Two-dimensional Airfoil Research Articles

A New Flow Control and Efficiency Enhancement Method for Horizontal Axis Wind Turbines Based on Segmented Prepositive Elliptical Wings

Flow separation occurs when wind turbines operate under large inflow conditions, which seriously affects the utilization of wind energy and reduces the output power of the blade. Therefore, a composite flow control configuration for horizontal axis wind turbines, founded on segmented prepositive elliptical wings, is proposed for efficiency enhancement. Taking a typical NREL Phase VI wind turbine as the prototype, its separation effect is evaluated by the CFD method. Then, starting from the improvement of the two-dimensional airfoil flow, the prepositive elliptic wing is designed according to the airfoil flow, and the optimal two-dimensional flow control configuration of the blade airfoil is obtained by simulation analysis. Finally, the two-dimensional configuration is extended to three-dimensional, and the aerodynamic characteristics of the blade before and after flow control are simulated and compared. The results show that, at wind speeds of 10~20 m/s, flow separation on the blade is effectively inhibited; meanwhile, the pressure difference between the pressure surface and the suction surface increases. These characteristics greatly improve the performance of wind turbine and increase its torque by more than 30%. Moreover, when the flow control effect cannot be reached, the blade torque is only reduced by approximately 2%.

A Shear-Sliding Rigid-Flexible Coupled Skin Variable-Sweep Wing Design and Heat-Fluid-Structure Multifield Coupling Analysis

The variable-sweep wing is very attractive for cross-speed domain aircraft. The shear-sliding rigid-flexible coupled skin variable-sweep wing and its associated mechanism are designed and optimized. The variable-sweep wing has smooth continuous deformation and rigid-flexible coupling features. The calculation model of the sliding skin patch segmentation strategy is established, and the aerodynamic characteristics of the two-dimensional airfoil before and after the deformation of the wing skin are analyzed. According to the deformation characteristics of sliding skin, the configuration of the associated mechanism is determined, and the kinematic characteristics of the reference points of each skin are calculated. The kinematic simulation verifies the force of the mechanism model at the joint of skin surfaces during the deformation process. Considering the aerodynamic heat at supersonic speed, the heat transfer, heat distribution, and structural thermal modes between the flow field and the skin are calculated based on the finite element method. The dynamic characteristics of the swept wing with different flight speeds and different morphologies are analyzed. The natural frequencies are found to be reduced by about 30% to 50% compared to cold models at supersonic speeds. Based on the results of the thermal fluid-solid coupling calculation, the skeleton structure of the swept wing is optimized, and the skeleton structure with 25% mass reduction and better performance is obtained.

Aerodynamic load evaluation of leading edge and trailing edge windward states of large-scale wind turbine blade under parked condition

The safety and reliability of wind turbine blades are increasingly challenged by extreme wind conditions such as typhoons, as wind turbines tend to become larger. Under these conditions, most units will be shut down and the blades will be pitched to around 90° to minimize the loads. This paper aims to compare a new strategy for the parked condition, i.e., the trailing edge windward state, with the traditional leading edge windward state to verify its technical feasibility. The aerodynamic loads of a 30%-thickness airfoil and a commercial wind turbine blade are comprehensively evaluated by wind tunnel experiment, CFD simulation and engineering analytical model. The two-dimensional airfoil cases indicate that the airfoil resultant force is lower in the trailing edge windward state than in the leading edge windward state for a wide range of angles of attack. Consequently, the three-dimensional blade cases shows that the low load region of the trailing edge windward state is relatively wider than that of the leading edge windward state. The averaged blade root load is reduced by 41.4% ~ 57.8% through trailing edge windward state with prescribed error bounds of windward angular. Besides, it is suggested that the traditional engineering analytical model should improve the precision of the extrapolated airfoil data around AOA = 180 deg. to ensure the accurate load evaluation under the trailing edge windward state. This study suggests a new control strategy for wind turbine blades under the parked condition, which offers significant benefits for load reduction and has a good potential for future applications.

