Bio-Inspired Axial Fan Design, 3D Printing Fabrication and Characterization for Noise and Flow Performance Optimization

Noise pollution from mechanical ventilation systems is an increasingly critical issue in the context of global energy transition, post-pandemic air quality requirements, and stringent environmental acoustic regulations. In this context, axial-flow fans represent a key technological component, acting as major sources of both tonal and broadband aerodynamic noise, with direct implications for public health, building energy performance, and urban liveability. Mechanical fans, particularly axial configurations, represent a primary source of both tonal and broadband noise, with direct implications for public health, building energy performance, and urban liveability. This research investigates the aeroacoustic noise generation mechanisms in axial-flow ventilation systems through an integrated analytical, numerical, and experimental approach. The study focuses on the fundamental airfoil-level processes that govern noise generation, as these elements constitute the building blocks of fan blades and rotor–stator interactions. The overall objective is to develop predictive tools and passive noise-control strategies for next-generation low-noise axial fan systems. The analysis begins with the investigation of airfoil self-noise mechanisms, which dominate broadband aerodynamic emissions and form the basis for understanding noise generation in axial fan components. A one-dimensional predictive framework, combined with a two-stage Morris sensitivity analysis, identifies the key aerodynamic, geometric, and turbulence-related parameters influencing sound pressure levels, including Mach number, chord length, trailing edge bluntness, and boundary layer displacement thickness. Inspired by the silent flight mechanisms of owls, bio-inspired trailing-edge serrations are then investigated as a passive control strategy for noise reduction in airfoil-based configurations relevant to axial fans. A hybrid numerical–experimental methodology, based on Large Eddy Simulations (LES) of the incompressible Navier–Stokes equations in vorticity formulation and acoustic analogy models, demonstrates the potential for noise reduction with minimal aerodynamic penalties. The optimization of serration distributions is carried out based on identified aerodynamic and acoustic influence regions, incorporating fan laws equations to predict their impact on overall system performance. The influence of surface tripping devices on aerodynamic transition and trailing-edge noise generation is then examined. These effects are analysed in relation to their role in controlling boundary-layer behaviour on airfoil sections representative of fan blades. Numerically, variations in trip height, depth, and position are studied on different airfoil chords using wall-modelled LES simulations, while experimental investigations are conducted on a representative airfoil profile across varying Reynolds numbers. These analyses, supported by Particle Image Velocimetry (PIV) and acoustic beamforming measurements, reveal the role of laminar separation bubbles and trip location in controlling boundary-layer development and acoustic scattering. Finally, the developed noise-control strategies are integrated at the system level, where their combined effects on rotor aerodynamic and acoustic performance are assessed. A rotor–stator configuration representative of axial fan systems is analysed to evaluate the cumulative impact of these solutions and to validate the proposed predictive framework. Overall, this research provides a unified framework linking airfoil-scale aeroacoustic mechanisms to the performance of axial-flow fan systems, delivering validated bio-inspired noise-reduction strategies and predictive methodologies for the design of next-generation low-noise ventilation technologies.