electric Vehicle ◽  
Sound Pressure ◽  
Pressure Level ◽  
Orthogonal Decomposition ◽  
Aerodynamic Noise ◽  
Turbulent Pressure ◽  
Rearview Mirror ◽  
Proper Orthogonal

With the development of new energy and intelligent vehicles, aerodynamic noise problem of pure electric vehicles at high speed has become increasingly prominent. The characteristics of the flow field and aerodynamic noise of the rearview mirror region were investigated by large eddy simulation, acoustic perturbation equations and reduction order analysis. By comparing the pressure coefficients of the coarse, medium and dense grids with wind tunnel test results, the pressure distribution, and numerical accuracy of the medium grid on the body are clarified. It is shown from the flow field proper orthogonal decomposition of the mid-section that the sum of the energy of the first three modes accounts for more than 16%. Based on spectral proper orthogonal decomposition, the peak frequencies of the first-order mode are 19 and 97 Hz. As for the turbulent pressure of side window, the first mode accounts for approximately 11.3% of the total energy, and its peak appears at 39 and 117 Hz. While the first mode of sound pressure accounts for about 41.7%, and the energy peaks occur at 410 and 546 Hz. Compared with traditional vehicle, less total turbulent pressure level and total sound pressure level are found at current electric vehicle because of the limited interaction between the rearview mirror and A-pillar.

Inverse design of aircraft cabin environment using computational fluid dynamics-based proper orthogonal decomposition method

2017 ◽  
Vol 27 (10) ◽  
pp. 1379-1391 ◽  
Author(s):  
Jihong Wang ◽  
Tengfei (Tim) Zhang ◽  
Hongbiao Zhou ◽  
Shugang Wang
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Proper Orthogonal Decomposition ◽  
Flow Fields ◽  
Orthogonal Decomposition ◽  
Inverse Design ◽  
Air Supply ◽  
Spatial Modes ◽  
Cabin Environment ◽  
Proper Orthogonal

To design a comfortable aircraft cabin environment, designers conventionally follow an iterative guess-and-correction procedure to determine the air-supply parameters. The conventional method has an extremely low efficiency but does not guarantee an optimal design. This investigation proposed an inverse design method based on a proper orthogonal decomposition of the thermo-flow data provided by full computational fluid dynamics simulations. The orthogonal spatial modes of the thermo-flow fields and corresponding coefficients were firstly extracted. Then, a thermo-flow field was expressed into a linear combination of the spatial modes with their coefficients. The coefficients for each spatial mode are functions of air-supply parameters, which can be interpolated. With a quick map of the cause–effect relationship between the air-supply parameters and the exhibited thermo-flow fields, the optimal air-supply parameters were determined from specific design targets. By setting the percentage of dissatisfied and the predicted mean vote as design targets, the proposed method was implemented for inverse determination of air-supply parameters in two aircraft cabins. The results show that the inverse design using computational fluid dynamics-based proper orthogonal decomposition method is viable. Most of computing time lies in the construction of data samples of thermo-flow fields, while the proper orthogonal decomposition analysis and data interpolation is efficient.

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