Advances in Wall Interference Corrections for Two-Dimensional Lifting Bodies

A novel approach to correcting the effects of wall interference has been developed for low-speed closed-wall wind tunnels using a nonlinear least-squares optimization process independent of the model geometry. Potential flow singularities are used to represent the test object, and the method of images is used to represent the tunnel walls. Trust-region reflective optimization enables the locations and strengths of singularities to be determined iteratively with only wall pressure measurements as independent inputs. Results are obtained from a range of two-dimensional and three-dimensional airfoil test cases using both computational fluid dynamics simulations and wind tunnel experiments, including a NACA 0012 with deployed spoiler, a NACA 0015, a NACA 4415, and a McDonnell Douglas 30P30N high-lift configuration. The nonlinear least-squares wall-correction method is shown to demonstrate a considerable improvement over the conventional two-variable technique.

Global Stability Analysis of Full-Aircraft Transonic Buffet at Flight Reynolds Numbers

Fully three-dimensional (3D) global stability analysis (GSA) is performed on the NASA Common Research Model at turbulent transonic buffet conditions. The framework here proposed is based on a Jacobian-free approach that enables GSA on large 3D grids, making this the first stability study on a full-aircraft at typical flight Reynolds numbers. The Reynolds-averaged Navier–Stokes solutions compare reasonably well with the available experiments and are used as base flows for the stability analyses. GSA is first performed at wind tunnel Reynolds number conditions, and a buffet-cell mode localized in the wing outboard region is found to be responsible for the onset. When the side-of-body (SOB) separation becomes larger at higher angles of attack, two additional modes are detected: a high-frequency mode localized in the SOB region and a low-frequency long-wavelength buffet-cell mode that may represent the link with the shock-oscillation instability found in two-dimensional airfoils. The existence of the buffet-cell mode is confirmed at flight Reynolds numbers. However, due to the presence of large SOB separation at the onset angle of attack, this mode is distributed along the whole wing and an SOB separation mode also appears. As well as characterizing buffet on industry-relevant geometries and flow conditions, this study proves that the proposed GSA framework is feasible for large 3D numerical grids and can represent a useful tool for buffet onset prediction during design and certification phases of commercial aircraft.

Experimental Assessment of the Poststall Performance of Two Highly Cambered Airfoils

Poststall aerodynamic data are required to design and validate propellers, rotors, and wind turbines. However, these data are scarce for (highly) cambered airfoils. This study provides poststall aerodynamic data for the E387 and the FX 63-137 airfoils, and it generates insight into the effect of airfoil camber on poststall aerodynamic behavior. Experimental lift, drag, and moment coefficients are presented for Reynolds numbers between 100,000 and 200,000 at angles of attack from −180 to 180 deg. Prestall performance is validated for the FX 63-137 airfoil, where hysteresis around stall is evident. Comparisons between the two airfoils and published results are made. The FX 63-137 produces a maximum poststall lift coefficient of 1.31 and a drag coefficient at 90 deg of 2.03, whereas the E387 generates values of 1.18 and 1.99, respectively. A geometric relationship is formulated to indicate if an airfoil should have a coefficient of drag larger than a flat plate at 90 deg, and it is found that the FX 63-137 is the only two-dimensional airfoil experimentally tested that conforms to this relationship.

Dynamic responses of a conceptual two-dimensional airfoil in hypersonic flows with random perturbations

This paper investigates a conceptual pitch–plunge airfoil in hypersonic flows with both structural and aerodynamic nonlinearity, meanwhile the effects of irregular fluctuations in the flow and external random loads modeled as a Gaussian white noise are considered. The dynamic responses of the airfoil model especially the bifurcation behaviors are analyzed via the harmonic balance method for the deterministic case. We found the airfoil system undergo both subcritical and supercritical Hopf bifurcations. Subsequently, the effects of stochasticity on the dynamical behaviors of the hypersonic airfoil system are explored in the regimes of subcritical and supercritical Hopf bifurcations depending on the system parameters. Several interesting phenomena are triggered under random perturbations such as intermittency and stochastic transition between the low-amplitude oscillation state and the undesirable high-amplitude oscillation state. These dynamics are further characterized via the probability density function and time history. This work will provide new insights into the safety and reliability design of hypersonic aircraft.

