CFD-Based Performance Analysis of Modified Archimedes Wind Turbine Blades

Abstract

This study evaluates the aerodynamic performance of a modified Archimedes Spiral Wind Turbine (ASWT) using Computational Fluid Dynamics (CFD). A baseline model was compared with different designs, including surface dimples and a trailing-edge flap. Simulations were carried out in SolidWorks Flow Simulation 2025 under a constant inlet velocity of 12 m/s and rotational speeds ranging from 50 to 500 RPM. The performance of the modified ASWTs was evaluated using key parameters, including the power coefficient ($C_p$), torque, and tip speed ratio ($TSR$). The obtained results follow the expected $C_p-TSR$ behavior, with a peak of $C_p=0.24277$ for the smooth blades and $C_p=0.2565$ for the blades with the flap at $TSR=1.63625$. While the addition of dimples along the surface of the blades resulted in reduced $C_p$ values, the trailing-edge flap consistently improved performance, yielding increased $C_p$ values in comparison to the baseline configuration. Overall, the flap modification highlighted higher aerodynamic efficiency, recognizing it as the most successful improvement among all the tested configurations. These findings shed light on the relevance of geometry-specific optimization in improving ASWT productivity for small-scale wind energy applications.

1. Introduction

The shift to sustainable and renewable energy systems has accelerated due to the growing worldwide demand for energy as well as the negative environmental effects of reliance on fossil fuels [1,2,3,4]. Because of its widespread availability, technological maturity and small environmental impact, wind energy has emerged as one of the most economically viable and scalable alternatives. The ongoing growth of wind-generating capacity around the world highlights how important it is for lowering greenhouse gas emissions and promoting long-term energy sustainability plans [5]. To increase energy conversion efficiency and guarantee dependable performance under a variety of operating conditions, substantial research efforts have been directed toward developing wind turbine technology [6,7].

Horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs) are the two main types of wind turbines, with each having unique aerodynamic traits and operating benefits. Large-scale energy generation is dominated by HAWTs because of their high efficiency in stable wind conditions, but VAWTs have drawn more interest because of their capacity to function well in areas with low wind speeds and severely turbulent flow conditions. VAWTs also provide benefits including lower structural complexity, omnidirectional wind acceptance, and adaptability for distributed and urban installations. Because of these features, VAWTs are especially appealing for situations with considerable space constraints and fluctuating wind conditions. Among the various VAWT designs, the Archimedes Spiral Wind Turbine (ASWT) has recently attracted notable interest due to its unique helical geometry, which promotes smoother and seamless airflow interaction and enhanced torque output compared to conventional designs [8,9,10,11].

Despite these improvements, VAWTs’ aerodynamic performance is determined by fundamentally unstable flow events, most notably dynamic stalls. This phenomenon is caused by cyclic variations in the blade angle of attack during rotation, which result in the formation, growth, and shedding of large-scale vortices. Although dynamic stalls might temporarily increase lift, they eventually cause flow separation, greater drag, and large load fluctuations, all of which have a negative influence on efficiency and structural integrity [12]. In contrast, VAWTs offer notable advantages such as omnidirectional operation and simplified maintenance, making them particularly well suited for deployment in turbulent urban wind environments [13,14,15]. Nevertheless, these systems face inherent drawbacks: their efficiency remains relatively low (20–30%), and they demand higher cut-in wind speeds (>3.5 m/s). Such requirements often exceed the range of typical urban wind conditions, which generally fall between 2 and 8 m/s [16,17]. This discrepancy highlights a critical technological gap and reinforces the urgent need for innovative solutions in low-velocity wind energy conversion systems. The complexity of these flow interactions emphasizes the vital requirement for advanced aerodynamic design solutions that can regulate separation and stabilize the flow field to improve overall turbine performance.

