Mathematical Tools for the Analysis of Turbulent Flows Part 5 (Autocorrelation)

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  • čas přidán 9. 09. 2024
  • Autocorrelation and crosscorrelation

Komentáře • 15

  • @tirthankarbanerjee6363
    @tirthankarbanerjee6363 Před 4 lety +5

    in the denominator, the square should be inside. else, really helpful! thank you.

  • @BrandonLobo
    @BrandonLobo Před 5 lety

    Thanks a lot for this. It clarified some thoughts I had on the matter. Your entire series on Turbulence has been great so far, going to check out part 8 now. Thanks Prof. Schluter.

  • @sarigulikhan
    @sarigulikhan Před 2 lety

    Thank you so much. I really enjoyed it!

  • @RestyLevy
    @RestyLevy Před 2 lety

    Hi professor, this is a really helpful video, thanks a lot for it

  • @cxrrt
    @cxrrt Před 11 měsíci

    excellent video

  • @zacmac
    @zacmac Před 5 lety

    Hi thanks for this great explanation, very very helpful.

  • @inquisitor1017
    @inquisitor1017 Před 7 lety +2

    I think the normalization factor for the auto-correlation function should be instead of ^2 ... the latter obviously does not yield a normalized 1 at the start since
    rho(0) = / ^2 =/= 1
    ^ it does not necessarily give 1, if not always different than 1.
    Similarly, for the cross-correlation with the addition of the x-component, as so: ...

    • @JMBBproject
      @JMBBproject Před 7 lety

      Indeed, the square should be inside the average brackets. I think this is also stated in Pope's/Lumley's book.

    • @BrandonLobo
      @BrandonLobo Před 5 lety

      True. I was wondering the same.

  • @arunv1986
    @arunv1986 Před 4 lety

    Hello Dr Schluter, I would like you to kindly clarify the term in the denominator of the auto-correlation (u^2). As I understand, it should be the average of the square of the velocity, which means that the power term should be inside the average and not outside.

  • @duosifan2303
    @duosifan2303 Před 6 lety

    Hi, Prof. Schluter! I want to know how we can compute the autocorrelation numerically. For example, I have a time series of the streamwise velocity at a fixed point in a channel flow and it is represented by U(t_i). Of course, the flow has reached statistical stationary.

  • @hamidfortab7769
    @hamidfortab7769 Před 5 lety

    QUESTION. Why rho(s) is always less than one? See diagram at 7:50. Thanks.

    • @jaedongtang37
      @jaedongtang37 Před 5 lety

      My intuition is it is a measure of how "correlated" the signal of current time and s time latter. If s = 0, then rho(s) = 1, it means signal is perfectly correlated to itself, it does make sense because what happens at current time fully determines itself (or 0 time latter). If s > 0, what happens at current time might "somehow" correlated to what happens at s time latter, but it might not be that "perfect". I think it might be proved to be less than 1 by math, but it is just my intuition.

    • @derivativecovariant2341
      @derivativecovariant2341 Před 5 lety

      becuz it is normalized, taking rho(0) the maximum value and equal to 1

  • @hulk8889
    @hulk8889 Před 2 lety

    Dissipation time scale?