Skip to main content
Log in

Spectral analysis on the component characteristics of wake systems generated by the submerged body

  • Original article
  • Published:
Journal of Marine Science and Technology Aims and scope Submit manuscript

Abstract

The flow physics around the underwater target and its direct interaction with the flexible free surface are the important prerequisite to non-acoustic detection technology, such as Synthetic Aperture Radar (SAR), optical measurement methods or infrared detection. How the structure of wake pattern changes over frequency in the spectral domain is the objective that can promote the applications of these new approaches and it plays a crucial role in better understanding of the relationship between free surface disturbances and the motion state of the submerged body. The existing data of wave height from Computational Fluid Dynamics (CFD) is transferred to a series of discrete nodes with evenly spaced increments through the data interpolation. Based on a joint analysis of 2D Fast Fourier Transform (FFT) and the dispersion relation, the X-shaped representation of submerged body wakes are identified in the wavenumber space, together with the curves of the dispersion relation so as to validate the correctness of the computational procedures. Then a decomposition of the wake system is performed, including the contribution of the near-field Bernoulli hump and far-field Kelvin wave, these two components can be separately reconstructed in the spatial domain using the Inverse Fast Fourier Transform (IFFT). The distance between the first two maximum peaks of the Bernoulli hump is given and the relationship with the Froude number (Fn) is also discussed. Finally, the 1D-Power Spectral Density (PSD) is available to describe the frequency components and proportion of the components. The results lead to a further understanding of the roles of wake components and the motion state of underwater target.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Data availability

The authors will supply the relevant data in response to reasonable requests.

Abbreviations

SAR:

Synthetic aperture radar

CFD:

Computational fluid dynamics

EFD:

Experimental fluid dynamics

FFT:

Fast Fourier transform

IFFT:

Inverse fast Fourier transform

PSD:

Power spectral density

RANS:

Reynolds averaged Navier Stokes

VOF:

Volume of fluid

h :

Depth of the submerged body

L :

Length of the submerged body

D :

Maximum diameter of the submerged body

k :

Turbulence kinetic energy

h*:

Non-dimensional depth

U :

Velocity of the freestream

kc :

Cutoff wavenumber

Fn:

Length Froude number

Fr:

Depth Froude number

C T :

Normalized resistance force

e :

Base size of the meshes

Re:

Reynolds number

Δt:

Time step

Δx, Δy:

Sample interval in x and y directions

M, N :

Sample number in x and y directions

Cp:

Pressure coefficient

ε :

Dissipation rate

q*:

Normalized amplitude of 2D-FFT

References

  1. Liu Y, Deng R, Zhao J (2019) Simulation of Kelvin wakes in optical images of rough sea surface. Appl Ocean Res 89:36–43

    Article  Google Scholar 

  2. Rabaud M, Moisy F (2014) Narrow ship wakes and wave drag for planing hulls. Ocean Eng 90:34–38

    Article  Google Scholar 

  3. Amiri MM, Sphaier SH, Vitola MA, Esperança PT (2019) URANS investigation of the interaction between the free surface and a shallowly submerged underwater vehicle at steady drift. Appl Ocean Res 84:192–205

    Article  Google Scholar 

  4. Issa V, Daya Z (2018) Modeling the ship white water wake in the midwave infrared. Appl Optics 57:10125

    Article  Google Scholar 

  5. Torsvik T, Soomere T, Didenkulova I, Sheremet A (2015) Identification of ship wake structures by a time–frequency method. J Fluid Mech 765:229–251

    Article  Google Scholar 

  6. Liu T, Guo Z (2013) Analysis of wave spectrum for submerged bodies moving near the free surface. Ocean Eng 58:239–251

    Article  Google Scholar 

  7. Gomit G, Rousseaux G, Chatellier L, Calluaud D, David L (2014) Spectral analysis of ship waves in deep water from accurate measurements of the free surface elevation by optical methods. Phys Fluids 26(122101):1–11

    Google Scholar 

  8. Liu P, Qiu J (2017) Simulation of synthetic aperture radar imaging of dynamic wakes of submerged body. IET Radar Sonar Navig 11(3):481–489

    Article  MathSciNet  Google Scholar 

  9. Xue F, Jin W, Qiu S, Yang J (2020) Wake features of moving submerged bodies and motion state inversion of submarines. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2966005

