Comparative Evaluation of Propeller Modeling Approaches for Efficient Simulations of Wing–Propeller Interaction

Harnessing renewable and clean energy resources from winds and tides are promising technologies to alter the high level of consumption of traditional energy resources because of their great global potential. In this regard, developing farms with multiple energy converters is of great interest due to the skyrocketing demand for sustainable energy resources. However, the numerical simulation of these farms during the planning phase might pose challenges, the most significant of which is the computational cost. One of the most well-known approaches to resolve this concern is to use the virtual blade model (VBM). VBM is the implementation of the blade element model (BEM). This was done by coupling the blade element momentum theory equations to simulate rotor operation with the Reynolds averaged Navier–Stokes (RANS) equation to simulate rotor wake and the turbulent flow field around it. The exclusion of the actual geometry of blades enables a lower computational cost. Additionally, due to simplifications in the meshing procedure, VBM is easier to set up than the models that consider the actual geometry of blades. One of the main unaddressed limitations of the VBM code is the constraint of modeling up to 10 renewable energy converters within one computational domain. This paper provides a detailed and well-documented general methodology to develop a virtual blade model for the simulation of 10-plus converters within one computational domain to remove the limitation of this widely used and robust code. The extended code is validated for both the single- and multi-converter scenarios. It is strongly believed that the technical contribution of this paper, combined with the current advancement of available computational resources and hardware, can open the gates to simulate farms with any desired number of wind or tidal energy converters, and, accordingly, secure the sustainability and feasibility of clean energies.

The present study describes the computational methodology adopted to evaluate the aerodynamic characteristics of a shrouded tail rotor. The dependence of the aerodynamic characteristics of a shrouded rotor on the shroud geometry and flight condition deeply affects the accuracy in estimating the thrust sharing of the antitorque system. Experimental testing and numerical investigations have been carried out in the past to characterize the shrouded tail rotor performance and the influence of the variation of the characteristic geometrical parameters. In this study, a modified Virtual Blade Model (VBM) approach has been exploited to model the structure of the flow field produced by the AW09 shrouded tail rotor operating in hover. The proposed modified VBM was tested on the isolated configuration along with the canonical model implementation. By correlation with experimental and numerical data, the introduced modification translated into modeling improvements both in terms of accuracy and stability. Finally, the modified model has been applied to the shrouded configuration by means of RANS and SBES simulations, and again the results are compared with experimental and numerical data. During the analysis different turbulence models were tested. The performance predictions achieved through Virtual Blade Modeling show a close correlation with the ones obtained by adopting a fully resolved blade approach with a significant saving in computational cost.

Agricultural unmanned aerial vehicles (UAVs), increasingly integral to crop protection through spraying operations, are significantly influenced by their downwash fields, which in turn affect the distribution of spray droplets. The key parameters impacting spray deposition patterns are the velocity of the downwash airflow and its spatial extent. Understanding the interplay of these parameters can enhance the efficacy of UAV applications in agriculture. Previous research has predominantly focused on downwash airflow velocity, often neglecting the spatial scope of the downwash. This paper presents an applied foundational study grounded in the compressible Reynolds-averaged Navier–Stokes (RANS) equations. Leveraging a dependable k-ε turbulence model and dynamic mesh technology, it develops an effective three-dimensional computational fluid dynamics (CFD) approach to analyze the downwash field’s distribution characteristics during UAV hover. To validate the CFD method, a visualization test was conducted using EPS (expanded polystyrene foam) balls dispersed in the airspace beneath the UAV, illustrating the airflow’s spatial distribution. Additionally, a parameter η was introduced to quantify changes in the wind field’s range, enabling the mapping of the cross-sectional area of the downwash airflow at various velocities within the UAV’s airspace. The study reveals that the downwash field’s overall shape evolves from a “four-point type” to a “square-like” and then to an “ellipse-like” configuration. Lower downwash airflow velocities exhibit a more rapid expansion of the wind field area. High-velocity downwash areas are concentrated beneath each rotor, while lower-velocity zones coalesce under each rotor and extend downward, forming a continuous expanse. Within the UAV’s downwash area, the deposition of droplets is more pronounced. At a given nozzle position, an increase in downwash airflow velocity correlates with greater droplet deposition within the downwash field. This research bridges a gap in downwash field studies, offering a solid theoretical foundation for the development of future UAV downwash field models.

