Evolution strategies for automatic optimization of jet mixing
P. Koumoutsakos, J. Freund, D. Parekh, AIAA Journal, 39(5), 967-969, 2001
Evolution strategies (ES) are introduced for the optimization of active control parameters for enhancing jet mixing. It is shown that the evolution algorithms can identify, in an automated fashion, not only previously known effective actuations but also é nd good but previously unidentié ed parameters. In this study, simulations of model jets are used to demonstrate the feasibility of the methods. ES are robust, highly parallel, and portable algorithms that ay be most useful in an experimental setting at realistic Reynolds numbers. Simulations of inviscid incompressible è ows using vortex models, as well as direct numerical simulations (DNS) of very low-Reynolds-number compressible è ows, are used in this study to evaluate different forcing parameters.