In response to these challenges, extensive computational and experimental research has been carried out to characterize the aerodynamic behavior of ASWTs and identify key performance-determining parameters. CFD, using Reynolds-Averaged Navier–Stokes (RANS) formulations and turbulence models like the SST k-ω model, is a trusted tool for predicting boundary-layer behavior, flow separation, and wake dynamics in wind turbine applications. While simplified methods such as Blade Element Momentum Theory (BEMT) remain useful for preliminary analysis, their accuracy can be limited in cases involving complex aerodynamic interactions and three-dimensional unsteady flow separation, especially when flow turbulence and blade curvature impacts are present. In such conditions, CFD-based approaches have shown improved predictive capability for resolving unsteady aerodynamic behavior [18]. When supported by grid independence studies and experimental validation, CFD simulations have demonstrated strong capability in accurately capturing the complex aerodynamic interactions governing turbine performance. Previous studies have demonstrated that turbine efficiency is highly sensitive to geometric features such as blade curvature, pitch angle, and overall rotor configuration. Reported results indicate that ASWTs can achieve power coefficient $\left(C_p\right)$ values in the range of approximately 0.25 to 0.29 at tip speed ratios $\left(TSR\right)$ between 1.5 and 2.19 [18,19,20,21,22], with some optimized configurations reporting $C_p$ values approaching 0.30 at higher $TSR$ ranges [19]. Furthermore, detailed flow field analyses have shown that blade angle variations significantly influence vortex dynamics, wake development, and energy extraction mechanisms, with optimal performance typically observed within $TSR$ ranges of approximately 1.0 to 2.0 [20].

Beyond primary geometric design, secondary structural parameters such as aspect ratio and rotor proportions have also been identified as critical determinants of aerodynamic performance. Variations in these parameters directly affect pressure distribution and flow behavior, thereby influencing torque generation and overall efficiency. Optimized configurations have been reported to achieve $C_p$ values of approximately 0.249 at $TSR$ values near 1.41, emphasizing the importance of dimensional tuning in turbine design [23]. In parallel, optimization-based studies have demonstrated that systematic parameter adjustment can significantly enhance both efficiency and operational stability, with peak performance generally occurring at $TSR$ values between 2 and 2.5 and $C_p$ values approaching 0.26 [24].

To further improve aerodynamic performance, a range of passive flow control techniques has been explored. The integration of vortex generators has been shown to enhance boundary-layer attachment and suppress flow separation, resulting in performance improvements of up to approximately 24% under certain operating conditions [25]. Similarly, advanced trailing-edge modifications, such as slotted deflective flaps, have demonstrated the ability to delay separation and reduce vortex shedding, leading to increases in the power coefficient of up to approximately 27% near optimal $TSR$ values [26]. These strategies are particularly effective in mitigating the adverse effects of dynamic stalls and improving the aerodynamic efficiency of rotating blades.

In addition to macro-scale design modifications, micro-scale surface treatments have emerged as an effective approach for improving aerodynamic behavior. Studies on VAWTs, including Savonius-type turbines, have shown that surface features such as dimples and fins can reduce drag and delay flow separation, resulting in performance enhancements of approximately $14–15\mathrm{\%}$ and improved torque generation, particularly at moderate wind speeds [27,28,29,30]. More recent investigations focusing on ASWT blades have confirmed that surface modifications can further improve boundary-layer characteristics and reduce wake losses, thereby enhancing energy conversion efficiency [31]. These findings demonstrate the potential of combining geometric optimization with surface engineering to achieve superior aerodynamic performance.

Moreover, system-level performance enhancements have been investigated through external flow manipulation techniques. The use of flow concentrators has been shown to accelerate incoming airflow and increase local wind velocity at the rotor, leading to improved torque generation and higher power coefficients compared to baseline configurations [32]. Such approaches highlight the significance of not only blade-level optimization but also the surrounding flow environment in determining overall turbine performance.

Recent advancements in blade profile design have further contributed to improving ASWT efficiency. Experimental and numerical studies have demonstrated that adopting airfoil-based blade profiles, such as NACA configurations, can significantly enhance aerodynamic performance. Power coefficients approaching approximately 0.30 have been achieved at $TSR$ values around $2$, with reported efficiency improvements of up to approximately 26.88% relative to conventional blade designs [33,34]. These results underscore the substantial impact of blade profile optimization on maximizing energy extraction.

