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A computational fluid dynamics (CFD) model is coupled with a computational structural dynamics (CSD) model to improve prediction of helicopter rotor vibratory loads in high-speed flight. The two key problems of articulated rotor aeromechanics in high-speed flight-advancing blade lift phase, and underprediction of pitch link load-are satisfactorily resolved for the UH-60A rotor. The physics of aerodynamics and structural dynamics is first isolated from the coupled aeroelastic problem. The structural and aerodynamic models are validated separately using the UH-60A Airloads Program data. The key improvement provided by CFD over a lifting-line aerodynamic model is explained. The fundamental mechanisms behind rotor vibration at high speed are identified as: 1) large elastic twist deformations and 2) inboard wake interaction. The large twist deformations are driven by transonic pitching moments at the outboard stations. CFD captures 3-dimensional unsteady pitching moments at the outboard stations accurately. CFD/CSD coupling improves elastic twist deformations via accurate pitching moments and captures the vibratory lift harmonics correctly. At the outboard stations (86.5% radius out), the vibratory lift is dominated by elastic twist. At the inboard stations (67.5% and 77.5% radius), a refined wake model is necessary in addition to accurate twist. The peak-to-peak pitch link load and lower harmonic waveform are accurately captured. Discrepancies for higher harmonic torsion loads remain unresolved even with measured airloads. The predicted flap-bending moments show a phase shift of about 10 deg over the entire rotor azimuth. This error stems from 1, 2, and 3/rev lift. The 1/rev lift is unaffected by CFD/CSD coupling. The 2 and 3/rev lift are significantly improved but do not fully resolve the 2 and 3/rev bending moment error. IntroductionT HE objective of this paper is to improve the prediction of rotor vibratory loads by replacing the lifting-line aerodynamic model of a comprehensive rotor analysis with computational fluid dynamics (CFD). The focus is on high-speed level flight of the UH-60A Blackhawk (155 kn, μ = 0.368). The state of the art in helicopter vibration prediction in high-speed flight is far from satisfactory 1 even though both vibratory airloads and structural response show consistent patterns for a large number of helicopters. 2,3 Prediction accuracy of vibratory blade loads is less than 50%. Measurements from the UH-60A Air Loads program 4 open the opportunity to trace back the sources of prediction deficiencies to discrepancies in airload calculation.Bousman in 1999 (Ref. 5) identified two key discrepancies in articulated rotor aeromechanics: 1) prediction of negative lift phase on the advancing side in high-speed flight and 2) underprediction of pitch link load (by 50%). The error in pitch link load stems from errors in pitching moment predictions. Figure 1 shows state-of-the-art lift and pitching moment predictions from lifting-line comprehensive analyses CAMRAD/JA and 2GCHAS (Ref. 6). The drop in th...

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This paper describes a computational infrastructure that supports Chimera-based interfacing of different CFD solvers-a body-fitted unstructured grid solver with a blockstructured adaptive cartesian grid solver-to perform time-dependent adaptive movingbody CFD calculations of external aerodynamics. The goal of this infrastructure is to facilitate the use of different solvers in different parts of the computational domain-body fitted unstructured to capture viscous near-wall effects, and cartesian adaptive mesh refinement to capture effects away from the wall. The computational infrastructure, written using Python, orchestrates execution of the different solvers and coordinates data exchanges between them, controlling the overall time integration scheme. Details about the infrastructure used to integrate the codes, the parallel implementation, and results from demonstration calculations are presented.

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A parallel high-order Discontinuous Galerkin (DG) method is used to solve the compressible Navier-Stokes equations on an overset mesh framework. The DG solver has many capabilities including: hp-adaption, curved cells, and support for hybrid, mixed element meshes. Combining these capabilities with overset grids allows the DG solver to be used in problems with bodies moving in relative motion to be combined in a near-body off-body solver strategy. The overset implementation is constructed to preserve the design accuracy of the baseline DG discretization. Multiple simulations are carried out to validate the accuracy and performance of the overset DG solver. These simulations demonstrate the capability of the high-order DG solver to handle complex geometry, hp-adaption, and large scale parallel simulations in an overset framework.