Hostname: page-component-76d6cb85b7-rxvq6 Total loading time: 0 Render date: 2026-07-10T03:09:22.775Z Has data issue: false hasContentIssue false
  • English
  • Français

Modal analysis of the wake past a marine propeller

Published online by Cambridge University Press:  19 September 2018

Francesca Magionesi ,
Giulio Dubbioso ,
Roberto Muscari Open the ORCID record for Roberto Muscari [Opens in a new window]  and
Andrea Di Mascio
Francesca Magionesi*
Affiliation:
CNR-INSEAN, via di Vallerano 139, 00128 Roma, Italy
Giulio Dubbioso
Affiliation:
CNR-INSEAN, via di Vallerano 139, 00128 Roma, Italy
Roberto Muscari
Affiliation:
CNR-INSEAN, via di Vallerano 139, 00128 Roma, Italy
Andrea Di Mascio
Affiliation:
CNR-IAC, via dei Taurini 19, 00185 Roma, Italy
*
†Email address for correspondence: francesca.magionesi@cnr.it
Get access Rights & Permissions [Opens in a new window]

Abstract

Modal decomposition techniques are used to analyse the wake field past a marine propeller achieved by previous numerical simulations (Muscari et al. Comput. Fluids, vol. 73, 2013, pp. 65–79). In particular, proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) are used to identify the most energetic modes and those that play a dominant role in the inception of the destabilization mechanisms. Two different operating conditions, representative of light and high loading conditions, are considered. The analysis shows a strong dependence of temporal and spatial scales of the process on the propeller loading and correlates the spatial shape of the modes and the temporal scales with the evolution and destabilization mechanisms of the wake past the propeller. At light loading condition, due to the stable evolution of the wake, both POD and DMD describe the flow field by the non-interacting evolution of the tip and hub vortex. The flow is mainly associated with the ordered convection of the tip vortex and the corresponding dominant modes, identified by both decompositions, are characterized by spatial wavelengths and frequencies related to the blade passing frequency and its multiples, whereas the dynamic of the hub vortex has a negligible contribution. At high loading condition, POD and DMD identify a marked separation of the flow field close to the propeller and in the far field, as a consequence of wake breakdown. The tonal modes are prevalent only near to the propeller, where the flow is stable; on the contrary, in the transition region a number of spatial and temporal scales appear. In particular, the phenomenon of destabilization of the wake, originated by the coupling of consecutive tip vortices, and the mechanisms of hub–tip vortex interaction and wake meandering are identified by both POD and DMD.

JFM classification

Nonlinear Dynamical Systems: Low-dimensional models Vortex Flows: Vortex dynamics Wakes/Jets: Wakes

