Investigating wake reproduction of a model-scale wind turbine: Experimental measurements versus Large Eddy Simulation with actuator line.

General comments:

The authors present a LES framework (Nek5000) for a model-scale wind turbine in an atmospheric boundary-layer wind tunnel, with two main methodological components: (i) a recycling–inflow strategy augmented by a controller-based volume forcing, and (ii) an extended actuator line method (ALM) that represents blades, tower, and nacelle. The manuscript is well written, and the documentation of the experimental setup, LES validation, and uncertainty assessment is valuable for reproducibility. The authors also provide quantitative validation of wake profiles at two downstream locations. Overall, the work is technically competent and scientifically sound. However, several central claims require stronger supporting evidence before the work can be recommended for publication.

Specific comments

1. The manuscript attributes improved near-wake gradients and enhanced tip-vortex representation to specific implementation choices, including local force evaluation at every grid point, avoiding radial smoothing, and disabling the optional tip-spreading correction. These decisions are physically defensible, but the current presentation does not provide a baseline comparison that isolates their incremental contribution. To substantiate the novelty and quantify the benefit, the paper should include a controlled ablation study (e.g., standard ALM versus the proposed extended ALM), reporting the impact on clearly defined wake metrics (velocity deficit, shear gradients, turbulence intensity, and spectra). Without such comparisons, the improvements remain qualitative and cannot be unambiguously attributed to the proposed modifications.
2. The nacelle drag coefficient is explicitly adjusted empirically until the wake appears to match observations. This compromises the independence of validation, especially for near-wake structure where nacelle effects are non-negligible. Please discuss a sensitivity study showing impact of nacelle Cd on wake metrics.
3. The controller-based forcing reduces TI MAPE below 0.75 m and argues that imposed perturbations have dissipated by the recycling plane. Matching TI does not guarantee matching spectra, integral length scales, anisotropy, or coherence, all of which affect wake recovery/meandering. Since downstream errors increase, we cannot determine whether residual discrepancies are dominated by inflow-structure mismatch or turbine forcing/model assumptions. Please address this point thoroughly, with clear justification and supporting evidence.
4. The manuscript compares +1° and −3° pitch cases and notes different agreements near tip vs root. If the nacelle Cd is tuned and the root region is known to be problematic for ALM, then pitch-induced differences may be difficult to isolate. Please quantify the pitch sensitivity to demonstrate the extent to which the reported error is dominated by a region where the model assumptions are known to be invalid.
5. Blade deformation mismatch should be connected to wake interpretation more directly. Since deformation affects angle of attack and thus loads, the wake validation may be partially right for the wrong reasons. Please elaborate further on this point.

Technical corrections

• Replace “looses its coherence” with “loses its coherence.”
• Figure annotations contain spelling errors: “Settling chanmber” → “Settling chamber”; “Font turntable” → “Front turntable”; “Substract” → “Subtract.”
• Correct “balde mean deformation” → “blade mean deformation.”
• Standardize unit formatting throughout (e.g., “ms−1” vs “m s−1”) and ensure consistent usage of D (rotor diameter) vs “ø” notation in figure labels/captions.

The manuscripts presents a combined experimental and numerical approach to the description of a wind turbine wake. In particular, experiments performed with ta turbulent boundary layer are used to validate an actuator line model of the same turbine. The results are promising in terms of overall agreement between the two approaches. The use of a high-order spectral method to solve the N-S equations coupled with an actuator line model is an interesting prospect. However, the manuscript lacks crucial details that significantly hamper it’s long term impact. Some comments below:

1. The main concern is the scarce amount of details provided regarding the numerical setup and the corresponding lack of any independence study. This is a crucial aspect as a CFD code that uses high-order spectral decomposition rather than “traditional” finite difference is used. “standard” best practices for actuator line models require 80-120 spanwise elements per blade. The kernel size is typically refined based on how many elements are used, with finer grids allowing for smaller and more realistic projection kernels. This ammount of discretizaion may still not be enough to correctly resolve the tip vortices (see: https://doi.org/10.1016/j.compfluid.2024.106477). Based on the information provided in section 3.1 a lot less elements were used to discretize the rotor area. While not directly comparable, authors performing ALM LES on scaled models using finite difference used orders of magnitude more cells (https://iopscience.iop.org/article/10.1088/1742-6596/2767/5/052050, https://doi.org/10.5194/wes-10-1707-2025). Especially because this is, in my understanding, the first time this ALM setup is presented, the quality of the results is hard to judge without grid independence and a comparison to the established literature, even if a different method to solve the N-S equations is used.
2. A second major issue is the lack of a comparison between experiment and simulations in total thrust or power. Similar wake characteristics can arise because of different levels of power extraction.
3. The scope of the manuscript does not appear to be crystal clear. If the focus is on validation why does the pitch angle in simulations not match the one in experiments? On the other hand if the scope is to study the influence of pitch angle, the gap that the manuscript is trying to fill should be better motivated. Moreover, experiments with a full rotor model and ABL are not easy to come across. This could be a major selling point for the study if better explained.
4. No details regarding how the airfoil coefficients used in the numerical model are derived are provided beyond Figure 17. Crucial details are missing such as the Reynolds number and the Ncrit that was used in XFoil. The NCrit value influences where transition occurs, which in turn can influence the airfoils performance significantly at low Reynolds numbers. I would expect the Ncrit value to be tuned according to the TI level in the wind tunnel
5. Where any steps taken to control the surface finish of the blade? This can influence BL transition and 3D printing usually generates quite rough surfaces.
6. No details are provided regarding the turbulence model
7. How long do the simulations run? What is the timestep? Statistical convergence must be accounted for in scale-resolving simulations
8. The ALM description also lacks crucial information. For instance, what strategy was used to sample the velocity in the flowfield? How many actuator points are used? What is the actual width of the kernel compared to the grid (eq. 10).
9. Are all experiments performed with 0° of blade pitch? Why compare to +1° and -3° in numerical simulations? Moreover, there seems to be higher thrust force extraction at the rotor edges, which may suggest inaccuracies in the tip-loss modelling.
10. Figure 23: Are the forces time-averaged? Why is a certain instant considered over another? Moreover, profiles are much smoother at the tip, what is this caused by? We are also not seeing the classical decline in axial forces close to the tip. This could be due to inaccuracies in tip effect modelling, or due to the large chord near the blade tip in the model, which does not feature taper as typical blades would.