Advertisement

Modeling the Directivity of Wheel/Rail Radiation Using a Circular/Straight Line of Perpendicular Dipole Pairs

  • Xuetao Zhang
Part of the Notes on Numerical Fluid Mechanics and Multidisciplinary Design book series (NNFM, volume 118)

Summary

Former measurement investigation on the directivity of wheel/rail radiation has specified that (1) rail radiation is of dipole directivity characteristic in the horizontal direction, whilst it is only about 4 dB more directional than a monopole source in a vertical plane perpendicular to the rail; (2) the directivity of wheel radiation is close to the vertical directivity of rail radiation.

The work presented in this paper intends to interpret the phenomenon. It is found that a model of a perpendicular dipole pair can explain these directivity characteristics specified by the measurement. This model naturally explains why rail radiation has different horizontal and vertical directivity characteristics and why wheel radiation is not a dipole source (at least for wheels with a curved web). The study also emphasizes that, when considering the directivity effect of a dipole source, the orientation of the dipole axis needs to be specified. Moreover when more than one dipole is concerned, a special disposition of the dipoles together with a selection of difference in their sound powers can result in a change of directivity pattern from that of a monopole to that of a dipole.

Since rail radiation dominates at low speed whilst wheel radiation becomes more important at high speed, the horizontal directivity of rolling noise varies with train speed. Therefore, this work on the directivity can help with to construct a proper directivity description of rolling noise, which is important for an accurate wayside noise prediction at different train speeds.

Keywords

Directivity Pattern Directivity Characteristic Dipole Source Train Speed Sound Power 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Peters, S.: The Prediction of Railway Noise Profiles. Journal of Sound and Vibration. Journal of Sound and Vibration 32(1), 87–99 (1974)Google Scholar
  2. 2.
    Thompson, D.: Railway Noise and Vibration: Mechanisms, Modelling and Means of Control. Elsevier, Amsterdam (2009)Google Scholar
  3. 3.
    Remington, P.J.: Wheel/rail noise, I: Characterization of the wheel/rail dynamic system. Journal of Sound and Vibration 46, 359–379 (1976)CrossRefGoogle Scholar
  4. 4.
    Zhang, X.: Measurements of Directivity on Test Rig, HAR12TR-020910 -SP04 HAR12TR-020910 -SP04 (Harmonoise technical report) (April 30, 2003)Google Scholar
  5. 5.
    Zhang, X., Jonasson, H.: Directivity of Railway Noise Sources. Journal of Sound and Vibration 293, 995–1006 (2006)CrossRefGoogle Scholar
  6. 6.
    Zhang, X.: To determine the horizontal directivity of a train pass-by, in03_627. In: The Proceedings for Inter. Noise 2003, Jeju, Korea, August 25-28 (2003)Google Scholar
  7. 7.
    Zhang, X.: Directivity of Railway Rolling Noise. In: Zhang, X. (ed.) Noise and Vibration Mitigation for Rail Transportation Systems. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol. 99, Springer, Heidelberg (2008)CrossRefGoogle Scholar
  8. 8.
    van Leeuwen, J.J.A., Ouwerkerk, M.A.: Comparison of some prediction models for railway noise used in Europe, Report L.94.0387.A, DGMR consulting engineers bv, p. 128, The Hague, The Netherlands (1997)Google Scholar
  9. 9.
    Howe, M.S.: Theory of Vortex Sound. Cambridge University Press, Cambridge (2003)MATHGoogle Scholar
  10. 10.
    Mahé, H., Thompson, D.J., Zach, A., Hölzl, G.: Experimental validation of the prediction model TWINS for rolling noise. In: Proceedings of Inter. Noise 1993, Leuven, Belgium, August 24-26, pp. 1459–1462.Google Scholar

Copyright information

© Springer 2012

Authors and Affiliations

  • Xuetao Zhang
    • 1
  1. 1.SP Technical Research Institute of SwedenBoråsSweden

Personalised recommendations