Flow Control Group

The research area is dedicated to the development, implementation, and validation, both numerical and experimental of flow control techniques towards improving the performance of aerodynamic bodies. Several wind tunnel facilities are available to the group as well as state of the art flow diagnostics and numerical fluid dynamics solvers.

Gioacchino.Cafiero@polito.it

Gaetano.Iuso@polito.it

Jacopo.Serpieri@polito.it

 

  • Artificial Intelligence-based strategies for a green transport

The term Machine Learning is nowadays ubiquitous thanks to the recent development of open-source libraries, such as Tensorflow developed by Google, which have made these algorithms, which are as powerful as they are complex to implement, more user-friendly. The potential of these algorithms lies in the ability to learn directly from data, in fact we speak of the "Data-Driven" approach.

This allows to completely change the paradigm with which a fluid dynamic problem is approached. Indeed, it is no longer necessary to develop an approximate physical model of complex problems, but it is the system that learns from the data.

The enormous amount of data available, both numerical and experimental, combined with the exponential growth of computational skills have meant that Machine Learning techniques, already known during the 1960s, were finally of effective practical application in real problems.

The application of Machine Learning to problems such as flow control can introduce significant improvements in the aerodynamic performance of road vehicles, more particularly in the minimization of aerodynamic drag. Deep Reinforcement Learning (DRL) has demonstrated capabilities in many fields, from video games to solving highly non-linear complex problems. Reinforcement Learning (RL) models an agent that interacts with an environment (in this case the motion field) through a series of actions (the control laws) obtaining a given reward (the function to be designed).

This research activity focuses attention on the implementation of Machine Learning techniques in the field of fluid dynamics and the control of the wake of squat bodies, characterized by high aerodynamic resistance, such as vehicles for transporting goods by road. They contribute a significant percentage of transport-related emissions. This is in line with the policies and proposals adopted by the European Commission which, through the Green Deal, seeks to guide EU policies on climate, energy, transport and taxation in order to reduce greenhouse gas emissions by at least 55%. by 2030 compared to 1990 levels.

 

  • Towards a zero-impact aircraft: innovative roughness geometries for drag reduction (PRIN 2022 funded project)

The reduction of pollutants in the atmosphere is one of the main goals set by the ACARE Flightpath 2050. To this end, significant efforts are currently being spent by the fluid dynamics community to tackle the problem associated with the friction drag of airborne vehicles.

Friction drag represents one of the most significant shares of drag exerted on aerodynamic bodies, typically contributing to about 50%.

This has stimulated a wealth of control methodologies that can generally be split into two different categories: active or passive. To the former belong those solutions that require energy, generally drawn from the engine bleed or from a dedicated power supply, with the drawback of increasing mass and costs.

One of the most attractive passive methodologies is that of the riblets, which are microgrooves operated on the surface and aligned to the freestream direction. The technique has already been applied to real cases, for example on swimsuits or America’s Cup ships.

Riblets have been widely investigated for the last 30 years. The interest in the topic is far from being abated, considering the potential benefit brought by this passive manipulation. Recent interest of aircraft manufacturers in implementing the technology on existing aircraft has fueled the research to find innovative and even more efficient solutions, with the push towards the definition of more drag reducing geometries, such as sinusoidal ones.

It is then paramount to determine the effect of the riblets’ geometry (such as wavelength amplitude and geometry of the groove) on the drag reduction that they can yield. This will open the path to the implementation of the grooves on small to large scale vehicles, contributing towards the achievement of the goals of mitigating the carbon footprint of air mobility.  

 

  • Development of flow control methodologies for lifting surfaces of next generation aircraft with hybrid/electric propulsion

The research activities concern the scientific and technological areas related to the Spoke 1 – Air Mobility within the framework of the National Center for Sustainable Mobility, funded by the National Recovery and Resilience Plan NextGenerationEU (PNRR 2022-2025).

The activities will fall within the remits of the Work Package n.2 “Disruptive technologies for electric and hybrid propulsion aircraft” and n.3 “Enabling technologies for next generation air mobility”. The Clean Aviation Programme (Strategic Research and Innovation Agenda,

2020) identifies hybrid and electric propulsions as one of the critical drivers to achieve carbon neutrality by 2050. The need to introduce innovative solutions for the propulsion systems, such as distributed propulsion, poses problems related to the aerodynamic efficiency of the next-generation vehicles.

In this sense, determining solutions that can mitigate the interference of integrating the propulsion system in the lifting system, represent a key goal.

The research objectives include:

• Development and performance evaluation of innovative surfaces for skin friction drag reduction on airborne vehicles, including data-based techniques for the optimization and the prediction of the performance.

• Evaluation of the effect of the integration of innovative propulsion systems on vehicles for regional transport, including flow control methodologies to mitigate the impact on the aerodynamics performance;

• Development of non-intrusive methodologies for the evaluation of the convective heat transfer with complex surfaces.

 

  • Active flow control for friction drag reduction (PRIN PNRR 2022 funded project)

The reduction of pollutants in the atmosphere is one of the main goals set by the ACARE Flightpath 2050. To this end, significant efforts are currently being spent by the fluid dynamics community to tackle the problem associated with the friction drag of airborne vehicles.

Friction drag represents one of the most significant shares of drag exerted on aerodynamic bodies, typically contributing to about 50%.

This has stimulated a wealth of control methodologies that can generally be split into two different categories: passive or active. These latter have the further advantage that their control parameters can be adapted to different flow conditions and to different purposes.

Among the active techniques, arrays of wall mounted plasma actuators can induce flow motions that damp the turbulence-regeneration mechanisms.  Plasma actuators are made of conductive elements some of which exposed to a gas (air) that, due to a strong electric field, can locally ionize. The ions are then accelerated by the electric field causing a fluid motion that can be used for flow control purposes.

The activities in this project comprise:

  • Development and characterization of arrays of plasma actuators
  • Deployment of plasma-based flow control in laboratory flow facilities and experimental assessments of the control effect
  • Numerical simulations of plasma-based active flow control and assessments of the control effect

 

  • Analysis of passive/active swirl jets

Jets are among the most spread industrial flows. A common application considers them as devices to control the heat transfer of a craft and the environment. Swirl jets are jets whose flow is induce to a swirl motion and proved to feature improved properties. The swirl motion can be caused by different means. The most common is a passive approach that considers an helicoidal insert in the jet nozzle. Besides, active approaches have been considered too. These have the advantage that their control parameters can be adapted to different flow conditions and to different purposes. These active approaches are based on the introduction of an azimuthal flow along the nozzle-accelerated axial one. This control flow can be injected by nozzle-installed orifices blowing pressurized air or by considering other flow actuators. Plasma actuators can be used for this purpose. Plasma actuators are made of conductive elements some of which exposed to a gas (air) that, due to a strong electric field, can locally ionize. The ions are then accelerated by the electric field causing a control flow that can be used to induce the jet flow swirl motion.

Research activities in this project aim at:

  • Designing and characterizing passive and plasma-based active swirls
  • Assessing the fluid dynamics effect of the swirl motion
  • Assessing the heat transfer performance of the swirl motion

 

ERC sectors

  • PE8_1 Aerospace engineering
  • PE8_5 Fluid mechanics

Keywords

  • Fluid dynamics
  • Aerodynamics
  • Flow control
  • Experimental methods