The identification of inflow air-data quantities such as the airspeed, angle of attack, and local lift coefficient on various sections of a wing or rotor blade is beneficial for load monitoring, aerodynamic diagnostics, and control on devices ranging from air vehicles to wind turbines. Real-time measurement of aerodynamic parameters during flight provides the ability to enhance aircraft operating capabilities while preventing dangerous stall situations. This Paper presents a novel leading-edge flow sensing algorithm for the determination of the air-data parameters using discrete surface pressures measured at a few ports in the vicinity of the leading edge of a wing or blade section. The approach approximates the leading-edge region of the airfoil as a parabola and uses pressure distribution from the exact potential-flow solution for the parabola to fit the pressures measured from the ports. Pressures sensed at five discrete locations near the leading edge of an airfoil are given as input to the algorithm to solve for the model parabola-flow problem using a simple nonlinear regression. The algorithm directly computes the inflow velocity and the stagnation-point location. A look-up table approach is adopted to deduce the section angle of attack and lift coefficient. The performance of the algorithm is assessed using experimental data in the literature for airfoils under different flow conditions. The results show good correlation between the actual and predicted aerodynamic quantities within the prestall regime, even for rotating blade sections.


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    Titel :

    Leading-Edge Flow Sensing for Aerodynamic Parameter Estimation


    Beteiligte:

    Erschienen in:

    AIAA Journal ; 56 , 12 ; 4706-4718


    Erscheinungsdatum :

    01.12.2018




    Medientyp :

    Aufsatz (Konferenz) , Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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