The need to reduce energy consumption, CO2 emissions, and energy losses in aerodynamics is a central issue that has driven substantial research efforts in areas such as transportation and wind energy. Some examples of engineering systems in these areas, are helicopters, air vehicles (drones), cars, trains, trucks, sailing boats and wind turbines (etc...). The interaction of these systems with fluids (fluid-structure interaction) is inevitable and is a major cause of instability, turbulence and undesired behaviours, producing low energy performance and more CO2 emissions. These challenges can be addressed through flow control strategies, which vary depending on the application. Two prominent control strategies are passive control and active control.
Passive control methodologies aim to modify the mechanical structure of the object by altering its shape to achieve an optimal behaviour for a specific condition of the environment (of the fluid that surrounds it). However, these strategies often
require costly numerical studies to determine optimal shape, and it may not always yield optimal results, especially when the object is subject to varying flow conditions.
Active control, on the other hand, is a relevant area of automatic control, standing out because it involves the use of sensors and actuators to provide real-time feedback. Actuators enable the dynamic adjustment of flow dynamics in real-time to maintain optimal performance and minimize aerodynamic losses. This adaptability makes active control a highly promising and robust solution. This highlights the motivation for using specifically, closed-loop active flow strategies, which utilize feedback mechanisms to enhance system robustness and performance. Thus, automatic control offers a variety of powerful tools for the analysis, identification, and control, and estimation design of complex dynamical systems arising in aerodynamics and fluid mechanics.
A major challenge in understanding and controlling flows in transportation industry or in wind energy is the fact that the flow behavior is strongly nonlinear and exhibits a spatial-temporal dependency. Typically, the dynamics is described by the Navier-Stokes (NS) equations, which is a model with nonlinear Partial Differential Equations (PDEs), making them particularly challenging to analyze. Thus, understanding and controlling the interactions between structures and fluids requires a multidisciplinary approach between the domains of fluid mechanics, applied mathematics and automatic control.
One of the common problems among these research domains are the modelling of the system to be controlled. Depending on the application and the control objectives, the model requirements may vary. For control design one may need simple control-oriented models , whereas for verification, validation and simulation, one may need a high-fidelity model, which hihlights the need for studying spatial discretization and model-order reduction techniques.
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This GDR action aims to strengthen collaboration between researchers in the domain of automatic control, fluidmechanics and applied mathematics.
We aim to develop an “état des lieux" with the main labs involved in the domain of automatic control appliedto fluids mechanics.
To enhance the visibility of this activity, we are planning to organize a workshop that will be instrumentalin identifying opportunities for collaboration, raising new theoretical questions, and exploring applications.
Additionally, we will discuss the experimental platforms available in France on which any theoretical contri-butions may be implemented and validated.
We will also leverage our network of researchers working in fluid mechanics and wind energy to showcase thepotential of automatic control for understanding, modeling, and managing these complex dynamical systems.
Ultimately, this GDR Action initiative may provide the foundation for submitting a groundbreaking for anANR MRSEI to build an European interdisciplinary group for EU project.
TBD