Assessment of the methodology for the CFD simulation of the flight of a quadcopter UAV

This study employed a combined approach of computational fluid dynamics (CFD), numerical simulations, and wind tunnel tests to investigate droplet drift characteristics and develop prediction models in order to address the issues of low pesticide utilization rates and high drift risk, associated with droplet drift during agricultural unmanned aerial vehicle (UAV) spraying, as well as the unreliable results of field experiments. Firstly, a numerical model of the rotor wind field was established using the multiple reference frame (MRF) method, while the realizable k-ε turbulence model was employed to analyze the flow field. The model’s reliability was verified through wind field tests. Next, the Euler–Lagrange method was used to couple the wind field with droplet movement. The drift characteristics of two flat-fan nozzles (FP90-02 and F80-02) were then compared and analyzed. The results showed that the relative error between the simulated and wind tunnel test values was within 20%. Centrifugal nozzle experiments were carried out using single-factor and orthogonal designs to analyze the effects of flight height, rotor wind speed, flight speed, and droplet size on drift. The priority order of influence was found to be “rotor wind speed > flight height > flight speed”, while droplet size (DV50 = 100–300 µm) was found to have no significant effect. Based on the simulation data, a multiple linear regression drift prediction model was constructed with a goodness of fit R2 value of 0.9704. Under the verification condition, the relative error between the predicted and simulated values was approximately 10%. These results can provide a theoretical basis and practical guidance for assessing drift risk and optimizing operational parameters for agricultural UAVs.

Aerodynamic characteristics of a guided rocket projectile are numerically simulated. Simulations are performed in a range of flight conditions using a commercial CFD software FLUENT, and variations of lift coefficients and drag coefficients with Mach numbers and angles of attack were demonstrated. The numerical results also indicate that the angle of canard deflection has significant influence on the flow field near tailfins.

Kenyalang is a fuel cell powered Unmanned Aerial Vehicle (UAV) developed by Universiti Teknologi MARA (UiTM). This paper discusses the aircraft performances analysis of Kenyalang. Computational Fluid Dynamic (CFD) using Numeca software had been performed to obtain the aerodynamics characteristic of the Kenyalang UAV in the form of lift (CL) and drag (CD) coefficients. Unstructured mesh and standard one - equation turbulence model, and Spalart-Allmaras selected in the simulation. Lift coefficients (CL) and drag coefficients (CD) were studied at flight condition of Mach 0.08 (~26 m/s) at different angles of attack, α. The CFD data results were used to obtain Stall Speed, Take off Distance and Rate of Climb, and the results are shown in this paper.

In order to construct a 3D rotor model, periodicity and Multiple Reference Frame (MRF) strategies were applied to address full Computational Fluid Dynamics (CFD) that incorporate the Reynolds-averaged Navier–Stokes (RANS) equations. A simulation model was run to examine the power of the wind turbines, both including and excluding the hub and tower. The purpose of this was to identify an approach that would decrease the computational time cost of wind turbine simulation. Firstly, a full-scale horizontal axis wind turbine simulation was carried out, and subsequently, comparisons were made with the results of the wind tunnel experiment utilizing the K-omega SST and Sparlat Allmaras viscosity models. The results were compared to determine the optimum model with the lowest simulation time and highest accuracy to the experimental results. Following this, the complete models’ simulation was compared to the model excluding the hub and tower in order to check the disparity in the results of the two. Additionally, to ascertain the computational cost saving, the ratio of the two simulation times was established. The findings show that the two models produce results that correspond well to the experimental results, and that the power coefficient had a greater value for the complete model than the simple model. Furthermore, it was found that the power coefficient values of the full model have significantly higher levels of similarity to the experimental values. The Sparlat Allmaras and K-omega SST viscosity models returned error percentages of 0.52% and 12.6% respectively. For the partial model utilizing the same computer device, a 5.7% error rate was recorded, with a computational time saving of approximately 34%.

