A Novel Multipolar Expansion for Acoustic Footprint Reduced Order Modeling

Abstract

Abstract. High-fidelity computational aeroacoustic simulations are often too computationally expensive for rapid evaluation of aircraft noise, especially when assessing full-system acoustic footprints during operations. This work introduces a physics-informed multipolar-expansion methodology that generates equivalent acoustic sources capable of accurately reproducing complex pressure fields in both near- and far-field regions at a fraction of the computational cost. The method employs expansions from monopoles to higher-order terms for noise modeling and prediction, using spherical harmonics as a complete basis of the Helmholtz equation. Acoustic moments coefficients are identified through linear regression analysis of pressure data obtained from numerical or experimental sampling, enabling the accurate reconstruction of the acoustic field once the coefficients are determined. The methodology is assessed using two representative aeroacoustic problems: a helicopter rotor operating in Blade–Vortex Interaction conditions and a subsonic jet at Mach 0.9 with varying nozzle temperatures. The results show excellent agreement with reference data, maintaining amplitude accuracy up to the far field while drastically reducing computational time. The proposed reduced-order model demonstrates strong robustness and generalizability, offering a fast and physically grounded tool for aerodynamic optimization, real-time control, and digital-twin frameworks, enabling efficient and scalable noise prediction in complex aeroacoustic environments.