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This article proposes an efficient correction model that enables the extension of the blade element momentum method (BEM) for swept blades. Standard BEM algorithms, assuming a straight blade in the rotor plane, cannot account for the changes in the induction system introduced by blade sweep. The proposed extension corrects the axial induction regarding two aspects: the azimuthal displacement of the trailed vorticity system and the induction of the curved bound vortex on itself. The extended algorithm requires little additional processing work and maintains BEM's streamtube independent approach. The proposed correction model is applied to simulations of swept blade geometries based on the IEA 15 MW reference wind turbine. Results show good agreement with lifting line simulations that inherently can account for the swept blade geometry. Blade sweep couples bending and torsion deformations by curving the blade axis in the inplane direction. As such, it can be used to passively alleviate loads and, thus, aeroelastically tailor wind turbine blades. The implementation of aeroelastic tailoring techniques, and the aeroelastic analysis in general, becomes increasingly significant with the size of wind turbine rotors continually rising. Due to its low computing complexity, BEM remains a crucial tool in the aerodynamic and aeroelastic analysis of wind turbine rotors. Thus, the proposed correction model contributes to a fast and accurate evaluation of swept blade designs.

To accurately predict the 1P aerodynamic loads of aviation propellers, this paper established a mathematical model of aviation propeller 1P aerodynamic loads based on the coupling method of blade element theory and momentum theory. Correction methods such as the Prandtl tip correction method and the propeller root correction method were implemented to further improve calculation accuracy. A 1P aerodynamic load calculation procedure was developed based on the mathematical model by using the Matlab software. 1P aerodynamic loads of a three-blade propeller were predicted for three different angles including 3 °, 9 °, and 12°. The numerical calculation results show that the calculated aerodynamic characteristic parameters of individual propeller blades obtained based on the propeller 1P aerodynamic load mathematical model deviate less than 6% from the CFD simulation results, and regular periodic pulsations are observed. The numerical calculations in this paper show that the propeller 1P aerodynamic load calculation procedure developed based on this model can accurately predict the propeller 1P aerodynamic load, which can provide some reference for the study of aviation propeller aerodynamic characteristics.

The 5.0 MW permanent magnet direct-drive wind turbine generator, with a rated rotational speed of 11.64 rpm, features three (3) LM 62 blades. The turbine blades are suitable for an IEC Class II wind turbine generator. The rotor radius measures 63.7 m with a distance of 1.7 m from the hub centre to the rotor shaft Jlange. An aerodynamic analysis of the LM 62 blade was performed to examine the power output and power coefJicient at wind speeds ranging from 3.0 m/s to 25.0 m/s using the Blade Element Momentum Theory suggested by DNV/Risø and derived from GH Bladed. The blade includes Jive airfoils with a design tip speed ratio of 8.65. Axial and tangential induction factors, lift and drag coefJicients, aerodynamic forces, and torque proJiles as normalized rotor blade length functions were calculated and compared with two BEM models. Discrepancies in the induction factors appear in the inboard section of the blade. The results show that the two BEM models are nearly identical when the upstream wind speed exceeds 11.18 m/s. A Student’s t-test compared the power curves predicted by both BEM models with those from the GH Bladed software. The GH Bladed BEM model had a correlation coefJicient of 0.998 and a t-value of 1.4139, which is below the critical t-value when compared to the GH Bladed software output. This indicates that the power curves are statistically similar with over 95% conJidence. The sound power level of the LM62 blade was found to be 103 dB at rated wind speed.