Unmanned aerial vehicles (UAV) are used in the military field for missions such as observation, surveillance and seeking object. UAV observation can be used to monitor humans, weather, forests, agriculture, and fisheries and so on. UAV can be operated for very broad missions with low development costs compared to manned aerial vehicles with a low risk of death. The design of an aircraft affects the performances of the aircraft itself. Aircraft flying characteristics are influenced by the value of coefficient of drag (CD) and coefficient of lift (CL). The value of CD affects how much aircraft friction with the air, while the value of CL affects how much lifting force the aircraft is produced so it can fly. The design output needs the most optimal CD and CL values to get the optimal aircraft performance. In this study, we simulated the effect of 4 digit NACA changes on the characteristics of the plane’s CD and CL. This study uses variations modification of NACA digits with different variables. NACA airfoil 4 digit series (MPXX) designates camber lines, maximum camber position and thickness. Based on the results of this study, the optimal CD and CL values for the Airfoil NACA with the Aerosonde UAV model are designs that have a large ratio of lift and drag (CL / CD). The lower the CD value and the higher the CL value, the better the performance of the UAV. The design that has the largest CL / CD is the NACA 6412 Airfoil.

In the golden era of digitalization, flow calculation research based on a numerical approach has become increasingly popular in the scientific world and has played a vital role in revealing the aerodynamic characteristics of various aircraft models. This paper, belonging to computational fluid dynamics, describes the process and results of a numerical simulation approach using the software OpenFOAM for an unmanned aerial vehicle (UAV) in the case of forwarding flight with a low Reynolds number. With regard to the numerical approach, the aerodynamic properties are investigated through the turbulence model k-ω-SST (shear stress transport), which is a part of the turbulence calculation approach Reynolds average Navier–Stokes (RANS). Furthermore, the entire process of mesh generation and the numerical calculation process by simpleFoam in OpenFOAM, which is the solver using the semi-implicit method for pressure-linked equations (SIMPLE) algorithm for steady, incompressible flow, are also depicted in this paper. In addition, the characteristics of the flow field surrounding the model and the characteristic aerodynamic coefficients (drag coefficient, lift coefficient, lift-to-drag ratio versus angle of attack and pressure coefficients, and skin-friction coefficients for special positions on the wing) of the model are also clearly illustrated. Finally, the simulation illustrations in ParaView, including the velocity field, pressure field and vortices in the stagnation region, are shown. The process description and results contribute a clear picture of the numerical execution steps in OpenFOAM and aerodynamic knowledge for a particular unmanned aerial vehicle model to the computational fluid dynamics field in the aerospace industry.

There are various configurations and parameters that contribute to the Design of Unmanned Aerial Vehicles for specific applications. This paper deals with an innovative design of an unmanned aerial vehicle for a specified class of UAVs that require demands such as long endurance, minimized landing space with vertical take-off and landing (VTOL) capabilities. The focal point of this design is superimposing the high endurance blended wing design into tri-copter to address these parameters. The preliminary calculations are initially performed for the blended wing VTOL vehicle based on the required payload capacity and endurance. Superimposing the tri-copter will decrease the aerodynamic efficiency of the vehicle. Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical methods and algorithms to solve complex problems involving fluid flow which will effectively employed to reduce the cost and time during the conceptual and preliminary design stages. CFD analysis was carried out to estimate the major parameters like lift, drag, lift coefficient (CL) and drag coefficient (CD) for various Angle of Attack (AoA) for configurations of blended wing vehicle with and without tri-copter system in the cruise condition. Thus, the vehicle design and propulsion system is effectively optimized using this drag estimation.

Unmanned Aerial Vehicles (UAVs) are becoming essential tools in precision agriculture, enabling real-time monitoring, improved land management, and more efficient use of resources. Among them, Vertical Takeoff and Landing (VTOL) UAVs are ideal for operating in confined and uneven agricultural terrains. However, UAVs equipped with inverted-V empennages suffer from aerodynamic drawbacks, including directional instability and adverse yaw under sideslip conditions. This paper advances the state of the art by optimizing the aerodynamic performance of inverted-V tail configurations through the integration of a dorsal fin. Using Computational Fluid Dynamics (CFD), we assess multiple dorsal fin designs on a UAV platform with a maximum takeoff weight of 10 kg, 2 kg payload, 2-hour endurance, 10 m/s stall speed, and a 5 km² operational range. We analyze key aerodynamic metrics—lift and drag coefficients, lift-to-drag ratio, yaw moment coefficient—as well as flow behavior via pressure contours and vorticity plots. Results confirm that sideslip angles degrade aerodynamic efficiency, but a properly designed dorsal fin, particularly variation 2, significantly reduces adverse yaw at higher angles of attack and sideslip. This modification enhances UAV stability and flight performance, marking a meaningful improvement in VTOL UAV design for agricultural applications.

