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Optimal Control of Chemical Processes
Project leader:
- Prof. Dr. Peter Benner
Max Planck Institut for Dynamics Complex Technical Systems Magdeburg,
Computational Methods in Systems and Control Theory,
Sandtorstr. 1, 39106 Magdeburg, Germany
Tel: +49 (0)391-6110-450
E-mail: benner@mpi-magdeburg.mpg.de
Researcher:
- Dr. Martin Stoll
Max Planck Institut for Dynamics Complex Technical Systems Magdeburg,
Computational Methods in Systems and Control Theory,
Sandtorstr. 1, 39106 Magdeburg, Germany
Tel: +49 (0)391-6110-805
E-mail: stollm@mpi-magdeburg.mpg.de
- Dr. Hamdullah Yücel
Max Planck Institut for Dynamics Complex Technical Systems Magdeburg,
Computational Methods in Systems and Control Theory,
Sandtorstr. 1, 39106 Magdeburg, Germany
Tel: +49 (0)391-6110-387
E-mail: yuecel@mpi-magdeburg.mpg.de
Duration: since October 2012
- Project description:
-
Chemical reactive flows lead to optimization problems governed by systems of convection diffusion partial
differential equations (PDEs) with nonlinear reaction mechanisms. Such problems are strongly coupled as
inaccuracies in one unknown directly affect all other unknowns. Prediction of these unknowns is very important
for the safe and economial operation of biochemical and chemical engineering processes. The solution
of these PDEs can exhibit boundary and/or interior layers on small regions where the solution has large gradients,
when convection dominates diffusion. Hence, special numerical techniques are required, which take the structure of
convection into. Recently, discontinuous Galerkin (DG) methods became an alternative to the finite difference, finite
volume and continuous finite element methods for solving wave dominated problems like convection diffusion equations
since they possess higher accuracy. We focus here on an application of adaptive DG methods for
(un)steady optimal control problems governed by copuled convection dominated PDEs with nonlinear reaction terms
with state and/or control constraints in 2D and 3D.
- Related publications:
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