Efficient solution strategies for cabin noise assessment of a wave resolving aircraft fuselage model

TL;DR

This paper explores three advanced computational strategies—discretisation, domain decomposition, and model order reduction—to significantly improve the efficiency of high-fidelity aircraft cabin noise simulations, reducing time and memory costs.

Contribution

It introduces and compares three novel approaches for efficient vibroacoustic simulation of aircraft fuselage models, enhancing computational performance in early design phases.

Findings

Reduced computational time and memory usage for large-scale models

Demonstrated efficiency gains on active research aircraft models

Validated approaches for high-frequency vibroacoustic simulations

Abstract

For the purpose of high-fidelity aircraft cabin noise simulations during early design phases, we study three efficient solving approaches for the fully coupled finite element model of an aircraft fuselage segment. Obtaining an efficient solution with respect to consumed computational time and resources is challenging within a conventional simulation pipeline, as large-scale and complex vibroacoustic models demand crucially high computational costs with increasing frequency. In this contribution, we adopt (1) frequency and domain-adaptive discretisation, (2) domain-decomposition techniques, and (3) model order reduction with rational Arnoldi Krylov subspace methods for an aircraft fuselage model. The three approaches have shown remarkable advantage thereby reducing the solving time as well as the memory requirement that are essential when solving large-scale models. While the discretisation and the model order reduction approaches accelerate the solving process by efficiently handling the complexity of the system to be solved, domain-decomposition techniques further handle the aspect of reducing the overall memory consumption. Finally with the help of active research aircraft models, we implement and showcase the achieved efficiency.