Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Krener, A.J. (2008)
Publisher: Co-Action Publishing
Types: Article

Classified by OpenAIRE into

arxiv: Physics::Fluid Dynamics
We study the observability of one and two-point vortex flow from one or two Eulerian or Lagrangian observations. By observability, we mean the ability to determine the locations and strengths of the vortices from the time history of the observations. An Eulerian observation is a measurement of the velocity of the flow at a fixed point in the domain of the flow. A Lagrangian observation is the measurement of the position of a particle moving with the fluid. To determine observability, we introduce the observability and the strong observability rank conditions and compute them for the various vortex configurations and observations in this idealized setting. We find that vortex flows with Lagrangian observations tend to be more observable then the same flows with Eulerian observations. We also simulate extended Kalman filters for the various vortex configurations and observations and find that they perform poorly when the ORC or the strong observability rank condition fails to hold.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Acheson, D. J. 1990. Elementary Fluid Dynamics. Clarendon Press, Oxford, 397 pp.
    • Aref, H., 1983. Integrable, Chaotic and Turbulent Vortex Motion in Two-Dimensional Flows. Ann. Rev. Fluid Mech. 15, 345-389.
    • Gelb, A. 1974. Applied Optimal Estimation. MIT Press, Cambridge, MA, 374 pp.
    • Hermann, R. and Krener, A. J. 1977. Nonlinear Controllability and Observability. IEEE, Trans. Auto. Control 22, 728-740.
    • Ide, K. and Ghil, M. 1997a. Extended Kalman Filtering for Vortex Systems. Part I: Methodology and Point Vortices. Dyn. Atmos. Oceans 27, 301-332.
    • Ide, K. and Ghil, M. 1997b. Extended Kalman Filtering for Vortex Systems. Part II: Rankine Vortices. Dyn. Atmos. Oceans 7, 333-350.
    • Ide, K., Kuznetsov, L. and Jones, C. K. R. T. 2002. Lagrangian Data Assimilation for Point Vortex Systems. J. Turbulence 3, available online at http://www.tandf.co.uk/journals/titles/14685248.asp.
    • Krener, A. J. 2002. The Convergence of the Extended Kalman filter. In: Directions in Mathematical Systems Theory and Optimization (eds A. Rantzer and C. I. Byrnes). Springer Verlag, Berlin, 173-182.
    • Kuznetsov, L., Ide, K. and Jones, C. K. R. T. 2003. A Method for assimilation of Lagrangian data. Mon. Wea. Rev. 131, 2247-2260.
  • No related research data.
  • No similar publications.

Share - Bookmark

Funded by projects

  • NSF | Reduced Order Modeling of H...

Cite this article