Numerical Simulation of a Two-Dimensional Spatial Unsteady Flow Past Thick Airfoils and Low-Aspect-Ratio Wings with Slot Suction in a Vortex Cell as Applied to Hybrid Aerostatic Aircraft

Numerical Simulation of a Two-Dimensional Spatial Unsteady Flow Past Thick Airfoils and Low-Aspect-Ratio Wings with Slot Suction in a Vortex Cell as Applied to Hybrid Aerostatic Aircraft

Latent Representation of Computational Fluid Dynamics Meshes and Application to Airfoil Aerodynamics

Mesh manipulation is central to computational fluid dynamics. However, creating appropriate computational meshes often involves substantial manual intervention that has to be repeated each time the target shape changes. To address this problem, we propose an autodecoder-based latent representation approach. Human prior knowledge is embedded into learned geometric patterns, which eliminates the need for further handcrafting. Furthermore, the resulting computational meshes are differentiable with respect to the model parameters, which makes it suitable for inclusion in end-to-end trainable pipelines. We apply the model on two-dimensional airfoils to demonstrate its ability to handle various tasks.

Numerical Study of Aerodynamic Performance of Airfoil with Variable Curvature Split Flap

To further improve the lift-rising effect of the attached flap on an airfoil, based on the unique movement pattern of a fluke when a dolphin moves forward, this paper puts forward a novel attached split flap model with variable curvature. The lift-type vertical axis wind turbine's typical blade airfoil NACA 0018 is taken as the research object. First, the aerodynamic performance of the two-dimensional airfoil is simulated based on the SST k-ω turbulence model. The contrast between the simulation and the experimental results proves the correctness of the numerical simulation methods in this paper. Then, the effectiveness of split flap is verified, and the lift-rising principle is briefly analyzed. Finally, the parametric study is carried out based on the flap model with variable curvature proposed in this paper, and the lift-rising principle of the variable curvature split flap is analyzed in detail. The results indicate that, with the rise of the flap's curvature index, the airfoil's lift coefficient (Cl) integrated with the flap gradually increases accordingly and tends to a constant value. The bionic research in this paper can provide a comprehensive reference for the aerodynamic shape design of airfoil trailing edge flap and the further optimization of energy efficiency of rotating machinery or aviation.

Experimental Analysis of Transonic Buffet Conditions on a Two-Dimensional Supercritical Airfoil

The present experimental investigation characterizes the development and decay of transonic buffet on the supercritical airfoil OAT15A, as well as the flow field and shock motion throughout the fully developed buffet cycle. A comprehensive database of high-speed focusing schlieren sequences provides access to the temporal and spectral behavior of the oscillatory shock motion within a broad parameter space, covering Mach numbers 0.68–0.80 and angles of attack 3.3–6.5 deg. From these data, multiple temporal and spectral properties characterizing the distinctness of the shock oscillation are extracted. Combining these indicators enables us to clearly distinguish fully established buffet from pre-buffet, buffet onset, and buffet offset. This criterion helps to interpret the diverse findings in the relevant literature cases. Particle-image velocimetry measurements provide detailed insight into the turbulence structure and behavior throughout a fully established buffet cycle at a Mach number of 0.72 and an angle of attack of 5 deg. Instantaneous and phase-averaged velocity maps indicate massive flow separation for shock positions close to the upstream limit. Velocity profiles illustrate the large intermittent velocity deficit persisting until the trailing edge and corroborate most pronounced separation when induced by an upstream-traveling shock wave. Representative phases of the buffet cycle visualize and quantify the severe modification of the flow topology modulated by the shock and lay the groundwork to improve the understanding of mechanisms governing shock buffet.

TransCFD: A transformer-based decoder for flow field prediction

The computational fluid dynamics (CFD) method is computationally intensive and costly, and evaluating aerodynamic performance through CFD is time-consuming and labor-intensive. For the design and optimization of aerodynamic shapes, it is essential to obtain aerodynamic performance efficiently and accurately. This paper proposed TransCFD, a Transformer-based decoding architecture for flow field prediction. The aerodynamic shape is parameterized and used as input to the decoder, which learns an end-to-end mapping between the shape and the flow fields. Compared with the CFD method, the TransCFD was evaluated to have a mean absolute error (MAE) of less than 1%, increase the speed by three orders of magnitude, and perform very well in generalization capability. The method simplifies the input requirements compared to most existing methods. Although the object of this work is a two-dimensional airfoil, the setup of this scheme is very general. TransCFD is promising for rapid aerodynamic performance evaluation, with potential applications in accelerating the aerodynamic design.

