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Title: Sequential Quadratic Programming (SQP) for optimal control in direct numerical simulation of turbulent flow
Authors: Badreddine, Hassaan #
Vandewalle, Stefan
Meyers, Johan # ×
Issue Date: Jan-2014
Publisher: Academic Press
Series Title: Journal of Computational Physics vol:256 pages:1-16
Abstract: The current work focuses on the development and application of an efficient algorithm for optimization of three-dimensional turbulent flows, simulated using Direct Numerical Simulation (DNS) or large-eddy simulations, and
further characterized by large-dimensional optimization-parameter spaces. The optimization algorithm is based on
Sequential Quadratic Programming (SQP) in combination with a damped formulation of the limited-memory BFGS method. The latter is suitable for solving large-scale constrained optimization problems whose Hessian matrices cannot be computed and stored at a reasonable cost. We combine the algorithm with a line search merit function based an an L1-norm to enforce the convergence from any remote point. It is first shown that the proposed form of the damped L-BFGS algorithm is suitable for solving equality constrained Rosenbrock type functions. Then, we apply
the algorithm to an optimal-control test problem that consists of finding the optimal initial perturbations to a turbulent temporal mixing layer such that mixing is improved at the end of a simulation time horizon T. The controls are further subject to a non-linear equality constraint on the total control energy. DNSs are used to resolve all turbulent scales of motion, and a continuous adjoint formulation is employed to calculate the gradient of the cost functionals. We compare the convergence speed of the SQP L-BFGS algorithm to a conventional non-linear conjugate gradient method (i.e. the current standard in DNS-based optimal control), and find that the SQP algorithm is more than an order of magnitude faster than the conjugate-gradient method.
ISSN: 0021-9991
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Applied Mechanics and Energy Conversion Section
Numerical Analysis and Applied Mathematics Section
× corresponding author
# (joint) last author

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