Large-Scale-Structure Identification and Control in Turbulent Shear Flows

Abstract

The control of turbulent sheax flows can be achieved through the control of the large-scale structures. Indeed, even in fully turbulent sheax flows, these laxge-scale structures are known to be of prhnary importance for most of the flow chaxacteristics. Due to the turbulent chaxacter of flows under practical and industrial interests, the detection, analysis, prediction and control of the laxge-scale structures axe 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 particulax, 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) appeaxing 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 Emits 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.