HLPW-4/GMGW-3: High-Order Discretization Technology Focus Group Workshop Summary

This paper summarizes the High-Order Technical Focus Group (HO-TFG) submissions for the joint 4th AIAA High Lift Prediction (HLPW-4) and 3rd Geometry and Mesh Generation Workshop (GMGW-3). The goal of the workshop was to assess the state-of-the-art in mesh generation and computational fluid dynamics software. The Common Research Model High-Lift (CRM-HL) variant served as the primary focus of the workshop, and a two-dimensional airfoil section from the CRM-HL was used as a verification test case. The HO-TFG was tasked with generating high-order curved meshes for both geometries, and computing high-order solutions using both Reynolds-averaged Navier–Stokes and scale-resolving formulations. While limited by computational resources, the final results demonstrate the potential of higher-order methods to increase solution accuracy with a lower degree-of-freedom count relative to second-order discretizations.

Transfer learning from two-dimensional supercritical airfoils to three-dimensional transonic swept wings

Machine learning has been widely utilized in flow field modeling and aerodynamic optimization. However, most applications are limited to two-dimensional problems. The dimensionality and the cost per simulation of three-dimensional problems are so high that it is often too expensive to prepare sufficient samples. Therefore, transfer learning has become a promising approach to reuse well-trained two-dimensional models and greatly reduce the need for samples for three-dimensional problems. This paper proposes to reuse the baseline models trained on supercritical airfoils to predict finite-span swept supercritical wings, where the simple swept theory is embedded to improve the prediction accuracy. Two baseline models are investigated: one is commonly referred to as the forward problem of predicting the pressure coefficient distribution based on the geometry, and the other is the inverse problem that predicts the geometry based on the pressure coefficient distribution. Two transfer learning strategies are compared for both baseline models. The transferred models are then tested on complete wings. The results show that transfer learning requires only approximately 500 wing samples to achieve good prediction accuracy on different wing planforms and different free stream conditions. Compared to the two baseline models, the transferred models reduce the prediction error by 60% and 80%, respectively.

Numerical Simulations of the Adverse Effects of Rain on Airfoil And Rotor Aerodynamic Characteristics

There is a significant interest in improving the performance of rotors under adverse operating conditions. However, there is a very limited understanding of the performance implications on two-dimensional (2D) airfoils and rotor blades under adverse effects of rainfall. Furthermore, the fundamental physical phenomena causing the loss in performance are not clearly understood. In this study, low-fidelity models are first developed to rapidly estimate the water layer formation on 2D airfoils and assess the resulting impact on lift and drag characteristics. The low-fidelity simulations are also useful to obtain quick estimates of water layer thickness as a function of liquid water content and droplet diameter. Subsequently, computational fluid dynamics studies for 2D airfoils and a small-scale rotor in hover are done to obtain more accurate estimates of the effects of rain on airfoil performance and match test data where available. Higher fidelity parametric studies for various airfoils were conducted by varying angles of attack, the liquid water content in the rain droplets, and the droplet diameters to capture trends in performance degradation. The resulting trends match the trends from the test data reasonably well. The higher fidelity airfoil loads are subsequently used within a classical combined blade element-momentum model to assess the loss of performance attributable to rain for a small-scale rotor. The present studies indicate a significant loss in thrust production, a rise in the power requirement, and a reduction in the figure of merit for small-scale rotors caused by rain.

Graph neural networks for the prediction of aircraft surface pressure distributions

Aircraft design requires a multitude of aerodynamic data and providing this solely based on high-quality methods such as computational fluid dynamics is prohibitive from a cost and time point of view. Deep learning methods have been proposed as surrogate models to predict aerodynamic quantities, showing great potential at significantly reduced cost. However, most approaches rely on a structured grid or are tested only for two-dimensional airfoil cases with a few thousand nodes. During aircraft programs, unstructured grids with millions of nodes are routinely used to model industrial-relevant complex physical systems. Hence, further investigation is required to study the applicability and extension of deep learning methods to industrial cases. In this paper, we use a graph neural network approach applicable to unstructured grids and extend it for the task of predicting surface pressure distributions for complex cases involving several hundreds of thousand of nodes. We compare this approach with proper orthogonal decomposition combined with an interpolation technique and with two other deep learning approaches, namely, a coordinate-based multilayer perceptron for pointwise predictions and its extension using surface normals as additional inputs. Results are first presented for a two-dimensional airfoil case and then for the NASA Common Research Model transport aircraft with an underlying mesh consisting of around 500,000 surface points. The deep learning methods demonstrate in transonic flows the ability to capture shock location and strength more accurately. Furthermore, the proposed graph-based approach with the addition of more geometric information such as connectivity and surface normals seems to provide an additional boost in performance over the coordinate-based multilayer perceptron yielding more realistic pressure distributions.

