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Published in: Experiments in Fluids 8/2019

01-08-2019 | Research Article

Bivariate 2D empirical mode decomposition for analyzing instantaneous turbulent velocity field in unsteady flows

Authors: Mehdi Sadeghi, Fabrice Foucher, Karim Abed-Meraim, Christine Mounaïm-Rousselle

Published in: Experiments in Fluids | Issue 8/2019

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Abstract

We introduce and demonstrate the bivariate two-dimensional empirical mode decomposition (bivariate 2D-EMD) for the decomposition of a turbulent instantaneous velocity field to separate spatial large-scale organized motion from random turbulent fluctuations. To validate this approach, it was applied to an experimental homogeneous and isotropic turbulent flow (HIT), perturbed by a synthetic Lamb–Oseen vortex that mimics the feature of organized motion. Through different test cases, the scale, the amplitude and the position of the synthetic vortex with respect to the turbulent velocity field were changed. By applying an energy criterion on the modes which resulted from the decomposition process, the initial HIT flow was separated from synthetic perturbation. It is important to point out that in this approach the decomposition as well as the distinction of different parts of the flow are free from any prior and objective assumptions and it requires just one instantaneous velocity field of the flow under analysis. The proposed methodology could be used for analyzing 2D velocity fields obtained from experimental measurement or CFD in different configurations (in-cylinder flow, channel flows, etc.).

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Footnotes
1
The dyadic filter bank decomposes a broad band signal into a collection of successively band-limited components by repeatedly dividing the frequency range.
 
