test Browse by Author Names Browse by Titles of Works Browse by Subjects of Works Browse by Issue Dates of Works
       

Advanced Search
Home   
 
Browse   
Communities
& Collections
  
Issue Date   
Author   
Title   
Subject   
 
Sign on to:   
Receive email
updates
  
My Account
authorized users
  
Edit Profile   
 
Help   
About T-Space   

T-Space at The University of Toronto Libraries >
Faculty of Applied Science and Engineering >
Faculty of Applied Science and Engineering Office of the Dean >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/25486

Title: Dynamical flow characterization of transitional and chaotic regimes in converging-diverging channels
Authors: Guzmán, A. M.
Amon, C. H.
Issue Date: Mar-1996
Publisher: Cambridge University Press
Citation: Guzmán AM, Amon CH. Dynamical flow characterization of transitional and chaotic regimes in converging-diverging channels. Journal of Fluid Mechanics. 1996;321:25-57.
Series/Report no.: Journal of Fluid Mechanics
Vol. 321
Abstract: Numerical investigation of laminar, transitional and chaotic flows in convergingdiverging channels are performed by direct numerical simulations in the Reynolds number range 10 < Re < 850. The temporal flow evolution and the onset of turbulence are investigated by combining classical fluid dynamics representations with dynamical system flow characterizations. Modern dynamical system techniques such as timedelay reconstructions of pseudophase spaces, autocorrelation functions, fractal dimensions and Eulerian Lyapunov exponents are used for the dynamical flow characterization of laminar, transitional and chaotic flow regimes. As a consequence of these flow characterizations, it is verified that the transitional flow evolves through intermediate states of periodicity, two-frequency quasi-periodicity, frequency-locking periodicity, and multiple-frequency quasi-periodicity before reaching a non-periodic unpredictable behaviour corresponding to low-dimensional deterministic chaos. Qualitative and quantitative differences in Eulerian dynamical flow parameters are identified to determine the predictability of transitional flows and to characterize chaotic, weak turbulent flows in converging-diverging channels. Autocorrelation functions, pseudophase space representations and Poincare maps are used for the qualitative identification of chaotic flows, assertion of their unpredictable nature, and recognition of the topological structure of the attractors for different flow regimes. The predictability of transitional flows is determined by analysing the autocorrelation functions and by representing their attractors in the reconstructed pseudophase spaces. The transitional flow behaviour is examined by the geometric visualization of the evolution of the attractors and Poincare maps until the appearance of a strange attractor at the onset of chaos. Eulerian Lyapunov exponents and fractal dimensions are quantitative parameters to establish the onset of chaos, the persistence of chaotic flow behaviour, and the long-term persistent unpredictability of chaotic Eulerian flow regimes. Lastly, three-dimensional simulations for converging-diverging channel flow are performed to determine the effect of the spanwise direction on the route of transition to chaos.
Description: Originally published in Journal of Fluid Mechanics Vol 321. Cambridge University Press holds all copyright of this article. CUP allows authors' work to be published in institutional repositories.
URI: http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=413551&fulltextType=RA&fileId=S002211209600763X
http://hdl.handle.net/1807/25486
ISSN: 0022-1120
http://dx.doi.org/10.1017/S002211209600763X
Appears in Collections:Faculty of Applied Science and Engineering Office of the Dean

Files in This Item:

File Description SizeFormat
Dynamical flow characterization of transitional and chaotic regimes in converging-diverging channels.pdf2.36 MBAdobe PDF
View/Open

Items in T-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

uoft