## 1 Introduction
[18] provided a statistical representation of dynamic stall occurrence on a downwind HAWT, after analyzing the surface pressure data from the National Renewable Energy Laboratory (NREL). They developed two hypotheses to explain the discrepancy at 30% span and estimated the frequency of dynamic stall on upwind wind turbines. [PERSON] et al. [19] conducted a series of steady state and unsteady wind tunnel tests for the S809 airfoil. [PERSON] and [PERSON] [20] addressed some challenging numerical aspects of dynamic stall, such as the prediction of flow reattachment and three-dimensional (3D) effects. [PERSON] et al. [21] developed a model for aerodynamic lift of wind turbine profiles, based on a backbone curve, in the form of the static lift, as a function of the angle of attack. It combines memory delay effects under attached flow with reduced lift, due to flow separation under dynamic stall conditions. A new prediction technology for dynamic stall, based on the Leishman-Beddoes model, was given by [PERSON] et al. [22]. In a recent experiment by [PERSON] and [PERSON] [23], they observed the formation and complex evolution of the leading-edge vortex and modified the classical dynamic-stall conceptual model, which is specifically related to the dynamics of the leading-edge vortex. [PERSON] et al. [24] improved the Beddoes-Leishman (B-L) model to account for the characteristics of wind turbine airfoils which have a larger thickness-to-chord ratio compared to aviation airfoils and operate at lower Mach numbers. A series of validations on S809 airfoil are performed to illustrate its advantage. [PERSON] et al. [25; 26] recommended that the transition model is necessary for accurately predicting dynamic stall at the lower Reynolds number of 10\({}^{5}\). Both 2D and 3D calculations were carried out, and the results with the SST \(k\)-\(\omega\) model were closer to the experimental data during the up stroke. The 2D RANS simulation is more excellent in capturing significant parts of the coherent large dynamics. [PERSON] et al. [27] adopted the DDES SST \(k\)-\(\omega\) model, which is combined with the laminar/turbulent transition modeled (the \(\gamma\)-Re\({}_{\theta}\) model), to present the combined effects of dynamic stall and rotational augmentation in the inboard parts of wind turbine blades. A further investigation was implemented by [PERSON] et al. [28]; they employed the transition SST model and found that these combined effects can dramatically reduce the sectional lift, drag hysteresis by almost 60% and 80%, and delay the onset of stall, compared to either the rotational augmentation and dynamic stall. [PERSON] et al. [29; 30] employed the plasma flow to optimize the performance of airfoil dynamic stall in the experiment and numerical calculation, respectively. The large eddy simulation (LES) was well applied in their research. Their results both showed that the strength of the dynamic separation vortex decreases and average aerodynamic force increases under the plasma flow loading. [PERSON] et al. [31; 32] investigated the action of vortex generators under dynamic stall and concluded that the transition SST \(k\)-\(\omega\) model is more suitable for the simulation of dynamic stall, and the vortex generators can elevate the maximum lift coefficient by almost 40%. They also presented comparative analysis of dynamic stall among the 2D airfoil, 3D non-rotating blade, and 3D rotating blade undergoing sinusoidal pitch oscillations. The flow mechanism of three-dimensional dynamic stall is further revealed. In summary, the transition SST \(k\)-\(\omega\) model is crucial to accurately predict the dynamic stall in a highly efficient simulation. As shown above, the research of dynamic stall on aircrafts and wind turbines in a clean air flow is without interruption since it was discovered. However, the associated exploration in a gas-solid flow is seriously lacking because of the small effect on the aerodynamic performance of an aircraft.