the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterization of Dynamic Stall on Large Wind Turbines
Abstract. This study shows an extensive analysis of dynamic stall on wind turbine airfoils preparing the development of a reduced-order model applicable to thick airfoils (t / c > 0.21) in the future. Utilizing URANS simulations of a pitching FFA-W3-211 airfoil at the Reynolds number of 15 million, our analysis identifies the distinct phases in the course of the evolution of dynamic stall. When the dynamic stall is conventionally categorized into the primary instability transitioning to the vortex formation stage, we suggest two sub-categories in the first phase, and an intermediate stage featuring a plateau in lift prior to entering the full stall region. This delays the inception of deep stall, approximately 3° for a simulation case. This is not predictable with existing dynamic stall models, optimized for low Reynolds number applications. These features are attributed to the enhanced flow attachment near the leading-edge, restricting the stall region downstream of the position of maximum thickness. The analysis on the frequency spectra of unsteady pressure confirms the distinct characteristics of the leading-edge vortex street and its interaction with large-scale mid-chord vortices to form the dynamic stall vortices (DSVs). Examination of the leading-edge suction parameter (LESP) proposed by Ramesh et al. (2014) for thin airfoils under low Reynolds numbers reveals that LESP is a valid criterion in predicting the onset of the static stall for thick airfoils under high Reynolds numbers. Based on the localized separation behavior during a dynamic stall cycle, we suggest a mid-chord suction parameter (MCSP) and trailing-edge suction parameter (TESP) as supplementary criteria for the identification of each stage. The MCSP exhibits a breakdown in magnitude at the onset of the dynamic stall formation stage and full stall, while TESP supports indicating the emergence of a deep stall by detecting the trailing-edge vortex.
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Status: open (until 09 May 2024)
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RC1: 'Comment on wes-2024-31', Anonymous Referee #1, 01 May 2024
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This paper presents URANS simulations for a pitching wind turbine profile at high Reynold numbers (>10^6). This paper describes the dynamic stall onset and then proposes a method to better predict the dynamic stall for Blade Element Momentum models. The paper is globally well written, even if some explanations are a bit hard to follow probably because the figures do not fully help the explanations. The study of the dynamic stall onset is not new, as the authors mentioned in the introduction, and the novelty of this paper could be that they study dynamic stall on wind turbine airfoils and attempt to develop a simple model to predict the dynamic stall onset.
I would have a couple of major concerns, that make me wonder if the author's explanations are solid enough to be reproduced and published:
A. With the amount of information given in this paper, I do not think I would be able to define the specific angles (αss, α*, α** and αtds) on another wind turbine profile. For example the static stall is not clear on a thick airfoil. How do the author define a static stall here? Is it a complete stall of the airfoil? For example Braud et al (Study of the wall pressure variations on the stall inception of a thick cambered profile at high Reynolds number, Physical Review Fluids, 2024) have shown in their recent paper that they did not find a complete stall of the airfoil on a wind turbine profile below 25°. (They also highlighted the importance of 3D effects at high Reynolds numbers).
The definition of α* as defined by Mulleners and Raffel (The onset of dynamic stall revisited, Exp Fluids, 2012), are based on POD modes on the vorticity field. It seems that here all these angles lack clear definitions.
B. Similarly, I would not be able to compute the Middle Chord Suction Parameter (MCSP) or (TESP) Trailing Edge Suction Parameter on another wind turbine profile. Whereas the Leading-Edge Suction Parameter (LESP) defined by Ramesh has a physical definition (it is based on the first Fourier term in thin-airfoil theory), I do not see a physical sense to the new MCSP and TESP. I did not understand how they were calculated. I do not think they can be defined in a similar way to the LESP using the inviscid flow theory.
C. The outcomes of this paper are intended for wind turbines. But I am not sure that the cases studied here are relevant to wind turbines. The applied turbulence intensity is 0.01%, while in general it is at least 8-10%. What would be the operating angle of attack on such a profile, and what would the expected variations in angle of attack be? For example the sinusoidal motion 20°+-15° does not seem realistic to me. Some contextualisation may help to appreciate the importance of dynamic stall on a wind turbine blade section.I have other minor comments:
1. end of page 6: "the conclusions regarding the formation of dynamic stall on future large WTs remain the same". I am not sure to what the authors refer to when they write "the same".
2. page 5: LE, TE, and CFL (and BLM and k in page 6) are used but were not introduced before. I do not know what CFL means.
3. section 2.2 seems more a section for the introduction. The beginning of section 5 may be more appropriate in this section "2. Methodology".
4. Section 2.4: This section might be better used as a nomenclature (if the WES template allows it).
5. Figure 3: It is hard to compare the different plots in figure 3. It may be easier to compare them if they are on the same plot (and probably with the time as x-axis). The phase-average value would probably suffice here to compare the general evolution of the numbers of cell or maximum CFL.
6. Why is the pitching case different for the mesh and time-step studies? (17°+-8° for the mesh study and 17°+-15° for the time-step study). The same pitching case for both studies would probably ease the comparison.
7. Figure 4. What do the arrows mean in figure 4?
8. page 10. What do the author mean with the term "open flow separation"?
9. Figure 6: The angle of attack as x-axis (place on the top of the plot for example) would help to visualise the time and the angle of attack at the same time.
10. Figure 6: Please indicate tss, t*, t** and tds in the x-axis of figure 6 and not just in the legend. It is harder to follow without these specific times in the graph.
11. Figure 6: the colorbar probably represents the pressure coefficient. Could you please mention it on top of the colorbar?
12. Figure 6: The colormap used is divergent, with a white color in the middle which "separates" the blue and red color. But the white value has no signifiant value here. A convergent colormap might be more appropriate here to better visualise the transitions in the pressure coefficients.
13. Figure 6: A Cp of -14 seems a lot to me. I cannot recall such a high absolute value even in simulations. Could the author confirm this extremum please?
14. Figure 7: The instantaneous pressure contours are probably not the best to visualise the vortices described in the text. The z-vorticity contours or the Q-criterion might be more appropriate.
15. Figure 7: Could the author add a colorbar here for the pressure value. It seems to be a different scale to the colorbar shown in figure 6, which uses the same colormap.
16. Figure 7: For each subcaption, it would be good to add the angle of attack and time, when these snapshot were taken, and if they correspond to a salient time such as tss, t*, t** or tds.
17. Page 13: What do the authors consider to be a thin profile and low Reynolds numbers? For example in a sinusoidal pitching airfoil cited in this paper (Deparday and Mulleners, PoF, 2019) or Deparday et al, JFM, 2022 (Experimental quantification of unsteady leading-edge flow separation), it seems there is a similar plateau of Cl but the airfoil is thinner and the Reynolds number lower, which would contradict the conclusions here.
18. Figure 8: I have the same comments about the divergent colormap, and no mention about what the colorbar represents.
19. Figure 8: It seems there is a periodic pattern with the Strouhal number. Could the author confirm this is not an artifact due to the time step of the simulations?
20. I do not understand why BEM is applied here. Did the authors model a rotating wind turbine blade? What is the geometry of the blade then, the rotational speed?
21. I would like to mention to the authors a new model for dynamic stall recently published (Bangga et al, Development and Validation of the IAG Dynamic Stall Model in State-Space Representation for Wind Turbine Airfoils, 2023, https://doi.org/10.3390/en16103994)Citation: https://doi.org/10.5194/wes-2024-31-RC1
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