Project description DEENESFRITPL Optimal control of unsteady flows using novel adjoint methods Active flow control aims to change the natural flow state or development path into a more desired state through different types of jets. This interdisciplinary field is highly relevant in aircraft: the use of such compact jets could eliminate the need for heavy flap systems to maintain the flow attached to the surface, and could therefore produce high lift and reduce drag. Funded by the Marie Skłodowska-Curie Actions programme, the KAFKA project aims to advance the computational study of active flow control systems with adjoint methods that cannot yet capture the chaotic physics of turbulent flows. Show the project objective Hide the project objective Objective Active Flow Control (AFC) mechanisms have tremendous potential in improving flow characteristics in a wide variety of sectors. For effective AFC design, it is essential to determine the sensitivity of each of the control parameters to the flow property of interest. Adjoint methods provide the sensitivity of the objective function to any number of input parameters at a reasonable additional cost. They are based on simple RANS turbulence modelling, which captures poorly the physics of flow especially in the presence of complex flow features such as flow separation, which can be effectively eliminated by flow control. Recently developed Reynolds Stress Models (RSM) display significant improvement in the flow prediction capacity as compared to conventional RANS models, yet adjoints with RSM are not yet available. An alternative for accurate flow prediction is Large Eddy Simulation (LES). Unfortunately resolving the chaotic turbulent motion results in exponential growth of the gradients.Our first objective is to develop an effective discrete adjoint method with an accurate and stable RSM, and compute sensitivities in complex flows involving active control mechanism applied to realistic wing geometries. Although RSM outperforms conventional turbulence models in a host of applications, there is a need for further physics-based calibration for specific flows. Our second objective is to use the adjoint method to drive the model coefficients to their optimum value such that the model results match with high-fidelity simulation data yielding a better turbulence model, which can be applied for effective flow control design in bluff body with severe rear flow separation. Our third objective will be to develop adjoint approaches for chaotic LES flows using the hosting groups' innovative gappy checkpointing approach that retains the accuracy of the LES but regularises the chaotic motion for the reverse adjoint pass, hence avoiding the exponential blowup of the sensitivities. Fields of science natural sciencesphysical sciencesclassical mechanicsfluid mechanicsfluid dynamicsnatural sciencescomputer and information sciencescomputational science Keywords Active Flow Control Adjoint Optimisation RANS Modelling Large Eddy Simulations Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2018 - Individual Fellowships Call for proposal H2020-MSCA-IF-2018 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator QUEEN MARY UNIVERSITY OF LONDON Net EU contribution € 224 933,76 Address 327 MILE END ROAD E1 4NS London United Kingdom See on map Region London Inner London — East Tower Hamlets Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 224 933,76
