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Randomness representation of Turbulence in an alluvial channel affected by downward seepage

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  • Sharma, Anurag
  • Mihailović, Dragutin T.
  • Kumar, Bimlesh

Abstract

In the present work, experimental investigations have been done to study the flow turbulence in an alluvial channel with and without seepage. Turbulence is generally depicted as flow randomness or irregularity. The inherent randomness of turbulence in seepage affected channel has been quantified through Kolmogorov complexity (KC) and the Kolmogorov complexity spectrum. The measures have been used in analysis of the velocity time series data of alluvial channel to compare the degree of turbulence with and without seepage. The result concludes that the value of the KC is higher with seepage flow which indicates that higher level of randomness has been observed in seepage flow. Also, the frequency analysis of velocity time series was carried out with the help of Hilbert–Huang transform, which shows that dominant time scale for seepage flow is lower, indicates increased rate of sediment transport. Spectral analysis of velocity time series also suggests more randomness in channel with seepage.

Suggested Citation

  • Sharma, Anurag & Mihailović, Dragutin T. & Kumar, Bimlesh, 2018. "Randomness representation of Turbulence in an alluvial channel affected by downward seepage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 74-85.
    • Handle: RePEc:eee:phsmap:v:509:y:2018:i:c:p:74-85
    DOI: 10.1016/j.physa.2018.06.012
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    References listed on IDEAS

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    1. Kinzli, Kristoph-Dietrich & Martinez, Matthew & Oad, Ramchand & Prior, Adam & Gensler, David, 2010. "Using an ADCP to determine canal seepage loss in an irrigation district," Agricultural Water Management, Elsevier, vol. 97(6), pages 801-810, June.
    2. Mihailović, D.T. & Nikolić-Đorić, E. & Drešković, N. & Mimić, G., 2014. "Complexity analysis of the turbulent environmental fluid flow time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 96-104.
    3. Pierpaolo Andriani & Bill McKelvey, 2009. "Perspective ---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations," Organization Science, INFORMS, vol. 20(6), pages 1053-1071, December.
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    Cited by:

    1. Lade, Abhijit D. & Mihailović, Anja & Mihailović, Dragutin T. & Kumar, Bimlesh, 2019. "Randomness in flow turbulence around a bridge pier in a sand mined channel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

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