Despite these significant advancements, the majority of existing studies have investigated performance enhancement strategies in isolation, focusing on either geometric optimization, surface modification, or flow control techniques independently. This segmented approach limits the ability to fully exploit the complex aerodynamic interactions governing ASWT performance. Therefore, there remains a critical need for an integrated design framework that simultaneously incorporates geometric optimization and advanced aerodynamic modifications to achieve synergistic performance improvements.

Although previous research has examined passive surface treatments on Savonius-type VAWTs and trailing-edge modifications on conventional wind turbine geometries, the incorporation of a trailing-edge flap developed and assessed specially for the Archimedes Spiral Wind Turbine geometry has not yet been documented in the literature. To close this gap, the main innovative contribution of this work is the introduction and computational evaluation of a trailing-edge flap modification on the ASWT. A thorough assessment of passive blade modification approaches for this turbine type is also provided by methodically assessing spherical dimple variants on the same geometry and directly comparing them against the flap modification and the smooth baseline. This dual-modification strategy, used in a single CFD framework under the same operating conditions, is what sets this study apart from earlier research.

Accordingly, the present study aims to develop and evaluate a modified Archimedes Spiral Wind Turbine through a comprehensive computational fluid dynamics (CFD) analysis. By systematically investigating the combined effects of geometric parameters and surface modifications, this work seeks to enhance energy harvesting efficiency and provide deeper insight into the underlying aerodynamic mechanisms governing ASWT performance under varying operating conditions.

2. Model Description

The turbine investigated in this work is an Archimedes wind turbine with a rotor length of 1.2 m, a diameter of 1.5 m, a blade angle $\alpha ={60}^{\circ }$, and a thickness of 5 mm, as shown in Figure 1.

Multiple simulations were carried out on the ASWT with the smooth blades so the results could be taken as a benchmark for the proposed alterations to the blades, which are meant to boost the overall performance. The two passive blade modifications considered in this study were spherical dimples and a trailing-edge flap.

All simulations were carried out using SolidWorks Flow Simulation 2025 under identical operating conditions to ensure consistent and comparable results. The inlet velocity was kept constant at 12 m/s throughout all simulations, as this was considered the optimal operating velocity, while the rotational speed of the turbine varied from 50 to 500 rpm in increments of 50 rpm. The wind turbine parameters used for the simulation are described in

Table 1. Parameters of the wind turbine.

Subject	Value	Unit
Rated power	500	W
Rated wind speed	12	m/s
Rated RPM	330	rpm
Blade dimensions	1.5 × 1.2	m
Number of blades	3	-

.

A rotating region was constructed around the turbine shape within the computational domain to precisely simulate the turbine blades’ rotational motion. While the outer domain stays stable, this rotating region serves as a cylindrical subdomain that encloses the turbine and rotates at the specified angular speed appropriate to each tested RPM. The solver can capture the interaction between the rotating blades and the surrounding airflow because the contact between the rotating and static sections permits the exchange of flow variables across the boundary. This method is crucial for CFD computations of rotating machinery because it guarantees that the pressure distributions, velocity fields, and aerodynamic forces generated around the blades are calculated in accordance with the proper rotational frame of reference, ultimately producing precise torque and power output estimations.

A baseline model was first established and then compared with several modified configurations intended to improve efficiency. The dimples were distributed along the edge region of the turbine blades, where flow behavior was expected to be most sensitive to surface modification. Four dimpled cases were analyzed: 100 dimples of 3 mm diameter, 400 dimples of 3 mm diameter, 400 dimples of 5 mm diameter, and 400 dimples of 7 mm diameter. In a separate configuration, a flap of 2 mm thickness was added at the blade edge. Based on geometric measurements from the CAD model, the flap height was 4.68 mm on the inner edge and 7.04 mm on the outer edge. The performance of all modified cases was evaluated against the baseline configuration using the power coefficient C_p vs. TSR under identical operating conditions.

3. Mathematical Modeling

To quantitatively assess the aerodynamic performance of the proposed Archimedes Spiral Wind Turbine, a thorough mathematical framework is developed to characterize fluid flow behavior and energy conversion. The study is based on the fundamental principles of fluid mechanics, with the governing equations of motion, such as the continuity and momentum equations, used to characterize the interaction between the incoming airflow and the rotating turbine blades. These equations form the foundation for forecasting velocity fields, pressure distributions, and the consequent aerodynamic forces responsible for torque generation.