Literature
go back to reference Ahrabian A, Rehman N, Mandic D (2013) Bivariate empirical mode decomposition for unbalanced real-world signals. IEEE Signal Process Lett 20(3):245–248CrossRef Ahrabian A, Rehman N, Mandic D (2013) Bivariate empirical mode decomposition for unbalanced real-world signals. IEEE Signal Process Lett 20(3):245–248CrossRef
go back to reference Bonnet JP, Delville J, Glauser MN, Antonia RA, Bisset DK, Cole DR, Fiedler HE, Garem JH, Hilberg D, Jeong J, Kevlahan NKR, Ukeiley L, Vincendeau E (1998) Collaborative testing of eddy structure identification methods in free turbulent shear flows. Exp Fluids 25:197–225CrossRef Bonnet JP, Delville J, Glauser MN, Antonia RA, Bisset DK, Cole DR, Fiedler HE, Garem JH, Hilberg D, Jeong J, Kevlahan NKR, Ukeiley L, Vincendeau E (1998) Collaborative testing of eddy structure identification methods in free turbulent shear flows. Exp Fluids 25:197–225CrossRef
go back to reference Borée J, Miles P (2014) In-Cylinder Flow. In: Crolla D, Foster DE, Kobayashi T, Vaughan N (eds) Encyclopedia of automotive engineering. Wiley, Chichester Borée J, Miles P (2014) In-Cylinder Flow. In: Crolla D, Foster DE, Kobayashi T, Vaughan N (eds) Encyclopedia of automotive engineering. Wiley, Chichester
go back to reference Brown GL, Roshko A (1974) On density effects and large structure in turbulent mixing layers. J Fluid Mech 64(4):775–816MATHCrossRef Brown GL, Roshko A (1974) On density effects and large structure in turbulent mixing layers. J Fluid Mech 64(4):775–816MATHCrossRef
go back to reference Druault P, Guibert P, Alizon F (2005) Use of proper orthogonal decomposition for time interpolation from PIV data. Exp Fluids 39(6):1009–1023CrossRef Druault P, Guibert P, Alizon F (2005) Use of proper orthogonal decomposition for time interpolation from PIV data. Exp Fluids 39(6):1009–1023CrossRef
go back to reference Ducoin A, Astolfi JA, Deniset F, Sigrist JF (2009) Computational and experimental investigation of flow over a transient pitching hydrofoil. Eur J Mech B Fluids 28(6):728–743MathSciNetMATHCrossRef Ducoin A, Astolfi JA, Deniset F, Sigrist JF (2009) Computational and experimental investigation of flow over a transient pitching hydrofoil. Eur J Mech B Fluids 28(6):728–743MathSciNetMATHCrossRef
go back to reference Epps B (2017) Review of vortex identification methods. In 55th AIAA aerospace sciences meeting, p 0989 Epps B (2017) Review of vortex identification methods. In 55th AIAA aerospace sciences meeting, p 0989
go back to reference Farge M, Schneider K, Kevlahan N (1999) Non-Gaussianity and coherent vortex simulation for two-dimensional turbulence using an adaptive orthogonal wavelet basis. Phys Fluids 11(8):2187–2201MathSciNetMATHCrossRef Farge M, Schneider K, Kevlahan N (1999) Non-Gaussianity and coherent vortex simulation for two-dimensional turbulence using an adaptive orthogonal wavelet basis. Phys Fluids 11(8):2187–2201MathSciNetMATHCrossRef
go back to reference Farge M, Pellegrino G, Schneider K (2001) Coherent vortex extraction in 3D turbulent flows using orthogonal wavelets. Phys Rev Lett 87(5):054501CrossRef Farge M, Pellegrino G, Schneider K (2001) Coherent vortex extraction in 3D turbulent flows using orthogonal wavelets. Phys Rev Lett 87(5):054501CrossRef
go back to reference Feynman J, Ruzmaikin A (2014) The centennial gleissberg cycle and its association with extended minima. J Geophys Res Space Phys 119(8):6027–6041CrossRef Feynman J, Ruzmaikin A (2014) The centennial gleissberg cycle and its association with extended minima. J Geophys Res Space Phys 119(8):6027–6041CrossRef
go back to reference Fiedler HE (1998) Control of free turbulent shear flows. Flow control. Springer, Berlin, pp 335–429CrossRef Fiedler HE (1998) Control of free turbulent shear flows. Flow control. Springer, Berlin, pp 335–429CrossRef
go back to reference Flandrin P (1998) Time-frequency/time-scale analysis, vol 10. Academic Press, CambridgeMATH Flandrin P (1998) Time-frequency/time-scale analysis, vol 10. Academic Press, CambridgeMATH
go back to reference Flandrin P, Rilling G, Goncalves P (2004) Empirical mode decomposition as a filter bank. Signal Process Lett IEEE 11(2):112–114CrossRef Flandrin P, Rilling G, Goncalves P (2004) Empirical mode decomposition as a filter bank. Signal Process Lett IEEE 11(2):112–114CrossRef