Information

Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 855 , 25 November 2018 , pp. 469 - 502
Check for updates
Copyright
© 2018 Cambridge University Press 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Ashton, R., Viola, F., Camarri, S., Gallaire, F. & Iungo, G. V. 2016 Hub vortex instability within wind turbine wakes: effects of wind turbulence, loading conditions and blade aerodynamics. Phys. Rev. Fluids 1, 1–18.Google Scholar
Bastine, D., Vollmer, L., Wächter, M. & Peinke, J. 2018 Stochastic wake modelling based on POD analysis. Energies 11 (3), 1–29.Google Scholar
Berkooz, G., Holmes, P. & Lumley, J. L. 1993 The proper orthogonal decomposition in the analysis of turbulent flows. Annu. Rev. Fluid Mech. 25, 539–575.Google Scholar
Chen, K. K., Tu, J. H. & Rowley, C. W. 2012 Variants of dynamic mode decomposition: boundary condition, Koopman, and Fourier analyses. J. Nonlinear Sci. 22 (6), 887–915.Google Scholar
Conlisk, A. T. 2001 Modern helicopter rotor aerodynamics. Prog. Aerosp. Sci. 37 (5), 419–476.Google Scholar
Debnath, M., Santoni, C., Leonardi, S. & Iungo, G. V. 2017 Towards reduced order modeling for predicting the dynamics of coherent vorticity structures within wind turbine wake. Phil. Trans. R. Soc. Lond. A 375, 1–14.Google Scholar
Di Felice, F., Di Florio, D., Felli, M. & Romano, G. P. 2004 Experimental investigation of the propeller wake at different loading conditions by particle image velocimetry. J. Ship Res. 48 (2), 168–190.Google Scholar
Di Mascio, A., Muscari, R. & Dubbioso, G. 2014 On the wake dynamics of a propeller operating in drift. J. Fluid Mech. 754, 263–307.Google Scholar
Felli, M., Camussi, R. & Di Felice, F. 2011 Mechanisms of evolution of the propeller wake in the transition and far fields. J. Fluid Mech. 682, 5–53.Google Scholar
Felli, M. & Di Felice, F. 2005 Propeller wake analysis in nonuniform inflow by LDV phase sampling techniques. J. Mar. Sci. Technol. 10, 159–172.Google Scholar
Felli, M., Falchi, M. & Dubbioso, G. 2015 Hydrodynamic and hydroacoustic analysis of a marine propeller wake by TOMO-PIV. In Proceedings of the Fourth International Symposium on Marine Propulsors (SMP’15), Austin, Texas, USA. SMP.Google Scholar
Freund, J. B. & Colonius, T. 2009 Turbulence and sound–field POD analysis of a turbulent jet. Intl J. Aeroacoust. 8 (4), 337–354.Google Scholar
Grigoropoulos, G., Campana, E. F., Diez, M., Serani, A., Goren, O., Sarioz, K., Danisman, D. B., Visonneau, M., Queutey, P. & Abdel-Maksoud, M. 2017 Mission-based hull-form and propeller optimization of a transom stern destroyer for best performance in the sea environment. In Proceedings of the VII International Congress on Computational Methods in Marine Engineering (MARINE’17). CIMNE.Google Scholar
Gupta, B. P. & Loewy, R. G. 1974 Theoretical analysis of the aerodynamic stability of multiple, interdigitated helical vortices. AIAA J. 12 (10), 1381–1387.Google Scholar
Holmes, P., Lumley, J. L., Berkooz, G. & Rowley, C. W. 2012 Turbulence, Coherent Structures, Dynamical Systems and Symmetry. Cambridge University Press.Google Scholar
Ianniello, S. 2016 The Ffowcs Williams–Hawkings equation for hydroacoustic analysis of rotating blades. Part 1. The rotpole. J. Fluid Mech. 797, 345–388.Google Scholar
Ianniello, S., Muscari, R. & Di Mascio, A. 2013 Ship underwater noise assessment by the acoustic analogy. Part I. Nonlinear analysis of a marine propeller in a uniform flow. J. Mar. Sci. Technol. 18, 547–570.Google Scholar
Iungo, G. V., Santoni-Ortiz, C., Abkar, M., Porté-Agel, F., Rotea, M. A. & Leonardi, S. 2015 Data-driven reduced order model for prediction of wind turbine wakes. J. Phys.: Conf. Ser. 625 (1), 012009.Google Scholar
Iungo, G. V., Viola, F., Camarri, S., Porté-Agel, F. & Gallaire, F. 2013 Linear stability analysis of wind turbine wakes performed on wind tunnel measurements. J. Fluid Mech. 737, 499–526.Google Scholar
Jeong, J. & Hussain, F. 1995 On the identification of a vortex. J. Fluid Mech. 285, 69–94.Google Scholar
Jovanović, M. R., Schmid, P. J. & Nichols, J. W. 2014 Sparsity-promoting dynamic mode decomposition. Phys. Fluids 26 (2), 1–22.Google Scholar