SolidWorks Flow Simulation solves the governing equations of fluid motion, including the conservation equations of mass, momentum, and energy. For turbulent flows, the Reynolds-averaged Navier–Stokes equations are solved together with turbulence transport equations. The equations are implemented in conservative form using a finite-volume discretization approach, allowing for the conservation of mass and momentum over each computational control volume.

Furthermore, essential performance metrics such as the power coefficient ($C_p$) and tip speed ratio ($TSR$) are established to evaluate the turbine’s efficiency under different operating situations. The link between these factors allows for the assessment of the turbine’s ability to extract kinetic energy from the wind and convert it into useful mechanical power. This mathematical formulation serves as the foundation for the subsequent computational fluid dynamics (CFD) research, resulting in a consistent and physically grounded approach to performance prediction. Therefore, the aerodynamic quantities obtained in this study, including torque, power, $TSR, { C}_p$ and $C_q$, are based on the numerical solution of the governing conservation equations of fluid flow.

$$\begin{gathered} Re={\displaystyle \frac{\rho vL}{\mu } \\ Re=\frac{1.225 \times 12 \times 1.5}{1.81 \times {10}^{-5}} \\ Re\approx 1.22 \times {10}^6} \end{gathered}$$

(1)

where

-

$Re$ = Reynold’s number;

-

$\mu$ = dynamic viscosity $\left(\mathrm{k}\mathrm{g}/\mathrm{m}·\mathrm{s}\right);$

-

$\rho$ = air density $\left(\mathrm{k}\mathrm{g}/{\mathrm{m}}^3\right);$

-

$L$ = pipe diameter $\left(\mathrm{m}\right);$

-

$v$ = flow velocity $\left(\mathrm{m}/\mathrm{s}\right).$

$$C_p={\displaystyle \frac{P}{0.5\times \rho \times A\times V^3}}$$

(2)

where

-

$C_p$ = power coefficient;

-

$P$ = turbine power $\left(\mathrm{W}\right);$

-

$\rho$ = air density $\left(\mathrm{k}\mathrm{g}/{\mathrm{m}}^3\right);$

-

$A$ = swept area $\left({\mathrm{m}}^2\right);$

-

$V$ = free-stream wind speed $\left(\mathrm{m}/\mathrm{s}\right).$

$$\omega ={\displaystyle \frac{2\times \pi \times N}{60}}$$

(3)

where

-

$\omega$ = angular velocity $\left(\mathrm{r}\mathrm{a}\mathrm{d}/\mathrm{s}\right);$

-

$N$ = rotational speed $\left(\mathrm{r}\mathrm{p}\mathrm{m}\right).$

$$\lambda ={\displaystyle \frac{\omega \times R}{V}}$$

(4)

where

-

$\lambda$ = tip speed ratio $\left(TSR\right).$

4. Methodology: Dimples and Flaps

4.1. Dimples

The first blade modification investigated was the addition of dimples. This modification was intended to reduce flow separation over the blade surface. The dimple concept was first explored through different placement strategies to identify the most sensitive blade regions for surface alteration. Based on this preliminary assessment, four representative dimple configurations were selected for detailed simulation: 100 dimples of 3 mm diameter, 400 dimples of 3 mm diameter, 400 dimples of 5 mm diameter, and 400 dimples of 7 mm diameter. These dimples were placed based on the blade flow analysis. As shown in Figure 2, flow separation was suspected to occur at a specific region on the blade, so the dimples were positioned accordingly. The dimples were tested first, with this diameter selected as the initial parameter for the dimple parametric study. The blade thickness was the main constraint limiting the maximum dimple diameter. After the initial 7 mm diameter dimples failed to produce promising results, the dimple diameter was reduced. It was determined that surface dimples are not an appropriate passive alteration for this turbine design because all dimpled configurations consistently decreased aerodynamic performance in comparison to the smooth baseline. This result is an important study finding in and of itself since it shows that methods that work well for traditional airfoil-based blades do not always adapt well to the three-dimensional curvature-based design of the ASWT.

