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EXPONENT
149 Commonwealth Drive
Menlo Park, CA 94025
Phone: (650) 688-6909
Fax: (650) 328-2990
Mobile: (650) 353-1015
E-mail: K a v i a t o r [a t] g m a i l [d o t] c o m
Background
Doctorate
Department of Aeronautics and Astronautics,
Stanford
University (1998-2005)
Master of Science
Department of Aeronautics and Astronautics,
Stanford
University (1997-1998)
Business Administration Degree
Institut d'Administration
des Entreprises (IAE), Toulouse, France (1996-1997)
Mechanical and Aeronautical Engineer Degree
Ecole Nationale Supérieure de
Mécanique et d'Aérotechnique (ENSMA), Poitiers, France
(1993-1996)
Research Interests
Local matrix preconditioning of the Euler and Navier-Stokes
equations
Local matrix preconditioning can help the convergence acceleration
of time-marching methods in solving the systems of Euler and Navier-Stokes
equations by improving the condition number of the continuous system of
equations and by clustering the eigenvalues of the discretized system in
regions of high damping and propagative efficiency. Preconditioning can
also preserve the accuracy of the solution for low Mach numbers. Various
preconditioners such as the Block-Jacobi, the van Leer-Lee-Roe or the Turkel
preconditionner are being investigated in order to combine their advantages
and to extend the benefits of Euler preconditionners to the Navier-Stokes
case.
Optimization of multistage coefficients for explicit multigrid flow solvers
Explicit Euler and Navier-Stokes flow solvers based on
multigrid schemes combined with modified Runge-Kutta multistage methods have
become very popular due to their efficiency and ease of
implementation. An appropriate choice of multistage coefficients
allows for high damping and propagative efficiencies in order to
accelerate convergence to the steady-state solution. It is possible to optimize the damping
and propagative efficiencies of modified Runge-Kutta multistage methods by
expressing the problem within the framework of constrained non-linear
optimization. The optimization process must be done in a systematic way for
a variety of objective functions and constraints in order to assess the roles
of both propagation and damping and thus find the coefficients that maximize
convergence. Such coefficients being different for a given set of Mach number,
flow angle and aspect ratio, it is possible to do an adaptive multistaging, i.e.
to use a different set of optimized coefficients for each computational cell.
Publications
K. Hosseini, "Practical Implementation of Robust Preconditioners for Optimized Multistage
Flow Solvers", Ph.D. thesis, Stanford University, June 2005. (The first link
has margins for one-sided printing. Here is
the version with margins suitable for two-sided printing).
S. Kim, K. Hosseini, K. Leoviriyakit,
and A. Jameson, "Enhancement of Adjoint Design Methods via Optimization of Adjoint Parameters", 43rd AIAA Aerospace Sciences Meeting &
Exhibit, AIAA Paper 2005-0448, Reno, NV, January 10-13, 2005.
K. Hosseini and J. Alonso, "Practical
Implementation and Improvement of Preconditioning Methods for Explicit Multistage Flow Solvers", 42nd AIAA Aerospace Sciences Meeting &
Exhibit, AIAA Paper 2004-0763, Reno, NV, January 5-8, 2004.
K. Hosseini and J.
Alonso, "Optimization of Multistage Coefficients for Preconditioned Explicit Multigrid Flow Solvers", 16th AIAA Computational Fluid
Dynamics Conference, AIAA Paper 2003-3705, Orlando, FL, June 23-26, 2003.
C.V./Resume
Presentation Slides
Squared Preconditioning and Optimized Multistaging for Explicit Multistage Flow Solvers, California
Institute of Technology, September 2004
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