Descrizione del progetto DEENESFRITPL Controllo ottimale di flussi instabili con nuovi metodi adjoint Il controllo attivo del flusso mira a modificare lo stato naturale del flusso o il percorso di sviluppo in uno stato più auspicabile attraverso diversi tipi di getti. Questo campo interdisciplinare è molto importante per i velivoli: l’uso di tali getti compatti potrebbe eliminare la necessità di pesanti sistemi di flap per mantenere il flusso aderente alla superficie, e potrebbe quindi produrre un’elevata portanza e ridurre la resistenza aerodinamica. Il progetto KAFKA, finanziato nell’ambito del programma di azioni Marie Skłodowska-Curie, mira a far progredire lo studio computazionale dei sistemi di controllo attivo del flusso con metodi adjoint che non possono ancora catturare la fisica caotica dei flussi turbolenti. Mostra l’obiettivo del progetto Nascondi l’obiettivo del progetto Obiettivo 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. Campo scientifico natural sciencesphysical sciencesclassical mechanicsfluid mechanicsfluid dynamicsnatural sciencescomputer and information sciencescomputational science Parole chiave Active Flow Control Adjoint Optimisation RANS Modelling Large Eddy Simulations Programma(i) 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 Argomento(i) MSCA-IF-2018 - Individual Fellowships Invito a presentare proposte H2020-MSCA-IF-2018 Vedi altri progetti per questo bando Meccanismo di finanziamento MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinatore QUEEN MARY UNIVERSITY OF LONDON Contribution nette de l'UE € 224 933,76 Indirizzo 327 MILE END ROAD E1 4NS London Regno Unito Mostra sulla mappa Regione London Inner London — East Tower Hamlets Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 224 933,76