Although the hub blockage effect is generally disregarded for large-sized horizontal axis wind machines, it can significantly affect the performance of small-sized turbines whose ratio between the hub and rotor radii can attain values up to 25–30%. This article proposes a generalisation of the Blade-Element/Momentum Theory (BE/M-T), accounting for the effects of the hub presence on the rotor performance. The new procedure relies on the quantitative evaluation of the radial distribution of the axial velocity induced by the hub all along the blade span. It is assumed that this velocity is scarcely influenced by the magnitude and type of the rotor load, and it is evaluated using a classical CFD approach applied to the bare hub. The validity and accuracy of the modified BE/M-T model are tested by comparing its results with those of a more advanced CFD-actuator-disk (CFD-AD) approach, which naturally and duly takes into account the hub blockage, the rotor presence, an and the wake divergence and rotation, and the results are validated against experimental data. The comparison shows that the correction for the hub blockage effects in the BE/M-T model significantly reduces the differences with the results of the reference method (CFD-AD) both in terms of global (power coefficient) and local (thrust and torque per unit length) quantities.

Coaxial rotor systems are appealing for multirotor drones, as they increase thrust without increasing the vehicle’s footprint. However, the thrust of a coaxial rotor system is reduced compared to having the rotors in line. It is of interest to increase the efficiency of coaxial systems, both to extend mission time and to enable new mission capabilities. While some parameters of a coaxial system have been explored, such as the rotor-to-rotor distance, the influence of rotor pitch is less understood. This work investigates how adjusting the pitch of the lower rotor relative to that of the upper one impacts the overall efficiency of the system. A methodology based on blade element momentum theory is extended to coaxial rotor systems, and in addition blade-resolved simulations using computational fluid dynamics are performed. A coaxial rotor system for a medium-sized drone with a rotor diameter of 71.12 cm is used for the study. Experiments are performed using a thrust stand to validate the methods. The results show that there exists a peak in total rotor efficiency (thrust-to-power ratio), and that the efficiency can be increased by 2% to 5% by increasing the pitch of the lower rotor. The work contributes to furthering our understanding of coaxial rotor systems, and the results can potentially lead to more efficient drones with increased mission time.

The planning and development of windfarms require accurate prediction of the thrust coefficient ( c T ) of wind turbines, which significantly affects the downstream wake. Traditional methods, such as blade element momentum theory (BEMT), often necessitate detailed geometric information of wind turbines for c T computation, information that is not frequently available, especially in the early stages of windfarm planning. This paper aims to address this challenge by presenting a novel and efficient approach to predict c T for horizontal-axis wind turbines (HAWTs). The proposed method integrates classical momentum theory with power curve data to estimate the average axial induction factor ( a ), thereby enabling the calculation of c T without requiring detailed geometric information of HAWTs. The method was validated against thirty-five existing pitch-controlled HAWTs, with R 2 values ranging from 0.9604 to 0.9989. This validation confirms the accuracy of the method, making it a viable alternative to traditional techniques that demand comprehensive wind turbine geometric details. The method has demonstrated both rapidity and precision in c T computation for turbine wake analysis, ensuring high levels of prediction accuracy and potentially lowering the barrier to entry for windfarm development. Unlike existing models predominantly focused on wind turbine power curves, c T modelling has largely been overlooked. This study makes a unique contribution to the field by proposing a novel method for c T prediction, thereby filling a critical gap in windfarm planning and development. However, while the study shows promising results, further research is warranted to explore its applicability in diverse windfarm scenarios and turbine configurations.

The propulsion system of a multi-rotor UAV plays a fundamental role in the aircraft flight characteristics. In fact, it generally represents the major contributor to the aerodynamic forces acting on the vehicle. While several approaches for modeling rotor thrust and drag forces exist, the problem of identifying the parameters for these models is still challenging. In this paper we propose a systematic method for identifying a limited number of parameters which guarantee accurate thrust and drag prediction according to Blade Element Theory (BET). Simple experimental tests employing a popular rotor system and a custom-made quadrotor are used both in the identification phase and for the final validation. The discussion of the results illustrates the accuracy of the method, while highlighting the modeling limit of BET. A refinement using Blade Element Momentum Theory is proposed and validated with the support of experimental data.

