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Dragonfly Rotor Optimization using Machine Learning Applied to an OVERFLOW Generated Airfoil Database

NASA’s 4th New Frontiers Mission is the Titan Dragonfly relocatable lander. This coaxial quadrotor vehicle will be launched on a rocket to Titan in 2028. Following a gravity assisted Earth flyby and an approximate 6-year transit, Dragonfly will enter the Titan atmosphere around 2034 with the goal of exploring Titan’s pre-biotic chemistry and habitability. The multirotor design for this unique application has continually evolved since 2016 with constraints such as Titan’s cryogenic atmosphere at 95 Kelvin (-288 F), gravity 14% that of Earth’s, atmospheric density 440% of standard sea-level air, and the inability to test the entire system together under all these conditions until the first flight on Titan. This paper focuses on rotor design aspects of the Dragonfly lander and introduces a novel framework for multirotor design optimization considering multiple flight conditions. The methodology leverages machine learning methods and is demonstrated in the context of Dragonfly. A new OVERFLOW Machine Learning Airfoil Performance (PALMO) database is first presented. PALMO is then wrapped inside a Bayesian optimization framework and applied to a 4-rotor system (one side of the Dragonfly lander). Training data is generated on each iteration of the optimization using the CAMRAD-II comprehensive analysis software to evaluate successive rotor designs in multiple relevant flight conditions. An optimal design for the 4-rotor system was found with approximately 900 rotor designs analyzed in CAMRAD-II, which required 9 million queries of the PALMO surrogate models. This demonstration case evaluated 10,000,000 potential candidate rotor designs in 5.5 hours on 114 CPU cores using uniform inflow, and in 27.8 hours using the prescribed wake model. This work thus enables mid-fidelity rotor design optimization without requiring access to high-performance computing.

Dragonfly↗

Full Scale Rotor Aeroacoustic Predictions and the Link to Model Scale Rotor Data

The NASA Aeroacoustic Prediction System (NAPS) is used to establish a link between model-scale and full-scale rotor predictions and is partially validated against measured wind tunnel and flight aeroacoustic data. The prediction approach of NAPS couples a comprehensive rotorcraft analysis with acoustic source noise and propagation codes. The comprehensive analysis selected for this study is CAMRAD-II, which provides the performance/trim/wake solution for a given rotor or flight condition. The post-trim capabilities of CAMRAD-II are used to compute high-resolution sectional airloads for the acoustic tone noise analysis, WOPMOD. The tone noise is propagated to observers on the ground with the propagation code, RNM (Rotor Noise Model). Aeroacoustic predictions are made with NAPS for an isolated rotor and compared to results of the second Harmonic Aeroacoustic Rotor Test (HART-II) program, which tested a 40% dynamically and Mach-scaled BO-105 main rotor at the DNW. The NAPS is validated with comparisons for three rotor conditions: a baseline condition and two Higher Harmonic Control (HHC) conditions. To establish a link between model and full-scale rotor predictions, a full-scale BO-105 main rotor input deck for NAPS is created from the 40% scale rotor input deck. The full-scale isolated rotor predictions are then compared to the model predictions. The comparisons include aerodynamic loading, acoustic levels, and acoustic pressure time histories for each of the three conditions. With this link established, full-scale predictions are made for a range of descent flight conditions and compared with measured trends from the recent Rotorcraft Operational Noise Abatement Procedures (RONAP) flight test conducted by DLR and ONERA. Additionally, the effectiveness of two HHC conditions from the HART-II program is demonstrated for the full-scale rotor in flight.

