For the rotor, achieving relatively high aerodynamic performance in specific wind conditions is a long-term goal. Inspired by the remarkable flight characteristics of owls, an optimal trailing edge serration design is investigated and proposed for a wind turbine rotor blade. Fluid flow interaction with the proposed serrations is explored for different wind conditions. The result is supported by subsequent validation with three-dimensional numerical tools. The present work employs a statistical-numerical method to predict and optimize the shape of the serrations for maximum aerodynamic improvement. The optimal combination is found using the Taguchi method with three factors: Amplitude, wavelength, and serration thickness. The viability of the solution on an application is assessed using the Weibull distribution of wind in three selected regions. Results show that the presence of serration is capable of improving the annual power generation in all the investigated cities by up to 12%. The rated speed is also shifted from 10 m/s to 8 m/s for most configurations. Additionally, all configurations show similar trends for the instantaneous torque, where an increase is observed in pre-rated speed, whereas a decrease is noticed in the post-rated speed region. A look at the flow field pattern for the optimal design in comparison with the clean blade shows that the modified blade is able to generate more lift in the pre-stall region, while for the post-stall region, early separation and increased wake dominate the flow.

The rapid growth of urbanization and increasing road traffic congestion are straining ground transportation infrastructure for both conventional and emergency purposes, driving the need for alternative mobility solutions. urban air mobility (UAM) offers a promising pathway by deploying electric vertical takeoff and landing (eVTOL) aircraft to enable efficient and flexible aerial transport in dense urban environments. However, the successful integration of UAM into city airspace faces critical technical challenges, both at the vehicle and operational levels. In particular, complex aerodynamic and aeroacoustic interactions between closely spaced propellers significantly influence vehicle performance, energy efficiency, and public acceptance. This work presents a review of experimental and computational studies on propeller–propeller and propeller–wing interactions, highlighting the state-of-the-art methodologies and their application to multirotor eVTOL designs. Results indicate that distributed electric propulsion systems arranged in side-by-side configurations exhibit minimal thrust degradation, typically less than 3% compared to an isolated propeller. However, reductions in propeller spacing can induce unsteady blade loading and increase tonal noise levels by up to 10 dB. In contrast, one-after-another configurations may suffer thrust losses of up to 80%, due to slipstream ingestion by the rear propeller, with a lateral separation of at least twice the propeller radius required to recover performance within 4% of the isolated case. The review also addresses propeller–wing interactions that modify local pressure distributions and spanwise lift, particularly in wing-mounted distributed propulsion configurations. The insights provided establish a foundation for developing efficient, low-noise multirotor architectures for future UAM integration.

The growing demand for urban air mobility (UAM) has accelerated the development of hybrid/electric vertical takeoff and landing (H-/eVTOL) aircraft, which use distributed propulsion systems that generate complex aerodynamic interactions during forward and transition flight. This study investigates the aerodynamic interactions between two propellers arranged in a one-after-another (OAA) configuration, using unsteady Reynolds-averaged Navier–Stokes (URANS) simulations coupled with the [ ] shear stress transport (SST) turbulence model. The numerical setup was validated against experimental data for the isolated propeller across all investigated advance ratios, showing good agreement. Results reveal that, in forward flight, the rear propeller experiences up to 24% thrust and 20% power loss due to the disturbed airflow created by the wake of the front propeller. This is accompanied by only a 21% increase in axial velocity at the rear propeller location, indicating less effective energy transfer and lower thrust. Pressure coefficient analysis at the rear propeller midspan within the overlap region indicates increased flow separation and lower local loading. During transition, the overlap decreases with tilt, yet at 30° and 60°, the rear propeller still loses up to 11% thrust and 10% power due to slipstream deflection. As the propeller tilt angle increases, the thrust in the propeller axis direction also increases; however, this requires more power and generates a more complex slipstream. These findings provide valuable insights into wake interactions and their influence on rear propeller performance, offering practical design guidelines to improve the efficiency and reliability of UAM vehicles.

The Micro Aerial Vehicles (MAVs) operate at a critical range of low Reynolds number (Re). The implementation of the low (Re) aerodynamics for MAVs has brought interest into the study of high-lift low Re airfoils. Such investigations may bring new insight into the aerodynamic performance of MAVs flights. The aim of the current investigation is to exam different numerical methods in the aerodynamics prediction of high-lift low Reynolds number S1223 airfoil. For that purpose, the Spallart Allmaras (S-A), two equations SST K-ω and the four equations transition γ-Reθ SST turbulence models were used. Results revealed that the SA turbulence model can predict the pre-stall low angles of attack and provides a good agreement with experimental data and XFOIL results. Whereas the two-equation model SST-enhanced K-ɷ and the transition SST models predict better the unsteadiness of the stall behaviour. XFoil accurately predicts the highest lift coefficient, even if it occurs at a lower angle of attack. These results showed the promising ability of the transition SST selection in predicting the stall behaviour.

In recent years, the aerodynamic drag became a major interest of automotive industry as it is one of the main components affecting the fuel consumption. To reduce aerodynamic drag force and improve the energetic efficiency, a complete understanding of the flow around ground vehicles is highly required. This study focused on the accuracy of a three different turbulence models in predicting Ahmed body components drag coefficients. Ahmed Body is a simplified model which mimics the bluff bodies in automotive aerodynamics. This study uses ANSYS Fluent to simulate the flow around Ahmed Body. Three different turbulence models (K-epsilon, K-omega SST and SST) were used in the study. The drag coefficient components for the different sections of the model were validated with the experimental published data. The results have shown that the SST model predicted accurately the total drag coefficient but failed to provide good agreement for the components drag coefficients.