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Active flow control technology is finding increasing use in aerospace applications to control flow separation and improve aerodynamic performance. In this paper we examine the characteristics of a class of fluidic actuators that are being considered for active flow control applications for a variety of practical problems. Based on recent experimental work, such actuators have been found to be more efficient for controlling flow separation in terms of mass flow requirements compared to constant blowing and suction or even synthetic jet actuators. The fluidic actuators produce spanwise oscillating jets, and therefore are also known as sweeping jets. The frequency and spanwise sweeping extent depend on the geometric parameters and mass flow rate entering the actuators through the inlet section. The flow physics associated with these actuators is quite complex and not fully understood at this time. The unsteady flow generated by such actuators is simulated using the lattice Boltzmann based solver PowerFLOW R . Computed mean and standard deviation of velocity profiles generated by a family of fluidic actuators in quiescent air are compared with experimental data. Simulated results replicate the experimentally observed trends with parametric variation of geometry and inflow conditions. Nomenclature

Computational results for an 18%-scale, semi-span Gulfstream aircraft model are presented. Exa Corporation's lattice Boltzmann PowerFLOW® solver was used to perform time-dependent simulations of the flow field associated with this high-fidelity aircraft model. The simulations were obtained for free-air at a Mach number of 0.2 with the flap deflected at 39º (landing configuration). We focused on accurately predicting the prominent noise sources at the flap tips and main landing gear for the two baseline configurations, namely, landing flap setting without and with gear deployed. Capitalizing on the inherently transient nature of the lattice Boltzmann formulation, the complex time-dependent flow features associated with the flap were resolved very accurately and efficiently. To properly simulate the noise sources over a broad frequency range, the tailored grid was very dense near the flap inboard and outboard tips. Extensive comparison of the computed time-averaged and unsteady surface pressures with wind tunnel measurements showed excellent agreement for the global aerodynamic characteristics and the local flow field at the flap inboard and outboard tips and the main landing gear. In particular, the computed fluctuating surface pressure field for the flap agreed well with the measurements in both amplitude and frequency content, indicating that the prominent airframe noise sources at the tips were captured successfully. Gear-flap interaction effects were remarkably well predicted and were shown to affect only the inboard flap tip, altering the steady and unsteady pressure fields in that region. The simulated farfield noise spectra for both baseline configurations, obtained using a Ffowcs-Williams and Hawkings acoustic analogy approach, were shown to be in close agreement with measured values. NomenclatureAOA = angle-of-attack C L = lift coefficient Cp' rms = unsteady RMS pressure coefficient Cp = pressure coefficient c = local chord DNS = Direct Numerical Simulation DES = Detached Eddy Simulation MDDES = Modified Delayed Detached Eddy Simulation GAC = Gulfstream Aerospace Corporation Hz = Hertz, cycles per second LES = Large Eddy Simulation M = Mach number PSD = power spectral density in [psi 2 /Hz] or [dB/Hz] psi = pounds per square inch Re = Reynolds number RMS = root mean square * Aerospace Engineer, Computational AeroSciences Branch, Associate Fellow AIAA AIAA 2014-2481 AIAA Aviation 2 RNG = Re-Normalization Group s = second URANS = unsteady Reynolds averaged Navier-Stokes VR = variable resolution X, Y, Z = right handed coordinate system

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