    Article  Google Scholar 

  10. Liu K, Wang K, Wang Y, Li Y (2020) Numerical simulation in time domain to study cross-flow VIV of catenary riser subject to vessel motion-induced oscillatory current. Int J Naval Arch Ocean Eng 12:491–500

    Article  Google Scholar 

  11. Sun Q, Yan W-J, Ren W-X (2021) Analytical investigation into error propagation of power spectral density transmissibility (PSDT) based on coherence function. J Sound Vib 514:116429

    Article  Google Scholar 

  12. Czifra Á, Goda T, Garbayo E (2011) Surface characterisation by parameter-based technique, slicing method and PSD analysis. Measurement 44:906–916

    Article  Google Scholar 

  13. Li Q, Deng Y, Li J, Shi W (2020) Roughness characterization and formation mechanism of abrasive air jet micromachining surface studied by power spectral density. J Manuf Process 57:737–747

    Article  Google Scholar 

  14. Marrocco V, Modica F, Fassi I (2019) Analysis of discharge pulses in micro-EDM milling of Si3N4-TiN composite workpiece by means of power spectral density (PSD). J Manuf Process 43:112–118

    Article  Google Scholar 

  15. Tao T, Wang H (2019) Modelling of longitudinal evolutionary power spectral density of typhoon winds considering high-frequency subrange. J Wind Eng Industrial Aerodyn 193:103957

    Article  Google Scholar 

  16. Sun Y, Liu P, Jin Y (2018) Ship wake components: isolation, reconstruction, and characteristics analysis in spectral, spatial, and TerraSAR-X image domains. IEEE Trans Geosci Remote Sens 56:4209–4224

    Article  Google Scholar 

  17. Lateb M, Masson C, Stathopoulos T, Bédard C (2013) Comparison of various types of k–ε models for pollutant emissions around a two-building configuration. J Wind Eng Ind Aerodyn 115:9–21

    Article  Google Scholar 

  18. Dong K, Wang X, Zhang D et al (2022) CFD research on the hydrodynamic performance of submarine sailing near the free surface with long-crested Waves. J Marine Sci Eng 10(1):90

    Article  Google Scholar 

  19. Groves.N.C, Huang, T.T. Geometric Characteristics of DARPA (Defense Advanced Research Projects Agency) SUBOFF Models (DTRC Model Numbers 5470 and 5471). DTRC/SHD-1298–01. 1989.

  20. Gonzalez-Martinez JF, Nieto Carvajal I, Abad J, Colchero J (2012) Nanoscale measurement of the power spectral density of surface roughness: how to solve a difficult experimental challenge. Nanoscale Res Lett 7:174

    Article  Google Scholar 

  21. Sudharsun G, Ali A, Mitra A et al (2022) Free surface features of submarines moving underwater: study of Bernoulli hump. Ocean Eng 249:110792

    Article  Google Scholar 

  22. Jaiswal AK, Sudharsun G, Warrior HV (2022) Detection of ships moving in a straight line and turning with implications for wide area surveillance. Int J Naval Arch Ocean Eng 14:100452

    Article  Google Scholar 

  23. Barman J, Kumar A, Warrior HV (2018) Wide area surveillance using ship wakes. Curr Sci 114:1606–1607

    Article  Google Scholar 

Download references

Funding

This work is financially supported by the National Natural Science Foundation of China (Grand No. 62181275, 62171245), Shandong Provincial Natural Science Foundation (Grand No. ZR2020QA045, Grant No. ZR2021MD106), Laoshan Laboratory Science and Technology Innovation Project (Grant No. LSKJ202204704).

Author information

Authors and Affiliations

Authors

Contributions

DL: investigation, writing-original draft, software. ZW: software, data curation, funding acquisition. CH: writing–review & editing, Funding acquisition. YX: FFT program, Interpolation. YZ: post-processing, revision.

Corresponding author

Correspondence to Dong Li.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 4762 KB)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, D., Wang, Z., He, C. et al. Spectral analysis on the component characteristics of wake systems generated by the submerged body. J Mar Sci Technol 28, 583–596 (2023). https://doi.org/10.1007/s00773-023-00942-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00773-023-00942-9

Keywords

Navigation