The present paper proposes the development of surrogate models for the description of acoustic emission of multi-propeller configurations, like those adopted by the vast majority of the Urban-Air-Mobility concepts nowadays under investigation. This approach represents an interesting and efficient solution for the aeroacoustic characterization of electrically-powered propeller array, for which reliable and cost-efficient aeroacoustic models are still lacking, and the application of costly high-fidelity tools is mandatory. The numerical investigation focuses on surrogate models that take into account the effects of geometric parameters, such as propeller hubs relative positions and de-phasing, on the propeller array noise emissions. A well-known Artificial Neural Network metamodelling technique is applied on a numerical database obtained through a boundary integral formulation for the solution of incompressible potential flows around lifting/thrusting bodies, followed by the application of the Farassat 1A boundary integral formulation for the noise field evaluation. Due to the proposed non-standard application of the metamodelling technique applied, particular attention is paid to identifying the best strategy to exploit a database with a minimal number of samples with respect to those managed in the standard application of machine learning technique.

Poggi, C., Rossetti, M., Bernardini, G., Gennaretti, M., Iemma, U. (2021). Metamodelling techniques for propeller array far-field noise. In Proceedings of INTER-NOISE 2021 - 2021 International Congress and Exposition of Noise Control Engineering (pp.2674-2686). The Institute of Noise Control Engineering of the USA, Inc. [10.3397/IN-2021-2203].

Metamodelling techniques for propeller array far-field noise

Poggi C.;Rossetti M.;Bernardini G.;Gennaretti M.;Iemma U.
2021-01-01

Abstract

The present paper proposes the development of surrogate models for the description of acoustic emission of multi-propeller configurations, like those adopted by the vast majority of the Urban-Air-Mobility concepts nowadays under investigation. This approach represents an interesting and efficient solution for the aeroacoustic characterization of electrically-powered propeller array, for which reliable and cost-efficient aeroacoustic models are still lacking, and the application of costly high-fidelity tools is mandatory. The numerical investigation focuses on surrogate models that take into account the effects of geometric parameters, such as propeller hubs relative positions and de-phasing, on the propeller array noise emissions. A well-known Artificial Neural Network metamodelling technique is applied on a numerical database obtained through a boundary integral formulation for the solution of incompressible potential flows around lifting/thrusting bodies, followed by the application of the Farassat 1A boundary integral formulation for the noise field evaluation. Due to the proposed non-standard application of the metamodelling technique applied, particular attention is paid to identifying the best strategy to exploit a database with a minimal number of samples with respect to those managed in the standard application of machine learning technique.
2021
Poggi, C., Rossetti, M., Bernardini, G., Gennaretti, M., Iemma, U. (2021). Metamodelling techniques for propeller array far-field noise. In Proceedings of INTER-NOISE 2021 - 2021 International Congress and Exposition of Noise Control Engineering (pp.2674-2686). The Institute of Noise Control Engineering of the USA, Inc. [10.3397/IN-2021-2203].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/398206
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