go back to reference Foucher F, Ravier P (2010) Determination of turbulence properties by using empirical mode decomposition on periodic and random perturbed flows. Exp Fluids 49(2):379–390CrossRef Foucher F, Ravier P (2010) Determination of turbulence properties by using empirical mode decomposition on periodic and random perturbed flows. Exp Fluids 49(2):379–390CrossRef
go back to reference Foucher F, Landry L, Halter F, Mounaïm-Rousselle C (2008) Turbulent flow fields analysis of a spark-ignition engine as function of the boosted pressure. In: 14th international symposium on laser techniques to fluid mechanics Foucher F, Landry L, Halter F, Mounaïm-Rousselle C (2008) Turbulent flow fields analysis of a spark-ignition engine as function of the boosted pressure. In: 14th international symposium on laser techniques to fluid mechanics
go back to reference Franzke CL (2014) Warming trends: nonlinear climate change. Nat Clim Change 4(6):423CrossRef Franzke CL (2014) Warming trends: nonlinear climate change. Nat Clim Change 4(6):423CrossRef
go back to reference Galmiche B, Mazellier N, Halter F, Foucher F (2014) Turbulence characterization of a high-pressure high-temperature fan-stirred combustion vessel using LDV, PIV and TR-PIV measurements. Exp Fluids 55(1):1636CrossRef Galmiche B, Mazellier N, Halter F, Foucher F (2014) Turbulence characterization of a high-pressure high-temperature fan-stirred combustion vessel using LDV, PIV and TR-PIV measurements. Exp Fluids 55(1):1636CrossRef
go back to reference Guanlei X, Xiaotong W, Xiaogang X (2009) Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures. Pattern Recognit 42(5):718–734MATHCrossRef Guanlei X, Xiaotong W, Xiaogang X (2009) Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures. Pattern Recognit 42(5):718–734MATHCrossRef
go back to reference Hemakom A, Ahrabian A, Looney D, Rehman NU, Mandic DP (2015) Nonuniformly sampled trivariate empirical mode decomposition. In: Acoustics, speech and signal processing (ICASSP) IEEE international conference on, pp 3691–3695 Hemakom A, Ahrabian A, Looney D, Rehman NU, Mandic DP (2015) Nonuniformly sampled trivariate empirical mode decomposition. In: Acoustics, speech and signal processing (ICASSP) IEEE international conference on, pp 3691–3695
go back to reference Hemakom A, Goverdovsky V, Looney D, Mandic DP (2016) Adaptive projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications. Philos Trans R Soc A Math Phys Eng Sci 374(2065):20150199CrossRef Hemakom A, Goverdovsky V, Looney D, Mandic DP (2016) Adaptive projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications. Philos Trans R Soc A Math Phys Eng Sci 374(2065):20150199CrossRef
go back to reference Hotelling H (1933) Analysis of a complex of statistical variables into principal components. J Educ Psychol 24(6):417MATHCrossRef Hotelling H (1933) Analysis of a complex of statistical variables into principal components. J Educ Psychol 24(6):417MATHCrossRef
go back to reference Huang NE, Attoh-Okine NO (2005) The Hilbert-Huang transform in engineering. CRC Press, Boca RatonMATHCrossRef Huang NE, Attoh-Okine NO (2005) The Hilbert-Huang transform in engineering. CRC Press, Boca RatonMATHCrossRef
go back to reference Huang NE, Shen Z, Lon SR, Wu MC, Shih HH, Zheng Q, Liu HH (1998) The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond Ser A Math Phys Eng Sci 454(1971):903–995MathSciNetMATHCrossRef Huang NE, Shen Z, Lon SR, Wu MC, Shih HH, Zheng Q, Liu HH (1998) The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond Ser A Math Phys Eng Sci 454(1971):903–995MathSciNetMATHCrossRef
go back to reference Huang NE, Shen Z, Long SR (1999) A new view of nonlinear water waves: the Hilbert spectrum. Annu Rev Fluid Mech 31(1):417–457MathSciNetCrossRef Huang NE, Shen Z, Long SR (1999) A new view of nonlinear water waves: the Hilbert spectrum. Annu Rev Fluid Mech 31(1):417–457MathSciNetCrossRef
go back to reference Huang YX, Schmitt FG, Lu ZM, Liu YL (2008) An amplitude frequency study of turbulent scaling intermittency using empirical mode decomposition and Hilbert spectral analysis. EPL (Europhys Lett) 84(4):40010CrossRef Huang YX, Schmitt FG, Lu ZM, Liu YL (2008) An amplitude frequency study of turbulent scaling intermittency using empirical mode decomposition and Hilbert spectral analysis. EPL (Europhys Lett) 84(4):40010CrossRef
