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Proposal of a new autocorrelation function in low wind speed conditions

Author

Listed:
  • Moor, L.P.
  • Degrazia, G.A.
  • Stefanello, M.B.
  • Mortarini, L.
  • Acevedo, O.C.
  • Maldaner, S.
  • Szinvelski, C.R.P.
  • Roberti, D.R.
  • Buligon, L.
  • Anfossi, D.

Abstract

In this study a new mathematical expression to describe the observed meandering autocorrelation functions in low-wind speed is proposed. The analysis utilizes a large number of best fit curves to show that the proposed theoretical function well reproduces the general form and the negative lobes characterizing the experimental meandering autocorrelation function. Further, the good agreement of the measured autocorrelation curves with the proposed algebraic autocorrelation function allows to calculate the magnitudes of the meandering period and of the loop parameter. The results agree with the values presented and discussed in the literature. Therefore, the new formulation describing experimental meandering autocorrelation functions can be used to simulate the dispersion of contaminant during low wind episodes and to determine relevant meandering parameters.

Suggested Citation

  • Moor, L.P. & Degrazia, G.A. & Stefanello, M.B. & Mortarini, L. & Acevedo, O.C. & Maldaner, S. & Szinvelski, C.R.P. & Roberti, D.R. & Buligon, L. & Anfossi, D., 2015. "Proposal of a new autocorrelation function in low wind speed conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 286-292.
    • Handle: RePEc:eee:phsmap:v:438:y:2015:i:c:p:286-292
    DOI: 10.1016/j.physa.2015.06.048
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    References listed on IDEAS

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    1. Arbage, Maria Cristina Andres & Degrazia, Gervásio Annes & Welter, Guilherme Sausen & Roberti, Débora Regina & Acevedo, Otávio Costa & de Moraes, Osvaldo Luiz Leal & Ferraz, Simone Teleginski & Timm, , 2008. "Turbulent statistical characteristics associated to the north wind phenomenon in southern Brazil with application to turbulent diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4376-4386.
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    Cited by:

    1. Martins, Luis Gustavo Nogueira & Stefanello, Michel Baptistella & Degrazia, Gervásio Annes & Acevedo, Otávio Costa & Puhales, Franciano Scremin & Demarco, Giuliano & Mortarini, Luca & Anfossi, Domenic, 2016. "Employing the Hilbert–Huang Transform to analyze observed natural complex signals: Calm wind meandering cases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1189-1196.

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