Investigation of fundamental flow mechanisms over a corrugated waveform using proper orthogonal decomposition and spectral analyses

Greig, David; Siddiqui, Kamran; Karava, Panagiota; Elatar, Ahmed

doi:10.1016/j.ijthermalsci.2015.05.003

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…In the flow field analysis of the containing particulate, mode decomposition technique is one of the effective methods to the study of complex flow states such as Proper orthogonal decomposition(POD) [10,11], Global eigenfrequency decomposition (GED) [12], and Dynamic modal decomposition (DMD) [13] methods, for example, Ma et al [12] put forward a modal analysis method based on fast Fourier transform, the full-field power spectrum density is employed as a foundation to select the characteristic frequency, the full-field amplitude spectrum, phase spectrum, and mode corresponding to the characteristic frequency can be obtained, and the complex flow field around the cylinder under the control of the composite jet can be analyzed efficiently and accurately. Wang et al [14]used the eigen orthogonal decomposition to separate the scale from the flow field, and found that the velocity distribution corresponding to the large scale structure was close to the original flow field, while the vorticity distribution and spectral characteristics of the small scale flow field were highly consistent with the original vorticity distribution.…”

Section: Introductionmentioning

confidence: 99%

Prediction of particulate content in oil based on SPA vibration feature selection

Liu¹,

Bin²

2022

Scientia Iranica

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Aiming at the non-stationary characteristics of oil pressure vibration signals containing particulate, a method for predicting particulate content in oil was proposed based on vibration characteristic frequency extraction by vibrational mode decomposition (VMD), variable selection using successive projections algorithm (SPA) and T_S fuzzy identification combined. Firstly, the pressure vibration signal was decomposed by VMD and a series of narrow-band characteristic frequency matrices were obtained. Then, variables were selected using SPA to construct the feature vector matrix. Finally, the feature vector matrix was used as the input of T_S fuzzy identification to identify the content of particulate in oil. The results showed that the VMD reconstruction of the original oil sample pressure signals could well characterize the main variation of the original signal; the 19 variables were selected from the characteristic frequency of the vibration signal from the oil pressure using SPA, the 19 pressure vibration characteristic frequency of 11 sample sets SPA selected was taken as the input variable of T_S identification model; for each set of sample, the predicted output of the content of particulate in oil was obtained, model prediction decision coefficient is 0.8637, the root mean square error is 0.1979, a reasonable prediction effect was obtained.

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Section: Introductionmentioning

confidence: 99%

Prediction of particulate content in oil based on SPA vibration feature selection

Liu¹,

Bin²

2022

Scientia Iranica

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“…Their aim was to study how the flow structures vary in different wall permeabilities. The study [22] investigated the energies and scales associated with turbulent flow features and how they are influenced by wall heating. The POD analysis and spectral analysis provided information about the flow energy and its patterns at different modes and gave a deep insight into the scales and energies of the physical flow structures.…”

Section: Introductionmentioning

confidence: 99%

A POD-Galerkin reduced-order model for isotropic viscoelastic turbulent flow

Chen

Han

et al. 2017

International Communications in Heat and Mass Transfer

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In this article, a proper orthogonal decomposition (POD) reduced-order model for isotropic turbulent flow of viscoelastic fluid is established for the first time. Particularly, since the present studies about viscoleastic fluid are mainly for revealing the mechanism of turbulence, we try to establish the reduced order model for momentum equations and constitutive equations, finally get both velocities and deformation rates calculated. Through decomposing the sampling matrices which are obtained by direct numerical simulation (DNS) using finite volume method (FVM), the velocity basis functions and deformation rate basis functions are generated respectively. According to the Galerkin projection method, the equations for velocity spectrum coefficients and deformation rate spectrum coefficients are deducted, which are coupled pluralistic nonlinear equations and solved iteratively by the Newton-Raphson method. To illustrate the performance of the proposed model for the viscoelastic fluid flow, a two-dimensional decaying isotropic turbulence testing case is designed in Example 1. It is found that the established reduced-order model obtains good accuracy when the decaying flow is at its early stage, but the errors get considerable when the flow steps into transition flow. In addition, a three-dimensional forced isotropic viscoelastic turbulence testing case is designed in Example 2. It is indicated that the errors of viscoelastic forced isotropic turbulent flow are acceptable. Finally, the calculation speed of the established reduced-order model is found to be much faster than that of DNS.

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“…; 17 meanwhile, POD technique was also applied to other applications such as three-dimensional (3D) large-scale structures for drag-reducing flow, 18 the studies of characteristics of wake behind a cylinder, 19,20 and the interactions between the underlying turbulent features in corrugated channel flows. 21 The spread of flux and the diffusion of sulfide ions in molten iron have great influence on the desulfurization efficiency in the process of desulfurization, and there is a close relation between the flow field in the ladle and them, hence it makes sense to study the flow field in the ladle with mechanical stirring. In this article, the information of flow field in three scaled-down models with different conditions was extracted by POD technique from a series of transient data that were obtained by numerical simulation and then the characteristics of POD modes were analyzed and compared.…”

Section: Introductionmentioning

confidence: 99%

Numerical study of flow field on molten iron desulfurization with mechanical stirring

Xiao

Chen

Dan

et al. 2016

Advances in Mechanical Engineering

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The flow field of molten iron in the desulfurization process utilizing the mechanical stirring method under three different conditions was investigated using numerical simulation. The three conditions were central and eccentric stirring with the standard impeller and central stirring with the worn impeller, respectively. Three 1/20-scale numerical models were established and four inspection regions were set up on them. In all, 600 sets of instantaneous velocity fields for each model were exported and proper orthogonal decomposition technique was applied to deal with the data. The macroscopic flow field in the normal model operating under standard conditions was analyzed, which found that the mean flow has a relatively large fluctuation in flow field despite having a high proportion in total kinetic energy. A steady close relationship was revealed between the first two modes by studying the correlation of their coefficients. The first four modes were comparatively analyzed, which reflected that the change in the mean flow in the ladle using a worn impeller is slow and eccentric stirring is beneficial to desulfurization due to the asymmetry of the flow field on two sides.

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Investigation of fundamental flow mechanisms over a corrugated waveform using proper orthogonal decomposition and spectral analyses

Cited by 7 publications

References 21 publications

Prediction of particulate content in oil based on SPA vibration feature selection

Prediction of particulate content in oil based on SPA vibration feature selection

A POD-Galerkin reduced-order model for isotropic viscoelastic turbulent flow

Numerical study of flow field on molten iron desulfurization with mechanical stirring

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