High-Fidelity Multidisciplinary Design Optimization of Low-Noise Rotorcraft
Li Wang, Boris Diskin, National Institue of Aerospace; Leonard Lopes, Eric Nielsen, Elizabeth Lee-Rausch, Robert Biedron, NASA Langley Research Center

High-Fidelity Multidisciplinary Design Optimization of Low-Noise Rotorcraft
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- SKU # : 75_2019_0184_Wang
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High-Fidelity Multidisciplinary Design Optimization of Low-Noise Rotorcraft
Authors / Details: Li Wang, Boris Diskin, National Institue of Aerospace; Leonard Lopes, Eric Nielsen, Elizabeth Lee-Rausch, Robert Biedron, NASA Langley Research CenterAbstract
A high-fidelity multidisciplinary analysis and optimization methodology is presented for low-noise rotorcraft design.Tightly coupled discipline models include physics-based computational fluid dynamics, rotorcraft comprehensive analysis,and acoustic-noise prediction and propagation. A discretely-consistent adjoint methodology accounts for sensitivitiesof the unsteady flow and unstructured, dynamically deforming, overset grids. The sensitivities of structuralresponses to blade aerodynamic loads are computed using a complex-variable approach. Sensitivities of the acousticmetrics are computed by manual differentiation. Interfaces are developed to enable interactions between the coupleddiscipline models for rotorcraft aeroelastic and aeroacoustic analysis and the integrated sensitivity analysis. Themultidisciplinary sensitivity analysis is verified through a complex-variable perturbation approach. A gradient-basedoptimization for a HART-II rotorcraft configuration in a forward-flight condition is demonstrated with the objectiveof reducing a rotorcraft noise metric of interest, subject to aerodynamic and geometric constraints. The optimizedconfiguration achieves a notable noise reduction and satisfies all required constraints. Computational cost of the optimizationcycle is assessed in a high-performance computing environment and found to be acceptable for design ofrotorcraft in general level-flight conditions.
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High-Fidelity Multidisciplinary Design Optimization of Low-Noise Rotorcraft
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