The increased velocity (Invelox) wind turbine system is a novel wind energy collection device. This system can collect and accelerate the air flow through a funnel and a Venturi tube. However, the efficiency of this system is relatively low under some wind directions. To improve the aerodynamic performance of Invelox, a straight-through layout with a windshield was proposed. The flow field of the improved design was studied by applying Computational Fluid Dynamics (CFD) and was compared with that in the original configuration. Numerical results show that when the Invelox exit is facing the incoming wind, the ratio of the average velocity inside the Venturi tube to the incoming wind speed, i.e., the speed ratio, will drop sharply, and even the airflow will push back. The improved layout can eliminate the sensitivity of incoming wind direction to aerodynamic characteristics. The windshield can effectively reduce the interference of incoming air to the outlet air, making the speed ratio increase by about 42%. Different wind profiles in the atmospheric boundary layer are used in the boundary of the flow domain as the incoming flow wind. With the increase in the wind profile index, the speed ratio of the Invelox system will gradually decrease.

With the rapid development of data-driven methods in recent years, deep neural networks have attracted significant attention for aerodynamic predictions and design optimizations. Among these methods, the multi-fidelity deep neural network (MFDNN), which can combine high-fidelity (HF) and low-fidelity (LF) data, has gained popularity. This paper systematically investigates the performances of employing MFDNN models in predicting aerodynamic coefficients and in performing aerodynamic shape optimizations (ASOs), especially the impact of using various HF/LF data ratios for training models. The results of the prediction accuracy of the aerodynamic coefficients of airfoils show that the less HF data used, the more advantages can be achieved by the MFDNN models than the single-fidelity models. The well-trained MFDNN models are then employed in an ASO problem of airfoil in the subsonic regime, and it is found that a higher HF/LF data ratio does not definitely result in a better performance in the ASO. As the insufficiency in the prediction accuracy of the optimal shapes appears when employing the non-updated MFDNN models, an update strategy is developed by tightly integrating the MFDNN models with the particle swarm optimization algorithm. To further reduce the time costs for updating models, a dual-threshold update strategy is then introduced, which can half the counts of evaluating HF data.

In this paper, the Navier-Stokes equations coupled with a Lagrangian discrete phase model are described to simulate the air-particle flows over the S809 airfoil of the Phase VI blade, the NH6MW25 airfoil of a 6 MW wind turbine blade and the NACA0012 airfoil. The simulation results demonstrate that, in an attached flow, the slight performance degradation is caused by the boundary layer momentum loss. After flow separation, the performance degradation becomes significant and is dominated by a more extensive separation due to particles, since the aerodynamic coefficient increments and the moving distance of separation point present similar variation trends with increasing angle of attack. Unlike the NACA0012 airfoil, a most particle-sensitive angle of attack is found in the light stall region for a wind turbine airfoil, at which the lift decrement and the drag increment reach their peak values. For the S809 airfoil, the most sensitive angle of attack is about 3° higher than that for the maximum lift-to-drag ratio. Hence, the aerodynamic performance of a wind turbine is very susceptible to particles. Based on the most sensitive angles of attack, the more sensitive scope of angles of attack of a blade airfoil and the more sensitive range of rotor tip speed ratios are predicted sequentially. The present study clarifies the principles for the performance degradation of a wind turbine airfoil due to particles and the conclusions are useful for the wind turbine design reducing the particle influences.

A Double-Passage Shape Correction Method for Predictions of Unsteady Flow and Aeroelasticity in Turbomachinery - Volume 9 Issue 4 - Tongqing Guo, Di Zhou, Zhiliang Lu

A practical vertical takeoff and acceleration strategy is developed for manned electric vertical takeoff and landing vehicles, with a simple vehicle operation principle defined. Firstly, a 6-DOF model is established for 120 kg reduced-scale protype electric vertical takeoff and landing vehicles, with its physical control principles illustrated. Then, a simple vehicle operation method is defined for the vehicle, where the conventional operation method for fixed-wings and helicopters is considered for a friendly stick response definition for pilots with different backgrounds. The defined simple vehicle operation principles are realized by a control architecture with a linear-active-disturbance-rejection-control-based inner loop stability augmentation system and an airspeed-based mode selection outer loop. This system is then used to perform a four-stage vertical takeoff and acceleration strategy, which targets at a smooth and safe transition. The Monte Carlo simulation results and the strategy simulations prove that the proposed strategy, which achieves the design target perfectly, can be easily performed with the developed simple vehicle operation system, and that it has sufficient robustness performance to reject at least 20% of the model’s uncertainties.

One major problem in the development of hypersonic vehicles is severe aerodynamic heating; thus, the implementation of a thermal protection system is required. A numerical investigation on the reduction of aerodynamic heating using different thermal protection systems is conducted using a novel gas-kinetic BGK scheme. This method adopts a different solution strategy from the conventional computational fluid dynamics technique, and has shown a lot of benefits in the simulation of hypersonic flows. To be specific, it is established based on solving the Boltzmann equation, and the obtained gas distribution function is used to reconstruct the macroscopic solution of the flow field. Within the finite volume framework, the present BGK scheme is specially designed for the evaluation of numerical fluxes across the cell interface. Two typical thermal protection systems are investigated by using spikes and opposing jets, separately. Both their effectiveness and mechanisms to protect the body surface from heating are analyzed. The predicted distributions of pressure and heat flux, and the unique flow characteristics brought by spikes of different shapes or opposing jets of different total pressure ratios all verify the reliability and accuracy of the BGK scheme in the thermal protection system analysis.