In this project, we intend to design a Canard wing-based Unmanned Aerial Vehicle (UAV), which can carry a wide range of missions, providing capabilities to handle our challenges with sophisticated care. Canard-based UAV is the latest trend in aviation technology designed for the use case of providing better maneuverability, which in result gives the UAV new capabilities, such as increased time for data gathering, transferring, and autonomous behavior. The basic disciplines like Aerodynamics, Engineering design, Flight dynamics, Propulsion, and Performance are carried out during the UAV designing process. The proposed methodology applied in this project is weight estimation, initial sizing, aerofoil and wing geometry, fuselage sizing, tail sizing, T/W ratio, aerodynamics, and performance analysis. The design of Canard Based UAV leads to a deeper understanding of the trade-off studies of the UAV and is demonstrated by optimizing for designed missions like surveillance. A drafted sketch is presented at the end of the design phase featuring the selected configurations of major components.

This study presents a surrogate-model-assisted Quasi-Newton optimisation framework for simultaneously improving the aerodynamic performance and radar stealth characteristics of an unmanned aerial vehicle (UAV). High-fidelity computational fluid dynamics (CFD) and computational electromagnetics (CEM) simulations are integrated through surrogate models generated via a face-centred central composite design within a design of experiments framework. Quadratic polynomial response surface equations are constructed for key aerodynamic and radar cross-section (RCS) metrics, enabling analytical gradient evaluation. A gradient-based quasi-Newton method with Broyden–Fletcher–Goldfarb–Shanno Hessian updates is employed to minimise a scalarised objective function combining normalised maximum lift coefficient, overall RCS and frontal RCS. Constraints are imposed on the lift-to-drag ratio ( $L/D \geq 10$ ) and static longitudinal stability ( ${C_{m0}} \geq 0$ ). Analytical derivatives from the response surface equations (RSEs) eliminate the need for direct numerical differentiation of CFD/CEM outputs, reducing computational cost and eliminating simulation noise. An interior-point sequential quadratic programming strategy is used to ensure satisfaction of nonlinear constraints during the optimisation process. The optimised UAV design demonstrates a $12{\rm{\% }}$ increase in maximum lift coefficient and a $30{\rm{\% }}$ reduction in both overall and frontal RCS compared to the baseline configuration. The results are confirmed through high-fidelity CFD and RCS simulations and are further validated experimentally in an anechoic chamber, with close agreement across all measured frequencies. The proposed methodology provides an efficient and experimentally verified approach for integrated aerodynamic and stealth optimisation in UAV design.

Unmanned Aerial Vehicles (UAVs) stand out as of late because of their different applications in observation, ethereal planning, and information assortment. Aerodynamic productivity is pivotal in boosting UAV execution, especially for flying wing setups. One promising way to improve aerodynamic performance is using dimples on the UAV's wing surface, which alters the flow behavior and diminishes drag. This study plans to examine the effect of different dimple shapes on the aerodynamic characteristics of a flying wing UAV. This paper conducts a comprehensive numerical analysis using Computational Fluid Dynamics (CFD) simulations. The flying wing UAV model is exposed to various dimple arrangements, including round, square, and octagon shapes, put decisively along the wing surface. The CFD simulations utilize the SST k-w turbulence model to capture the flow features accurately. The aerodynamic assessment of each dimple shape is assessed by inspecting essential boundaries like lift coefficient, drag coefficient, and the coefficient of moment for UAV. Preliminary results indicate that dimples significantly affect the aerodynamic behavior of the flying wing UAV. Dimple shape prominently affects drag decrease, stream strength, and, by and large, lift-to-drag ratio. A similar examination gives experiences into the benefits and burdens related to various dimple shapes, aiding the plan streamlining process for flying wing UAVs. The optimized dimple shape recognized through this exploration might upgrade the UAV's endurance, range, and payload limit, making it a resource in applications requiring delayed or broadened flight activities.