Abstract
We present a set of stochastic optimization strategies and we discuss their applications to fluid mechanics problems. The optimization strategies are based on state-of-the-art stochastic algorithms and are extended for the application on fluid dynamics problems. The extensions address the question of parallelization, strategy parameter adaptation, robustness to noise, multiple objective optimization, and the use of empirical models. The applications range from burner design for gas turbines, cylinder drag minimization, aerodynamic profile design, micromixer, microchannel, jet mixing to aircraft trailing vortex destruction.
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Koumoutsakos, P., Müller, S.D. (2006). Flow Optimization Using Stochastic Algorithms. In: Koumoutsakos, P., Mezic, I. (eds) Control of Fluid Flow. Lecture Notes in Control and Information Sciences, vol 330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36085-8_10
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DOI: https://doi.org/10.1007/978-3-540-36085-8_10
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