4.2. Flaps

A flap was then introduced as the second blade modification. A trailing-edge flap was added to the upper face of the blade to improve the aerodynamic performance of the turbine.

For each simulation, the following average performance parameters were extracted: power coefficient $\left(C_p\right)$, torque coefficient $\left(C_q\right)$, torque, power, and tip speed ratio $\left(TSR\right)$.

5. Results and Discussions

The following are the results of the minimum gap size and mesh sensitivity analysis mentioned above, which took into consideration mesh 1 through 7 and a minimum gap size of $0.025$ to $0.005$ m, with an interval of $0.005$ m.

The mesh sensitivity analysis highlighted in Figure 3a shows that as the mesh level increases, the variation in C_p becomes smaller, indicating convergence of the solution. A noticeable change in C_p is observed between lower mesh levels (1–3), while the variation between higher mesh levels (3–6) becomes minimal. This confirms that mesh level 3 is sufficient to capture the flow physics without excessive computational cost.

Similarly, the minimum gap size sensitivity analysis highlighted in Figure 3b shows that reducing the gap size improves the resolution of the flow near the blade surface, particularly in regions of high-velocity gradients. The minimum gap size refers to a mesh refinement parameter in SolidWorks Flow Simulation rather than a physical gap within the turbine geometry. This parameter defines the smallest geometric feature or flow passage that the meshing algorithm attempts to resolve. The default minimum gap size generated by SolidWorks 2025 flow simulation was approximately 1.3 m, which is excessively large relative to the dimensions of the turbine blades and would not adequately capture the local flow features. Therefore, the minimum gap size was reduced to 0.02 m to improve mesh resolution around the blade geometry and better resolve the associated velocity gradients and flow structures. Further reduction was considered unnecessary because it would substantially increase the computational cost while producing negligible changes in the calculated aerodynamic performance parameters. Reducing the minimum gap size below 0.02 m resulted in only negligible changes in Cp. Therefore, a minimum gap size of 0.02 m was selected, as it provides a balance between accuracy and computational efficiency.

The values chosen at the end of these studies were a minimum gap size of 0.02 m and mesh 3, as they demonstrate both accuracy and less computational time.

The time step in SolidWorks Flow Simulation is automatically controlled by the solver throughout the computation rather than being fixed. Until the monitored engineering goals meet the specified convergence threshold, the solver runs the simulation by dynamically modifying the time step depending on the local flow conditions and numerical stability criteria. The entire physical simulation duration for the chosen mesh configuration (mesh 3) was 1.17616 s, with a final recorded time step of 0.00397571 s at the point of convergence.

During every simulation, the observed quantities, such as the power coefficient ($C_p$), torque coefficient ($C_q$), torque, power, tip speed ratio ($TSR$), angular velocity and inlet velocity, were studied as engineering objectives. Only when every monitored goal attained 100% of the convergence criterion as provided by the solution was convergence deemed accomplished. Therefore, instead of using immediate current values, the final values presented in this analysis were taken from the averaged value column of the objectives log once convergence was verified. By using this method, the stated aerodynamic quantities are guaranteed to reflect stable, time-averaged behavior rather than fleeting variations in the flow field.

Table 2. Convergence summary for the mesh 3 case.

Parameter	Value	Units
Mesh level	Mesh 3	-
Total cells	274,498	-
Iterations to convergence	317	-
Travels	1.0022	-
Physical simulation time	1.17616	S
Final time step	0.00397571	S
Goal convergence	100	%
Reported value type	Averaged goals	-

provides an overview of the convergence parameters for mesh 3.

In terms of computational cost, each mesh 3 simulation took about 20 min to attain convergence. The overall computational time was substantial due to the testing of ten rotational velocities for each blade configuration and the evaluation of several configurations; however, the results were essentially comparable because the same standardized mesh and uniform convergence specifications were used in all cases.

To evaluate the performance of the ASWT, the power coefficient ($C_p$) was plotted as a function of the tip speed ratio $\left(TSR\right)$ for the smooth and flapped blade configurations.