Kumar, P. & Mahesh, K. 2015 Analysis of marine propulsor in crashback using large eddy simulations. In Proceedings of the Fourth International Symposium on Marine Propulsors (SMP’15). Austin, Texas, USA. SMP.Google Scholar
Kumar, P. & Mahesh, K. 2017 Large eddy simualtion of propeller wake instabilities. J. Fluid Mech. 814, 361–396.Google Scholar
Lumley, J. L. 1970 Stochastic Tools in Turbulence. Academic Press.Google Scholar
Muld, T. W., Efraimsson, G. & Henningson, D. S. 2012 Mode decomposition on surface–mounted cube. Flow Turbul. Combust. 88 (3), 279–310.Google Scholar
Muscari, R., Di Mascio, A. & Verzicco, R. 2013 Modeling of vortex dynamics in the wake of a marine propeller. Comput. Fluids 73, 65–79.Google Scholar
Newland, D. E. 1993 An Introduction to Random Vibrations, Spectral and Wavelet Analysis, 3rd edn. Longman.Google Scholar
Oberleithner, K., Sieber, M., Nayeri, C. N., Paschereit, C. O., Petz, C., Hege, H. C., Noack, B. R. & Wygnanski, I. 2011 Three-dimensional coherent structures in a swirling jet undergoing vortex breakdown: stability analysis and empirical mode construction. J. Fluid Mech. 679, 383–414.Google Scholar
Okulov, V. L. 2004 On the stability on multiple helical vortices. J. Fluid Mech. 521, 319–342.Google Scholar
Okulov, V. L. & Sørensen, J. N. 2007 Stability of helical tip vortices in rotor far wake. J. Fluid Mech. 576, 1–25.Google Scholar
Paik, B., Kim, K., Lee, J. & Lee, S. 2010 Analysis of unstable vortical structure in a propeller wake affected by a simulated hull wake. Exp. Fluids 48 (6), 1121–1133.Google Scholar
Rempfer, D. & Fasel, H. F. 1994 Evolution of three-dimensional coherent structures in a flat-plate boundary layer. J. Fluid Mech. 260, 351–375.Google Scholar
Roache, P. J. 1997 Quantification of uncertainty in computational fluid dynamics. Annu. Rev. Fluid Mech. 29, 123–160.Google Scholar
Rowley, C. W. & Dawson, S. T. M. 2017 Model reduction for flow analysis and control. Annu. Rev. Fluid Mech. 49, 387–417.Google Scholar
Rowley, C. W., Mezic, I., Bagheri, S., Schlatter, P. & Henningson, D. S. 2009 Spectral analysis of nonlinear flows. J. Fluid Mech. 641, 115–127.Google Scholar
Salvatore, F., Pereira, F., Felli, M., Calcagni, D. & Di Felice, F.2006 Description of the INSEAN E779A propeller experimental dataset. INSEAN Tech. Rep. 2006-085.Google Scholar
Sarmast, S., Dadfar, R., Mikkelsen, R. F., Schlatter, P., Ivanelli, S., Sørensen, J. N. & Henningson, D. S. 2014 Mutual inductance instability of the tip vortices behind a wind turbine. J. Fluid Mech. 755, 705–731.Google Scholar
Schmid, P. J. 2010 Dynamic mode decomposition of numerical and experimental data. J. Fluid Mech. 656, 5–28.Google Scholar
Schmid, P. J., Violato, D. & Scarano, F. 2012 Decomposition of time-resolved tomographic PIV. Exp. Fluids 52, 1567–1579.Google Scholar
Semeraro, O., Bellani, G. & Lundell, F. 2012 Analysis of time–resolved PIV measurements of a confined turbulent jet using POD and Koopman modes. Exp. Fluids 53, 1203–1220.Google Scholar
Sirovich, L. 1987 Turbulence and the dynamics of coherent structures. Part I–III. Q. Appl. Maths 45 (3), 561–590.Google Scholar
Sørensen, J. N. 2011 Instability of helical tip vortices in rotor wakes. J. Fluid Mech. 682, 1–4.Google Scholar
Spalart, P. R. 2009 Detached eddy simulation. Annu. Rev. Fluid Mech. 41, 181–202.Google Scholar
Statnikov, V., Meinke, M. & Schröder, W. 2017 Reduced-order analysis of buffet flow of space launchers. J. Fluid Mech. 815, 1–25.Google Scholar
Vermeer, L. J., Sørensen, J. N. & Crespo, A. 2003 Wind turbine wake aerodynamics. Prog. Aerosp. Sci. 39 (6–7), 467–510.Google Scholar
Viola, F., Iungo, G. V., Camarri, S., Porté-Agel, F. & Gallaire, F. 2014 Prediction of the hub vortex instability in a wind turbine wake: stability analysis with eddy–viscosity models calibrated on wind tunnel data. J. Fluid Mech. 750, R1.Google Scholar
Widnall, S. E. 1972 The stability of a helical vortex filament. J. Fluid Mech. 54 (4), 641–663.Google Scholar
Wood, D. H. & Boersma, J. 2001 On the motion of multiple helical vortices. J. Fluid Mech. 447, 149–171.Google Scholar