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Results from the Sixth AIAA CFD Drag Prediction Workshop Cases 2 to 5 are presented. These cases focused on force/moment and pressure predictions for the NASA Common Research Model wing-body and wing-body-nacellepylon configurations. The Common Research Model geometry differed from previous workshops in that it was deformed to the appropriate static aeroelastic twist and deflection at each specified angle of attack. The grid refinement study and nacelle-pylon drag increment prediction (Case 2) used a common set of overset and unstructured grids, as well as user-created multiblock structured, unstructured, and Cartesian-based grids. Solutions were requested for both the wing-body and wing-body-nacelle-pylon at a fixed Mach number and lift coefficient. The wing-body static aeroelastic/buffet study (Case 3) specified an angle-of-attack sweep at finely spaced intervals through the zone where wing separation was expected to begin. The optional Case 4 requested grid adaption solutions of the wing-body at a specified flight condition. Optional Case 5 requested coupled aerostructural wing-body solutions. Results from this workshop highlight the progress made since the last workshop, and the continuing need for computational fluid dynamics (CFD) improvement, particularly for conditions with significant flow separation. These comparisons also suggest the need for improved experimental diagnostics to guide future CFD development.

The main objective of this research is to propose a method for decomposing the total drag of a nacelle into external, internal, and wake drag. From a bookkeeping agreement, the internal drag (i.e., the drag generated inside a nacelle) is the engine manufacturer's responsibility and is not to be included in the aircraft's total drag. Consequently, computing the internal drag is mandatory for the airframe and engine constructors concerned and can be achieved either experimentally or by computational-fluid-dynamics analysis. Up to now, aerodynamic engineers have used a near-field approach to compute the internal drag using computational-fluid-dynamics analysis, but this method has serious drawbacks, including its dependency on the accurate location of the stagnation line. The new method proposed here has been applied to multiple two-and three-dimensional test cases, and results show that it is independent of the location of the stagnation line and yields accurate results that agree well with experimental and empirical data. Results also show that the wake drag of a through-flow nacelle is caused by the flow passing through the nacelle and so needs to be added to the internal drag. Nomenclatureextrapolated near-field drag coefficient from a refinement study c = reference chord, m D NF = near-field drag (pressure friction), N D FF = far-field drag (viscous wave spurious induced), N D V = viscous drag, N D W = wave drag, N D I = induced drag, N D SP = spurious drag, N D c = configuration drag, N D Install = installation drag, N D WBPN = drag of a wing-body-pylon-nacelle configuration, N D WB = drag of a wing-body configuration, N D irr = irreversible drag (viscous wave spurious), N F V = viscous sensor F W = shock sensor f = momentum vector f vw = momentum vector associated with irreversible processes f i = momentum vector associated with reversible processes I = impulsion M = Mach number n = n x ; n y ; n z , normal vector pointing to the outside of the volume p = static pressure, kPa p ∞ = freestream static pressure, kPa q = u v w, velocity vector, m∕s R = perfect gas constant, J∕kg · K Re c = Reynolds number based on a reference chord S ref = reference area, m 2 S A = aircraft surface area S ∞ = surface surrounding the configuration where the flow is undisturbed S T = Trefftz's plane u, v, w = velocity components in the x, y, and z directions, m∕s u ∞ = freestream velocity, m∕s= spurious volume α = angle of attack, deg γ = ratio of specific heats ΔH = enthalpy variation from the freestream state, J∕kg Δs = entropy variation from the freestream state, J∕K Δ u = axial velocity defect, m∕s μ l = laminar viscosity, N · s∕m 2 μ t = turbulent viscosity, N · s∕m 2 μ ∞ = freestream viscosity, N · s∕m 2 ρ = density, kg∕m 3 ρ ∞ = freestream density, kg∕m 3 τ x = τ xx τ xy τ xz , vector of viscous deviatoric stresses, N∕m 2

A proper orthogonal decomposition (POD) method is used to interpolate the flow around an airfoil for various Mach numbers and angles of attack in the transonic regime. POD uses a few numerical simulations, called snapshots, to create eigenfunctions. These eigenfunctions are combined using weighting coefficients to create a new solution for different values of the input parameters. Since POD methods are linear, their interpolation capabilities are quite limited when dealing with flow presenting nonlinearities, such as shocks. In order to improve their performance for cases involving shocks, a new method is proposed using variable fidelity. The main idea is to use POD to interpolate the difference between the CFD solution obtained on two different grids, a coarse one and a fine one. Then, for any new input parameter value, a coarse grid solution is computed using CFD and the POD interpolated difference is added to predict the fine grid solution. This allows some nonlinearities associated with the flow to be introduced. Results for various Mach numbers and angles of attack are compared to full CFD results. The variable fidelity-based POD method shows good improvement over the classical approach.

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