In Figure 4, the $C_p-TSR$ curves show a behavior consistent with the literature, where $C_p$ increases with $TSR$ up to an optimal point and then decreases. This trend reflects the balance between aerodynamic torque generation and increasing drag losses at higher rotational speeds. At low $TSR$, the turbine does not extract energy efficiently due to low relative velocity, while at high $TSR$, aerodynamic losses dominate, reducing performance.

The smooth blade configuration shows a clear peak $C_p$ within the expected $TSR$ range, confirming that the turbine operates under realistic aerodynamic conditions. The flap configuration consistently produces higher $C_p$ values across the entire $TSR$ range, with the most significant improvement observed near the optimal $TSR$ region.

This improvement indicates that the flap modifies the flow structure around the blade, enhancing lift generation. As a result, the torque produced by the turbine increases, which directly contributes to a higher $C_p$.

Dimples usually demonstrate improvements in conventional wind turbine blades by delaying flow separation and energizing the boundary layer. Based on this, an analysis of the smooth blade was conducted to identify regions of low velocity and near-zero shear stress, indicating possible flow separation zones.

However, after implementing multiple spherical dimple configurations in these regions, the results showed a consistent decrease in performance, as shown in Figure 5. While the “spherical dimples” appear round from their top view, their geometry is three-dimensional, with each dimple forming a spherical cap pressed into the blade surface, as shown in Figure 2.

This suggests that, unlike conventional airfoil-based blades, the flow over the Archimedes turbine is highly three-dimensional and already dominated by complex curvature effects. The introduction of dimples increased surface roughness without effectively controlling separation, leading to higher drag and reduced aerodynamic efficiency. Therefore, the dimple modification was found to be ineffective for this specific turbine geometry.

The addition of a trailing-edge flap with a thickness of $2$ mm and an outer length of $7.04$ mm and inner length of $4.68$ mm resulted in a noticeable and significant improvement in performance across all operating conditions and variables. The flap dimensions were chosen as a preliminary experimental configuration rather than a result of formal parametric optimization, which were determined using the local blade geometry acquired from the CAD model, guaranteeing that the flap maintained a mathematical compatibility with the blade’s trailing-edge profile. This layout was designed as a proof of concept to see if a trailing-edge flap could provide significant aerodynamic benefits on the turbine in question. A systematic optimization of flap dimensions can be observed as a potential field for future research.

Figure 6 illustrates the percentage increase in $C_p$, where the y-axis origin represents the baseline smooth turbine. The improvement is attributed to the flap modification; although the increase peaks at certain operating points and diminishes at others, it remains a net positive gain throughout.

The detailed numerical values of the power coefficient and the corresponding percentage improvement for the flap configuration are presented in

Table 3. $C_p$ values and percentage improvement in the flap configuration relative to the smooth baseline across all tested operating conditions.

RPM	Smooth ${\mathit{C}}_{\mathit{p}}$ Front	Flap ${\mathit{C}}_{\mathit{p}}$ Front	${∆\mathit{C}}_{\mathit{p}}$ Absolute Front	TSR	% Increase
50	0.060706	0.083519	0.022813	0.327	37.58%
100	0.115569	0.159386	0.043817	0.654	37.92%
112.5	0.127518	0.177739	0.050221	0.736311	39.38%
125	0.142815	0.191537	0.048722	0.821396	34.12%
137.5	0.164404	0.203758	0.039354	0.899935	29.28%
150	0.181656	0.19903	0.017374	0.982	9.57%
200	0.227176	0.247608	0.020432	1.309	8.99%
250	0.242769	0.265645	0.022876	1.636	9.43%
300	0.240079	0.264674	0.024595	1.964	10.24%
350	0.219052	0.245297	0.026245	2.291	11.98%
400	0.177677	0.205916	0.028239	2.618	15.90%
450	0.113557	0.143638	0.030068	2.945	26.48%

.

This behavior can be explained by the better control of the flow separation and improved lift generation produced by this flap.

