Abstract
The control of turbulent shear flows can be achieved through the control of the large-scale structures. Indeed, even in fully turbulent shear flows, these large-scale structures are known to be of primary importance for most of the flow characteristics. Due to the turbulent character of flows under practical and industrial interests, the detection, analysis, prediction and control of the large-scale structures are quite complex. We present, in this chapter, several tools available for accessing these large-scale structures. Non conditional, stochastic methods, based on correlations, are preferentially detailed. In particular, the Proper Orthogonal Decomposition and the Linear Stochastic Estimation are described. As an illustration of the potentialities of these objective stochastic approaches, the particular case of the turbulent plane mixing layer is derived as a guide-line all along this chapter. In its last part this chapter will focus onto the way by which, using POD, low dimensional models of the structures can be derived, in the framework of a closed loop control of these structures. This approach, deeply related to the notion of deterministic chaos, is then emphasized. The important problem of the closure (mean flow/turbulent flow) appearing in this context is recalled. The last part of this chapter is devoted to a point that is specific and of importance for these stochastic approaches. The limits for the representation of the flow by these models when the flow configuration evolves have to be given. The methods able to take into account this evolution are of crucial importance and under rapid development.
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Delville, J., Cordier, L., Bonnet, JP. (1998). Large-Scale-Structure Identification and Control in Turbulent Shear Flows. In: Gad-el-Hak, M., Pollard, A. (eds) Flow Control. Lecture Notes in Physics, vol 53. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69672-5_4
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