Taking a lead from the humpback whale flukes, characterized by a series of bumps that result in a sinusoidal-like leading edge, this paper reports on a three-dimensional numerical study of sinusoidal leading edges on cambered airfoil profiles. The turbulent flow around the cambered airfoil with the sinusoidal leading edge was computed at different angles of attack with the open source solver OpenFOAM, using two different eddy viscosity models integrated to the wall. The reported research focused on the effects of the modified leading edge in terms of lift-to-drag performance and the influence of camber on such parameters. For these reasons a comparison with a symmetric airfoil is provided. The research was primarily concerned with the elucidation of the fluid flow mechanisms induced by the bumps and the impact of those mechanisms on airfoil performance, on both symmetric and cambered profiles. The bumps on the leading edge influenced the aerodynamic performance of the airfoil, and the lift curves were found to feature an early recovery in post-stall for the symmetric profile with an additional gain in lift for the cambered profile. The bumps drove the fluid dynamic on the suction side of the airfoil, which in turn resulted in the capability to control the separation at the trailing edge in coincidence with the peak of the sinusoid at the leading edge.

The integration of rotating machineries in human-populated environments requires to limit noise emissions, with multiple aspects impacting on control of amplitude and frequency of the acoustic signature. This is a key issue to address and when combined with compliance of minimum efficiency grades, further complicates the design of axial fans. The aim of this research is to assess the capability of unsupervised learning techniques in unveiling the mechanisms that concur to the sound generation process in axial fans starting from high-fidelity simulations. To this aim, a numerical dataset was generated by means of large Eddy simulation (LES) simulation of a low-speed axial fan. The dataset is enriched with sound source computed solving a-posteriori the perturbed convective wave equation (PCWE). First, the instantaneous flow features are associated with the sound sources through correlation matrices and then projected on latent basis to highlight the features with the highest importance. This analysis in also carried out on a reduced dataset, derived by considering two surfaces at 50% and 95% of the blade span. The sampled features on the surfaces are then exploited to train three cluster algorithms based on partitional, density and Gaussian criteria. The cluster algorithms are optimized and their results are compared, with the Gaussian Mixture one demonstrating the highest similarity (>80%). The derived clusters are analyzed, and the role of statistical distribution of velocity and pressure gradients is underlined. This suggests that design choices that affect these aspects may be beneficial to control the generation of noise sources.

Members of the aerospace fan community have systematically developed computational methods over the last five decades. The complexity of the developed methods and the difficulty associated with their practical application ensured that, although commercial computational codes date back to the 1980s, they were not fully exploited by industrial fan designers until the beginning of the 2000s. The application of commercial codes proved to be problematic as, unlike aerospace fans, industrial fans include electrical motors and other components from which the flow will invariably separate. Consequently, industrial fan designers found the application of commercial codes challenging. The decade from 2000 to 2010 was focused on developing techniques that would facilitate converged solutions that predicted the fans’ performance characteristics over the stable part of their operating range with reasonable accuracy, using a practical computational effort. In this paper, we focus on elucidating aspects of the flow physics that one cannot easily study in a laboratory environment, discussing the challenges involved and the relative merits of the available modelling techniques. The paper ends with a discussion of the practical problems associated with the use of commercial codes in a development environment and finally the legislation that is driving the need for aerospace style computation methods.

In this paper we discuss a computational method focused on the prediction of unsteady aerodynamics, adequate for industrial turbomachinery. Here we focus on a single rotor device selected from a new family of large tunnel ventilation axial flow fans. The flow field in the fan was simulated using the open source code OpenFOAM, with a large-eddy simulation (LES) approach. The sub-grid scale (SGS) closure relied on a one-equation model, that requires us to solve a differential transport equation for the modeled SGS turbulent kinetic energy. The use of such closure was here considered as a remedial strategy in LES of high-Reynolds industrial flows, being able to tackle the otherwise insufficient resolution of turbulence spectrum. The results show that LES of the fan allows to predict the pressure rise capability of the fan and to reproduce the most relevant flow features, such as three-dimensional separation and secondary flows.