1 / 15

Decomposition nonstationary turbulence velocity in open channel flow

Decomposition nonstationary turbulence velocity in open channel flow. Ying-Tien Lin 2005.12.12. Background. Laminar flow and turbulent flow. Background. Flow velocity profile. Turbulent velocity or Fluctuated velocity. Mean velocity. Background. Turbulent flow occurs in our daily life.

bing
Download Presentation

Decomposition nonstationary turbulence velocity in open channel flow

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Decomposition nonstationary turbulence velocity in open channel flow Ying-Tien Lin 2005.12.12

  2. Background • Laminar flow and turbulent flow

  3. Background • Flow velocity profile

  4. Turbulent velocity or Fluctuated velocity Mean velocity Background • Turbulent flow occurs in our daily life. put cube sugar into a cup of coffee • Turbulent model Assume

  5. Background • Reynolds shear stress Sediment particles Shear stress River

  6. Background • Stationary turbulence flow • Nonstationary turbulence flow (occurs in flooding period) Mean velocity How to find its time-varying mean velocity?

  7. Decomposition method • Fourier decomposition method • Wavelet transformation • Empirical mode decomposition

  8. Fourier decomposition method • It is unable to show how the frequencies vary with time in the spectrum. DFT LF Inv. DFT

  9. Wavelet transformation • Linear combinations of small wave • Be able to show the frequency varies with time DWT Threshold Inv. DWT

  10. Empirical Mode Decomposition (EMD) • The upper and lower envelopes of U(t) are constructed by connecting its local maxima and minima. Upper envelope Velocity Instantaneous velocity Lower envelope Time

  11. Empirical mode decomposition (EMD) • The mean value of the two envelopes is then computed. The difference between the instantaneous velocity and the mean value is called the first intrinsic mode function (IMF), c1(t). IMF is a function that: 1. has only one extreme between zero crossings. 2. has a mean value of zero. This is called the Sifting Process

  12. C1(t) C5(t) C12(t) residual(t)

  13. Results Add noise Denoising

  14. Results Add noise Denoising

  15. Summary • These three decomposition methods perform good fitting with the original functions. • EMD seems better than the other two methods.

More Related