# Advancements and Applications of Rim-Driven Fans in Aerial Vehicles: A Comprehensive Review
## 9 FEA and CFD
The modeling approaches by [PERSON] et al. demonstrated performance results that closely matched the experimental data, with deviations of less than 5% across a range of advance ratios when assessed using a Wageningen B4-70 propeller [67]. [PERSON] et al. (2008) discussed a model for designing a naval propulsion system that integrates electromagnetic and hydrodynamic factors [99]. The model takes into account both the electromagnetic forces that drive the motor and the fluid dynamics that determine the thrust generated by the rotor (Figure 8). The goal of the model is to optimize the system for maximum efficiency and reliability in marine environments. The article described the various components of the model and shows how it was used to design and test a prototype of the system. [PERSON] et al. delve into the prediction of hydrodynamic performance for a rim-driven thruster, considering different duct designs (as depicted in Figure 9) and incorporating modeling for transition turbulence. The researchers conducted numerical simulations using a 3D unsteady Reynolds-averaged Navier-Stokes solver, and compared the results with experimental measurements. The study found that the inclusion of transition turbulence modeling significantly improved the prediction accuracy of thrust and torque coefficients for the rim-driven thruster. The results also showed that the duct design has an impact on the hydrodynamic performance of the thruster, with the presence of a stator blade enhancing the performance at low advance coefficients. Overall, the article highlights the importance of considering transition turbulence modeling in predicting the hydrodynamic  
Figure 8: Coupled hydro and EM/thermal models [99]. Figure 7: Rim-driven thruster surface mesh [98] (Copyright (2023), with permission from Elsevier). performance of rim-driven thrusters, which can aid in their design and optimization for various applications [100]. [PERSON] present a simulation-based design optimization tool for rim-driven thrusters including a parametric description of blade geometry and a multi-objective algorithm driven by high-fidelity calculations [26] (Figure 10). The design process utilizes B-spline curves for blade geometry, RANS calculations, and a genetic algorithm. Four blade configurations are tested, and the optimized propellers outperform a benchmark ducted propeller. The number of blades does not significantly impact cavitation risk. Computational cost is a constraint, and exploring faster algorithms could enhance the design process. Overall, the tool proves effective in improving performance and minimizing cavitation in rim-driven thrusters. Faster calculation methods could enhance convergence. Figure 10: Study of cavitation risk and tip vortices [26]. (Copyright (2023), with permission from Elsevier). Figure 9: (**A**) The streamline patterns under different loading conditions for duct 19A (**top**), duct 37 (**middle**), and duct Sym (**bottom**); (**B**) the vorticity distribution in the wake at distances behind the propeller for duct 19A (**top**), duct 37 (**middle**), and duct Sym (**bottom**) [100]. (Copyright (2023), with permission from Elsevier). The study by [PERSON] et al. compared the performance of an RDF with an equivalently sized electric ducted fan (EDF) [101]. The study discovered that the RDF configuration outperforms the EDF in terms of thrust, providing 212 N compared to the EDF's 95 N, and achieving a higher RDF efflux velocity of 150 m/s (equivalent to 336 mph) as opposed to the EDF's 103 m/s (230 mph). Researchers initially used a 2D pitch-line methodology to determine the initial fan blade shapes and velocity estimates. However, there was a significant discrepancy in the calculated thrust values between the 2D pitch-line methodology (317 N) and the CFD model (212 N). This difference was partly attributed to an overly optimistic assumption regarding the effective through-flow area of the hubless configuration in the 2D pitch-line approach.