An adjoint-based Navier-Stokes design and optimization method for two-dimensional multi-element high-lift configurations is derived and presented. The compressible Reynolds-averaged Navier-Stokes equations are used as a flow model together with the Spalart-Allmaras turbulence model to account for high Reynolds number effects. When a viscous continuous adjoint formulation is used, the necessary aerodynamic gradient information is obtained with large computational savings over traditional finite difference methods. The high-lift configuration parallel design method uses a point-to-point matched multiblock grid system and the message passing interface standard for communication in both the flow and adjoint calculations. Airfoil shape, element positioning, and angle of attack are used as design variables. The prediction of high-lift flows around a baseline three-element airfoil configuration, denoted as 30P30N, is validated by comparison with available experimental data. Finally, several design results that verify the potential of the method for high-lift system design and optimization are presented. The design examples include a multi-element inverse design problem and the following optimization problems: lift coefficient maximization, lift-to-drag ratio maximization, and the maximum lift coefficient maximization problem for both the RAE2822 single-element airfoil and the 30P30N multi-element airfoil.
NomenclatureC d , C l = airfoil coefficients of drag and lift C lmax = maximum lift coefficientboundary shape G G = gradient vector H = total enthalpy I = cost function L = lift M ∞ = freestream Mach number p = static pressure p d = desired target static pressure R = governing equations or residual Re = Reynolds number S = surface area t/c = thickness-to-chord ratio w = conservative flow variables in Cartesian coordinates x,y = Cartesian coordinates y + = dimensionless wall distance α = angle of attack α cl max = stall angle of attack δ = first variation λ = step size in steepest descent method ψ = Lagrange multiplier, costate or adjoint variables