With the increasing size of wind turbines, the inflow conditions are also becoming more and more complex, and the rotor speed and blade-pitch angle are unknown under complex inflow conditions, so in order to avoid establishing an equivalent wind speed model, the control system was coupled to the blade element momentum theory (BEMT) to establish an aerodynamic model. In addition, due to the increasing flexibility of blades, a structural model of blades that can solve any section shape and any material properties was established based on the geometrically exact beam theory. Finally, the aerodynamic model and the structural model were coupled to establish the aeroelastic model and implemented by C++. The model was applied to engineering calculations, and the aerodynamic characteristics of wind rotors and the dynamic response of blades under different low-level jets (LLJ) were calculated and analyzed. The results show that when the control system is coupled to the BEMT, part of the power error is transferred to the rotor speed for below-rated wind speeds, and all the power error is transferred to blade-pitch angle for the above-rated wind speeds. The structural model can accurately calculate the static, dynamic displacement and natural frequency of the blades. When the LLJ height is different, the control system weakens the influence of strong shear wind on the average aerodynamic force on the sweeping surface of the wind rotor, but the amplitude of aerodynamic force is still greatly affected by the LLJ height. When the aerodynamic force on the blade is similar, the law of structure dynamic response is the same, which is mainly affected by the natural frequency of the blade. Our work has important reference significance for calculating the aerodynamic characteristics of wind rotors and the dynamic response of blades.

Influence of Mach numbers and telescoping positions (TP) on the aerodynamic-enhancement mechanism of Variable Diameter-and-Speed Tilt-Rotors (VDSTR) was investigated by utilizing Blade Element and Momentum Theory (BEMT), with the original metal-blade tilt-rotors of XV-15 employed as the benchmark. First, by fixing the operational tip Mach numbers while allowing free cooperation of variable diameter and speed, the mechanism was analyzed, and the effects of air compressibility and telescoping position on the mechanism were further scrutinized. Then, advantages over single-variable techniques were highlighted by comparing hover and high-speed forward flight performance. The results highlight distinct aerodynamic improvement mechanisms for VDSTR in different flight states. The reduction of induced power compensates for increased profile drag power, a fundamental mechanism enhancing VDSTR in hover. The mechanism relies on blade contraction in high-speed forward flight, effectively reducing profile drag power. Moreover, compared to the original XV-15 blade, VDSTR enhances forward flight efficiency by 6.93% under specified load and Figure of Merit (FM*) by 4.07% under the designed load, resulting in a power reduction of 51.5 kW and 24.9 kW, respectively, and outperforming single-variable methods. Outward TP movement consistently negatively affects efficiency gain in both states. Optimal TP for promoting aerodynamic-enhancement under both flight states is identified between the root and middle sections of the original blade.

Due to the complexity of aerodynamic coupling between the duct and propeller, the overall design and optimization of ducted fans often require extensive experience and time. Meanwhile, traditional design methods based on Blade Element Momentum Theory, Lifting Surface Theory, Vortex Lattice Methods, and Panel Method usually exhibit certain deviations between their design results and actual outcomes. This is because these approaches struggle to accurately calculate the aerodynamic coupling effects between the duct and propeller, coupled with numerous simplifications inherent in the methods themselves. Considering the strong nonlinear coupling relationship between the duct and propeller, the Response Surface Method (RSM), which enables efficient and accurate analysis of multi-variable coupling effects, was selected for the parameter design and optimization of ducted fans. Computational Fluid Dynamics (CFD) was applied to evaluate the impact of design parameters on overall aerodynamic performance. This approach addresses the limitations of traditional methods, including low design accuracy, high computational cost, and insufficient multi–objective optimization capability. It explicitly models multi-parameter coupling and nonlinear effects using a small number of experimental points, combined with the Multi-Objective Genetic Algorithm (MOGA) to find the global optimum. Compared to the baseline duct fan, the optimized duct fan achieved a 9.6% increase in overall lift and a 9.5% improvement in lift efficiency.