go back to reference Lewalle J, Delville J, Bonnet JP (2000) Decomposition of mixing layer turbulence into coherent structures and background fluctuations. Flow Turbul Combust 64(9):301–328MATHCrossRef Lewalle J, Delville J, Bonnet JP (2000) Decomposition of mixing layer turbulence into coherent structures and background fluctuations. Flow Turbul Combust 64(9):301–328MATHCrossRef
go back to reference Liang H, Lin QH, Chen JDZ (2005) Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease. IEEE Trans Biomed Eng 52(10):1692–1701CrossRef Liang H, Lin QH, Chen JDZ (2005) Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease. IEEE Trans Biomed Eng 52(10):1692–1701CrossRef
go back to reference Linderhed A (2009) Image empirical mode decomposition: a new tool for image processing. Adv Adapt Data Anal World Sci Publ Co 1(02):265–294MathSciNetCrossRef Linderhed A (2009) Image empirical mode decomposition: a new tool for image processing. Adv Adapt Data Anal World Sci Publ Co 1(02):265–294MathSciNetCrossRef
go back to reference Lumley JL (1967) The structure of inhomogeneous turbulent flows. In: Yalgom AM, Tatarski VI (eds) Atmospheric turbulence and wave propagation. Nauka, Moscow, pp 166–178 Lumley JL (1967) The structure of inhomogeneous turbulent flows. In: Yalgom AM, Tatarski VI (eds) Atmospheric turbulence and wave propagation. Nauka, Moscow, pp 166–178
go back to reference Lumley JL (2001) Early work on fluid mechanics in the IC engine. Annu Rev Fluid Mech 33(1):319–338MATHCrossRef Lumley JL (2001) Early work on fluid mechanics in the IC engine. Annu Rev Fluid Mech 33(1):319–338MATHCrossRef
go back to reference Mandic DP, Rehman N, Wu Z, Huang NE (2013) Empirical mode decomposition-based time-frequency analysis of multivariate signals: the power of adaptive data analysis. IEEE Signal Process Mag 30(6):74–86CrossRef Mandic DP, Rehman N, Wu Z, Huang NE (2013) Empirical mode decomposition-based time-frequency analysis of multivariate signals: the power of adaptive data analysis. IEEE Signal Process Mag 30(6):74–86CrossRef
go back to reference Mazellier N, Foucher F (2011) Separation between coherent and turbulent fluctuations: what can we learn from the empirical mode decomposition? Exp Fluids 51(2):527–541CrossRef Mazellier N, Foucher F (2011) Separation between coherent and turbulent fluctuations: what can we learn from the empirical mode decomposition? Exp Fluids 51(2):527–541CrossRef
go back to reference Nunes JC, Guyot Y, Delechelle E (2005) Texture analysis based on local analysis of the bidimensional empirical mode decomposition. Mach Vis Appl 16(3):177–188CrossRef Nunes JC, Guyot Y, Delechelle E (2005) Texture analysis based on local analysis of the bidimensional empirical mode decomposition. Mach Vis Appl 16(3):177–188CrossRef
go back to reference Pearson K (1901) LIII. On lines and planes of closest fit to systems of points in space. Lond Edinb Dublin Philos Mag J Sci 2(11):559–572MATHCrossRef Pearson K (1901) LIII. On lines and planes of closest fit to systems of points in space. Lond Edinb Dublin Philos Mag J Sci 2(11):559–572MATHCrossRef
go back to reference Rehman N, Mandic DP (2011) Filter bank property of multivariate empirical mode decomposition. IEEE Trans Signal Process 59(5):2421–2426MathSciNetMATHCrossRef Rehman N, Mandic DP (2011) Filter bank property of multivariate empirical mode decomposition. IEEE Trans Signal Process 59(5):2421–2426MathSciNetMATHCrossRef
go back to reference Rehman N, Looney D, Rutkowski TM, Mandic DP (2009) Bivariate EMD-based image fusion. In: Statistical signal processing, 2009. SSP’09. IEEE/SP 15th workshop on. IEEE, pp 57–60 Rehman N, Looney D, Rutkowski TM, Mandic DP (2009) Bivariate EMD-based image fusion. In: Statistical signal processing, 2009. SSP’09. IEEE/SP 15th workshop on. IEEE, pp 57–60
go back to reference Rehman N, Park C, Huang NE, Mandic DP (2013) EMD via MEMD: multivariate noise-aided computation of standard EMD. Adv Adapt Data Anal 5(02):1350007MathSciNetCrossRef Rehman N, Park C, Huang NE, Mandic DP (2013) EMD via MEMD: multivariate noise-aided computation of standard EMD. Adv Adapt Data Anal 5(02):1350007MathSciNetCrossRef
go back to reference Rehman N, Ehsan S, Abdullah SMU, Akhtar MJ, Mandic DP, McDonald-Maier KD (2015) Multi-scale pixel-based image fusion using multivariate empirical mode decomposition. Sensors 15(5):10923–11094CrossRef Rehman N, Ehsan S, Abdullah SMU, Akhtar MJ, Mandic DP, McDonald-Maier KD (2015) Multi-scale pixel-based image fusion using multivariate empirical mode decomposition. Sensors 15(5):10923–11094CrossRef
