PhD position in Flow Control

Despite efforts of manufacturers to optimise shape of transport vehicles, aerodynamic mechanisms (separation, mixing, etc…) still represent an important source of energy cost. Significant efforts in the development of strategies to limit the effects of these mechanisms on the performance of the given system have been conducted over the years. Among these, passive actuators generally based on intrusive objects in the flow (riblets, vortex generators etc…) have long been studied. However, these actuators can not be considered for optimal solutions in the context described previously where varying initial conditions or unsteady perturbations may cause significant changes of the flow behaviour. In contrast, active actuators which can be at least turned on and off offer potential to control a large variety of input parameters such that the examined system operates at its best performance whatever are the initial conditions and upstream perturbations. To drive such actuators, command laws and more globally controllers are required. Different strategies can be employed to design these controllers among which model-based approaches. These require the knowledge of a physical model which is used to obtain an estimation of the flow state. Real-time state estimation over short and mid-term horizons based on the limited knowledge of spatial and time discrete measurements remains however a challenging task while an essential element for real-time flow control applications.

This problem of state estimation is well known by the community of meteorologists who have to deal with a large amount of heterogeneous data collected over the globe to predict the evolution of the weather in space at various scales and in time over different horizons. Methodologies implemented use data assimilation techniques where collected data are assimilated, when available, with the physical model of weather forecast to correct the state estimate obtained by the model, and eventually to correct the model itself for further more accurate predictions. In the specific context of aerodynamic-related problems, the complexity resides essentially in the large number of degrees of freedom of the flow dynamics, in the broad range of scales to examine and in non-linearities driving the flow dynamics. To design a physical model which can be managed in real-time applications, Galerkin projection of the Navier-Stokes equations into an appropriate orthonormal basis is historically the most common used approach. The orthonormal basis is dedicated to capture flow features which are believed essential to the desired objective. The physical “reduced-order model” obtained can then be used in conjunction with data assimilation techniques to design dynamic observers able to predict the flow state from limited information typically available in practical applications.

The main objective of the present PhD thesis is to develop such dynamic observers inspired from the methodologies implemented in meteorology, in the perspective of future control development. Experimental demonstration will be effected by considering the canonical case of a plane mixing layer. Interest will be especially focused on the ability of the observers to take into account the flow changes due to modifications of initial condition and to the presence of upstream perturbations. The demonstrator should emphasize the capability of the implemented methodologies to properly estimate the flow state in the mixing region using limited information (point flow velocity downstream and wall-pressure upstream the leading edge) and to improve the physical model when necessary. Such work will therefore open the doors for a wide range of applications far beyond control issues.

The candidate will have his office at Institut PPRIME (Poitiers, France) within the Fluids, Thermal and Combustion Sciences Dept. and team ATAC (Aerodynamics, Turbulence, Acoustic and Control). He will be immersed in an attractive scientific context. At the end of the 3-year project, the candidate will be awarded the phD degree by Université de Poitiers.