Numerical Prediction of Fluid Flow Noise with a Hybrid CFD-Acoustics Approach

<div class="section abstract"><div class="htmlview paragraph">This paper presents a fully parallelized Computational Acoustics (CA) module, integrated within the Simerics-MP+ platform, developed for the prediction of noise source power and far-field propagation across a range of Computational Fluid Dynamics (CFD) applications. Utilizing the Ffowcs Williams-Hawkings (FWH) acoustic analogy, the CA module seamlessly integrates with existing CFD workflows, offering minimal computational overhead with less than a 5% increase in runtime. Extensive validation has been conducted against analytical, numerical, and experimental data in various acoustic scenarios, including monopole and dipole noise emissions, flow around slender bodies, circular cylinders and aero-propellers. These validation studies underscore the reliability of the framework in accurately identifying noise sources and assessing the impact of design modifications, significantly reducing the need for expensive physical prototyping in industries such as automotive and aerospace.</div><div class="htmlview paragraph">Building upon these foundational capabilities, the study extends the application of the CA module to the challenging task of noise simulation in axial fans, commonly employed in HVAC systems, automotive components, and industrial processes. Given the proximity of axial fans to human operators, noise control is critical, necessitating compliance with stringent regulatory standards. In low-Mach-number fans, aerodynamic fluctuations and complex flow interactions are key contributors to noise emissions. By combining Wall-Modeled Large Eddy Simulation (LES) with the FWH approach in a second-order finite volume framework within the platform, the study simulates the European Acoustics Association (EAA) benchmark case of a ducted axial fan across various flow rates. Validation against experimental data shows good agreement, demonstrating the effectiveness of this approach in facilitating virtual testing. This methodology enables engineers to implement noise mitigation strategies early in the design process, reducing development costs and enhancing overall system performance.</div></div>