go back to reference Reynolds WC, Hussain AKMF (1972) The mechanics of an organized wave in turbulent shear flow. Part 3. Theoretical models and comparisons with experiments. J Fluid Mech 54(2):263–288CrossRef Reynolds WC, Hussain AKMF (1972) The mechanics of an organized wave in turbulent shear flow. Part 3. Theoretical models and comparisons with experiments. J Fluid Mech 54(2):263–288CrossRef
go back to reference Rilling G, Flandrin P, Goncalves P, Lilly JM (2007) Bivariate empirical mode decomposition. Signal Process Lett 14(12):936–939CrossRef Rilling G, Flandrin P, Goncalves P, Lilly JM (2007) Bivariate empirical mode decomposition. Signal Process Lett 14(12):936–939CrossRef
go back to reference Roudnitzky S, Druault P, Guibert P (2006) Proper orthogonal decomposition of in-cylinder engine flow into mean component, coherent structures and random Gaussian fluctuations. J Turbul 7:1–19MathSciNetCrossRef Roudnitzky S, Druault P, Guibert P (2006) Proper orthogonal decomposition of in-cylinder engine flow into mean component, coherent structures and random Gaussian fluctuations. J Turbul 7:1–19MathSciNetCrossRef
go back to reference Sadeghi M, Foucher F, Abed-Meraim K, Mounaïm-Rousselle C (2016) Analysis of the bivariate EMD behavior for separating coherent structures from interference fluctuations in isotropic homogeneous turbulence. In: Progress in turbulence VI, pp 97–103 Sadeghi M, Foucher F, Abed-Meraim K, Mounaïm-Rousselle C (2016) Analysis of the bivariate EMD behavior for separating coherent structures from interference fluctuations in isotropic homogeneous turbulence. In: Progress in turbulence VI, pp 97–103
go back to reference Wang YH, Yeh CH, Young HWV, Hu K, Lo MT (2014) On the computational complexity of the empirical mode decomposition algorithm. Phys A 400:159–167CrossRef Wang YH, Yeh CH, Young HWV, Hu K, Lo MT (2014) On the computational complexity of the empirical mode decomposition algorithm. Phys A 400:159–167CrossRef
go back to reference Wu Z, Huang NE (2004) A study of the characteristics of white noise using the empirical mode decomposition method. Proc R Soc Lond Ser A Math Phys Eng Sci 460(2046):1597–1611MATHCrossRef Wu Z, Huang NE (2004) A study of the characteristics of white noise using the empirical mode decomposition method. Proc R Soc Lond Ser A Math Phys Eng Sci 460(2046):1597–1611MATHCrossRef
go back to reference Wu Z, Huang NE (2009) Ensemble empirical mode decomposition: a noise assisted data analysis method. Adv Adapt Data Anal 1(01):1–41CrossRef Wu Z, Huang NE (2009) Ensemble empirical mode decomposition: a noise assisted data analysis method. Adv Adapt Data Anal 1(01):1–41CrossRef
go back to reference Wu Z, Huang NE, Chen X (2009) The multi-dimensional ensemble empirical mode decomposition method. Adv Adapt Data Anal 1(03):339–372MathSciNetCrossRef Wu Z, Huang NE, Chen X (2009) The multi-dimensional ensemble empirical mode decomposition method. Adv Adapt Data Anal 1(03):339–372MathSciNetCrossRef
go back to reference Wu CH, Chang HC, Lee PL, Li KS, Sie JJ, Sun CW, Yang C, Li PH, Deng HT, Shyu KK (2011) Frequency recognition in an SSVEP-based brain computer interface using empirical mode decomposition and refined generalized zero-crossing. J Neurosci Methods 196(1):170–181CrossRef Wu CH, Chang HC, Lee PL, Li KS, Sie JJ, Sun CW, Yang C, Li PH, Deng HT, Shyu KK (2011) Frequency recognition in an SSVEP-based brain computer interface using empirical mode decomposition and refined generalized zero-crossing. J Neurosci Methods 196(1):170–181CrossRef
go back to reference Zhou Y, Chen W, Gao J, He Y (2012) Application of Hilbert–Huang transform based instantaneous frequency to seismic reflection data. J Appl Geophys 82:68–74CrossRef Zhou Y, Chen W, Gao J, He Y (2012) Application of Hilbert–Huang transform based instantaneous frequency to seismic reflection data. J Appl Geophys 82:68–74CrossRef
Metadata
Title
Bivariate 2D empirical mode decomposition for analyzing instantaneous turbulent velocity field in unsteady flows
Authors
Mehdi Sadeghi
Fabrice Foucher
Karim Abed-Meraim
Christine Mounaïm-Rousselle
Publication date
01-08-2019
Publisher
Springer Berlin Heidelberg
Published in
Experiments in Fluids / Issue 8/2019
Print ISSN: 0723-4864
Electronic ISSN: 1432-1114
DOI
https://doi.org/10.1007/s00348-019-2775-5

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