Multifidelity Prediction Framework with Convolutional Neural Networks Using High-Dimensional Data

This paper proposes two novel multifidelity neural network architectures developed for high-dimensional inputs such as computational flowfields. We employed a two-dimensional flow-varying transonic supercritical airfoil problem while exploring and comparing our methods with the former “multifidelity deep neural networks” from the literature. We call these novel methods “modified multifidelity deep neural networks” and “multifidelity convolutional neural networks.” The main objective of this study is to establish an advanced multifidelity prediction framework that can be applied to any computational data; however, here, we applied our methods to the prediction of aerodynamic coefficients using pressure coefficient fields around the airfoil. To generate the dataset, first, a coarse grid is employed using the SU2 Euler solver for low-fidelity data; then, a relatively finer grid is used to obtain the viscous solutions by using the Spalart–Allmaras turbulence model for the high-fidelity data. The performance metrics to compare the methods are determined as the test accuracy, the physical training time, and the size of the high-fidelity samples. The results demonstrate that the proposed multifidelity neural network architectures outperform the multifidelity deep neural networks in predictive modeling using high-dimensional inputs by improving the multifidelity prediction accuracy significantly.

Numerical analysis of shock characteristics control based on bump

The effects of bump control on shock aerodynamic characteristics have been investigated by simulations. A bump control that based on the changes of local upper surface of two-dimensional (2D) airfoil or three-dimensional (3D) wing model has been applied to affect the shock intensity and position. The simulation results are close of other experiment when the calculate parameters are same with each other. The simulations show that the drag and lift characteristics can be improved with the bump control, and the results of improvement strongly depend on control parameters. For the 2D RAE2822 airfoil, the optimal control position of the bump control must keep close to the position of the shock wave. The 3D local bump that located on 80% wing span wise and closed to the tip can acquire a batter control results for the 3D RAE2822 wing model.

Numerical study on the water entry of two-dimensional airfoils by BEM

Hydrodynamics of the traditional wedges, cylinders, and cones entering water have been heavily studied. However, the hydrodynamic characteristics of airfoils are practically unknown; the problem is inspired by the recently widely developed fixed-wing unmanned aerial-underwater vehicle, which can fly in the air, cruise in water and frequently enters and exits free water surface. In this study, the hydrodynamic characteristics and fully nonlinear free surface deformation for the water entry of airfoils have been investigated by the time domain boundary element method. First, convergence study based on the NACA0012 airfoil is considered. The time step and element size are adjusted, and the results show that the free surface elevation and pressure distribution agree well with those obtained through Reynolds-averaged Navier–Stokes equations. The results show that the higher the entry velocity, the greater the peak hydrodynamic force. Furthermore, the higher thickness ratio causes greater added mass. Gravity and velocity are found to significantly influence the hydrodynamic behavior, including the time-varying force, while thickness ratio has a great impact on added mass and pressure.

Fast transonic flow prediction enables efficient aerodynamic design

A deep learning framework is proposed for real-time transonic flow prediction. To capture the complex shock discontinuity of transonic flow, we introduce the residual network ResNet and deconvolutional neural networks to learn the nonlinear discontinuity phenomenon in transonic flow, which is affected by the Mach number, angle of attack, Reynolds number, and aerodynamic shape. In our framework, flow field variables on actual grid points are utilized in the neural network training to avoid the interpolation operation and the input of spatial position with a point cloud that is required with traditional convolutional neural networks. To investigate and validate the proposed framework, transonic flows around two-dimensional airfoils and three-dimensional wings are utilized to verify its effectiveness and prediction accuracy. The results prove that the model is able to efficiently learn the transonic flow field under the influence of the Mach number, angle of attack, Reynolds number, and aerodynamic shape. Significantly, some essential physical features, such as shock strength and location, flow separation, and the boundary layer, are accurately captured by this model. Furthermore, it is shown that our framework is able to make accurate predictions of the pressure distribution and aerodynamic coefficients. Thus, the present work provides an efficient and robust surrogate model for computational fluid dynamics simulation that enhances the efficiency of complex aerodynamic shape design optimization tasks and represents a step toward the realization of the digital twin concept.