Boyd, D. Douglas, Jr.↗

Blade-Vortex Interaction (BVI) Noise and Airload Prediction Using Loose Aerodynamic/Structural Coupling

Predictions of blade-vortex interaction (BVI) noise, using blade airloads obtained from a coupled aerodynamic and structural methodology, are presented. This methodology uses an iterative, loosely-coupled trim strategy to cycle information between the OVERFLOW-2 (CFD) and CAMRAD-II (CSD) codes. Results are compared to the HART-II baseline, minimum noise and minimum vibration conditions. It is shown that this CFD/CSD state-of-the-art approach is able to capture blade airload and noise radiation characteristics associated with BVI. With the exception of the HART-II minimum noise condition, predicted advancing and retreating side BVI for the baseline and minimum vibration conditions agrees favorably with measured data. Although the BVI airloads and noise amplitudes are generally under-predicted, this CFD/CSD methodology provides an overall noteworthy improvement over the lifting line aerodynamics and free-wake models typically used in CSD comprehensive analysis codes.

Sim, B. W.↗

Initial Aerodynamic and Acoustic Study of an Active Twist Rotor Using a Loosely Coupled CFD/CSD Method

Preliminary aerodynamic and performance predictions for an active twist rotor for a HART-II type of configuration are performed using a computational fluid dynamics (CFD) code, OVERFLOW2, and a computational structural dynamics (CSD) code, CAMRAD -II. These codes are loosely coupled to compute a consistent set of aerodynamics and elastic blade motions. Resultant aerodynamic and blade motion data are then used in the Ffowcs-Williams Hawkins solver, PSU-WOPWOP, to compute noise on an observer plane under the rotor. Active twist of the rotor blade is achieved in CAMRAD-II by application of a periodic torsional moment couple (of equal and opposite sign) at the blade root and tip at a specified frequency and amplitude. To provide confidence in these particular active twist predictions for which no measured data is available, the rotor system geometry and computational set up examined here are identical to that used in a previous successful Higher Harmonic Control (HHC) computational study. For a single frequency equal to three times the blade passage frequency (3P), active twist is applied across a range of control phase angles at two different amplitudes. Predicted results indicate that there are control phase angles where the maximum mid-frequency noise level and the 4P non -rotating hub vibrations can be reduced, potentially, both at the same time. However, these calculated reductions are predicted to come with a performance penalty in the form of a reduction in rotor lift-to-drag ratio due to an increase in rotor profile power.

Boyd, David D. Jr.↗

FUN3D Airload Predictions for the Full-Scale UH-60A Airloads Rotor in a Wind Tunnel

An unsteady Reynolds-Averaged Navier-Stokes solver for unstructured grids, FUN3D, is used to compute the rotor performance and airloads of the UH-60A Airloads Rotor in the National Full-Scale Aerodynamic Complex (NFAC) 40- by 80-foot Wind Tunnel. The flow solver is loosely coupled to a rotorcraft comprehensive code, CAMRAD-II, to account for trim and aeroelastic deflections. Computations are made for the 1-g level flight speed-sweep test conditions with the airloads rotor installed on the NFAC Large Rotor Test Apparatus (LRTA) and in the 40- by 80-ft wind tunnel to determine the influence of the test stand and wind-tunnel walls on the rotor performance and airloads. Detailed comparisons are made between the results of the CFD/CSD simulations and the wind tunnel measurements. The computed trends in solidity-weighted propulsive force and power coefficient match the experimental trends over the range of advance ratios and are comparable to previously published results. Rotor performance and sectional airloads show little sensitivity to the modeling of the wind-tunnel walls, which indicates that the rotor shaft-angle correction adequately compensates for the wall influence up to an advance ratio of 0.37. Sensitivity of the rotor performance and sectional airloads to the modeling of the rotor with the LRTA body/hub increases with advance ratio. The inclusion of the LRTA in the simulation slightly improves the comparison of rotor propulsive force between the computation and wind tunnel data but does not resolve the difference in the rotor power predictions at mu = 0.37. Despite a more precise knowledge of the rotor trim loads and flight condition, the level of comparison between the computed and measured sectional airloads/pressures at an advance ratio of 0.37 is comparable to the results previously published for the high-speed flight test condition.

Lee-Rausch, Elizabeth M.↗