In Figure 7, the plotted $C_p-TSR$ curves exhibit a common overall pattern across the different ASWT studies and the present work. Visually, each curve begins with a gradual rise in the low-$TSR$ region, continues upward toward a single dominant peak, and then declines again as $TSR$ increases further. Although the exact steepness of the rise, the position of the peak region, and the rate of decline differ slightly from one curve to another, the general profile remains very similar throughout. In other words, all curves retain the same characteristic parabolic-like or bell-shaped trend, despite being obtained from different investigations.

This consistent behavior is significant because it shows that the general aerodynamic response of the Archimedes spiral wind turbine remains fundamentally unchanged, even when the studies differ in geometry, scale, blade design, numerical assumptions, experimental procedures, and operating conditions. While such variations may influence the detailed position of the optimum region or slightly shift the curve upward, downward, left, or right, they do not alter the essential shape of the $C_p-TSR$ relationship itself. The repeated appearance of this same trend in the literature suggests that it is an inherent performance characteristic of ASWT systems rather than a feature unique to a particular model or simulation setup.

As a result, the curve shape agreement between the current findings and the published research offers helpful qualitative validation. However, because the referred studies differ in terms of geometry, scale, blade design, operating conditions, and experimental or numerical assumptions, this comparison should be viewed as qualitative rather than completely quantitative. Thus, the resemblance in the bell-shaped Cp-TSR trend does not constitute a full quantitative validation against an equivalent experimental or numerical benchmark, but it does verify the realism of the current CFD behavior. Comparison with experimental data or a verified CFD case with comparable geometry, boundary conditions, and operating conditions would be necessary for a more thorough validation. While recognizing the constraints of the validation approach, this validates the interpretation of the information at hand and supports the conclusion that the simulated aerodynamic performance is realistic and consistent with the known features of Archimedes spiral wind turbines.

Overall, during the simulations that were carried out, the ASWT followed the expected $C_p-TSR$ trend. The dimpled configurations did not improve the performance of the turbine and instead had a negative effect on all the parameters, indicating that this modification is not suitable for this specific blade geometry, and potentially most geometries of this turbine. In contrast, the trailing-edge flap consistently improved the performance across the tested RPM range. Therefore, among the studied blade alterations, the flap configuration has proven to be the most effective method for enhancing the performance of the ASWT.

6. Conclusions

A CFD-based assessment of an Archimedes Spiral Wind Turbine was conducted to examine the aerodynamic effects of two passive blade modifications, namely surface dimples and a trailing-edge flap, relative to a smooth baseline configuration. The baseline results reproduced the characteristic $C_p-TSR$ trend reported for Archimedes turbines in the literature, with a peak of $C_p=0.24277$ for the smooth blades and $C_p=0.2565$ for the blades with the flap at $TSR=1.63625$, supporting the credibility of the adopted methodology. The results showed that the aerodynamic effectiveness of passive control strategies is strongly dependent on the underlying blade geometry. In the present case, the introduction of spherical dimples near the blade edge did not improve performance; instead, all dimpled configurations produced a measurable reduction in $C_p$ compared with the smooth blade, with losses of approximately $2.13–3.63\mathrm{\%}$ near the optimal operating condition. This behavior indicates that the complex three-dimensional flow development over the Archimedes blade is not favorably altered by localized surface roughness and that the added dimples primarily increased aerodynamic penalties rather than improving boundary-layer behavior. By contrast, the trailing-edge flap consistently enhanced turbine performance over the operating range investigated. The flap increased the power coefficient by approximately $5.66\%$ around the optimum $TSR$, with larger gains observed at higher $TSR$ values, indicating a sustained positive aerodynamic effect. This improvement is attributed to more favorable flow guidance near the blade edge, leading to better control of separation and enhanced aerodynamic loading. Among the tested configurations, the flapped blade therefore represented the most effective modification for improving ASWT performance. Overall, the findings demonstrate that performance enhancement in Archimedes Spiral Wind Turbines requires geometry-specific design interventions rather than direct adoption of concepts proven for conventional blade forms. Within this context, trailing-edge flap implementation appears to be a promising passive strategy for improving the aerodynamic efficiency of small-scale ASWT systems. Further work should focus on experimental validation and on a broader parametric optimization of flap geometry, placement, and inclination to clarify the governing flow mechanisms and to determine the limits of achievable performance improvement.