Hydrodynamic Analysis of a NREL 5 MW Monopile Wind Turbine Under the Effect of the 30 October 2020 İzmir-Samos Tsunami

Abstract

Although offshore wind turbines are essential for renewable energy, their construction and design are quite complex when environmental factors are taken into account. It is quite difficult to examine their behavior under rare but dangerous natural events such as tsunamis, which bring great danger to their structural safety and serviceability. With this motivation, this study investigates the effects of tsunami and wind on an offshore National Renewable Energy Laboratory (NREL) 5 MW wind turbine both hydrodynamically and aerodynamically. First, the NREL 5 MW monopile offshore wind turbine model was parameterized and the aerodynamic properties of the rotor region at different wind speeds were investigated using the blade element momentum (BEM) approach. The tsunami data of the İzmir-Samos (Aegean) tsunami on 30 October 2020 were reconstructed using the data acquired from the UNESCO data portal at Bodrum station. The obtained tsunami wave elevation dataset was imported to the QBlade software to investigate the hydrodynamic and aerodynamic characteristics of the NREL 5 MW monopile offshore under the tsunami effect. It was observed that the hydrodynamics significantly changed as a result of the tsunami effect. The total Morison wave force and the hydrodynamic inertia forces significantly changed due to the tsunami–monopile interaction, showing similar cyclic behavior with amplified forces. An increase in the horizontal force levels to values greater than twofold of the pre-event can be observed due to the İzmir-Samos tsunami with a waveheight of 7 cm at the Bodrum station. However, no significant change was observed on the rated power time series, aerodynamics, and bending moments on the NREL 5 MW monopile offshore wind turbine due to this tsunami.

1. Introduction

Offshore wind turbines are a frequently studied topic by researchers due to the recent increase in energy demand. For this reason, the hydrodynamic and aerodynamic properties of offshore wind turbines are challenging due to their location. There are some studies in the literature examining the hydrodynamic and aerodynamic aspects of offshore wind turbines. In the study conducted by Cheng et al., an aero-hydrodynamic model was created using OpenFOAM for the numerical simulation of a floating wind turbine [1]. In the study conducted by Tran et al., a high-fidelity fluid-structure interaction simulation was created that takes into account aero-hydrodynamic effects using the Computational Fluid Dynamics (CFD) approach based on the overset grid technique [2]. In another study conducted by Shi et al. [3], hydrodynamic and aerodynamic loads were investigated in the time domain for three different FOWTs under normal and extreme conditions. Also, second-degree hydrodynamic loads were investigated by analyzing at different water depths. In the study conducted by Xu et al., the aerodynamic characteristics of floating offshore wind turbines (FOWT) under the atmospheric boundary layer were investigated [4]. Also, wake characteristics were investigated in the study [4]. In another investigation conducted by Bayati et al., the second-order hydrodynamic effects on semi-submersible FOWTs were investigated [5]. In a study conducted by Ren et al., the hydrodynamic properties of the Monopile-WT-WEC Combination concept, which was introduced as a new concept, were numerically investigated in both time and frequency domains under operational sea conditions [6]; 1:50 scale-model tests were also conducted.

The performance of horizontal and vertical wind turbines can be analyzed both hydrodynamically and aerodynamically using software such as ANSYS, OpenFAST, and QBlade. Comprehensive comparisons between various software are presented in the literature [7]. Also, there are many studies in the literature that rely on QBlade and experimentally validate it, including the verification of its embedded offshore wind turbine module. Thus, QBlade is used in this study, which provides a numerical approach. In the study conducted by Faisal Mahmuddin in 2017, he designed and analyzed the blade profile using BEM and Qblade [8]. In another study conducted by Alaskari et al., an analysis was conducted of a horizontal wind turbine that could produce less than 1 kW of energy [9]. In a study conducted by Robiul Islam et al., the blade designs and analyses of small wind turbines under low wind speeds were carried out using Qblade. In the study, verification was performed using BEM theory with the help of MATLAB software [10]. Koç et al. investigated QBlade, and XFOIL was combined to design and analyze the airfoil. Then, a horizontal-axis wind turbine with a diameter of 2 m was designed and analyzed. Similarly, the same turbine was analyzed using ANSYS-Fluent, which uses the CFD approach, and the results were compared [11]. In a study conducted by Szczerba et al., the effect of the blade pitch angles of H-type vertical axis wind turbines on the turbine characteristics was investigated numerically and experimentally [12]. QBlade was used for the study [12]. The highest values of the power coefficient (Cp) obtained at different pitch angles and different wind speeds were compared experimentally and numerically [12]. In the study conducted by Muhsen et al., the design and optimization of a small-scale horizontal wind turbine at low wind speed was carried out [13]. For this purpose, Xfoil and Qblade were used [13]. The Cp values obtained as a result of the study were compared with the experimental results conducted in [14,15]. In a study conducted by Husaru et al., the effect of yaw angle on the performance of horizontal axis wind turbine was investigated [16]. For this purpose, QBlade software was used [16]. As a result of the study, it was seen that the power coefficient data obtained were compatible with the experimental data [16]. In a study conducted by Chaudhary et al., both experimental and numerical studies of a small horizontal axis wind turbine were carried out [17]. For this wind tunnel test, QBlade was used and a CFD study was carried out [17]. In the study, the creation of an optimal wind turbine blade was attempted using 14 different airfoils under low wind speed [17]. In a study conducted by Barber and Nordborg, the development of tools used for the analysis of vertical axis wind turbines was studied [18]. For this purpose, the data obtained from wind tunnel tests were compared with the simulation results using QBlade [18].

Natural disasters such as tsunamis can greatly influence offshore structures involving offshore wind turbines. Thus, it is crucially important to investigate the dynamics of monopile offshore wind turbines under the influence of such events. Some studies in the literature have been conducted on the effect of tsunamis on offshore wind turbines. In a study conducted by Matsunobu et al., the effects of earthquakes and tsunamis on wind turbines were analyzed [19]. In a study conducted by Min et al. in 2024, the performance and dynamic responses of a 15 MW semi-submersible type floating wind turbine moored in shallow water under the influence of Tohoku tsunami waves were investigated [20], where the tsunami waves were formed by combining three-component solitary waves [20]. Another recent study investigated the gravity-based foundation of offshore wind turbines under tsunamis, where a three-dimensional numerical model of dam-break wave tsunami with small, middle, and large scales was considered [21]. Designing wind turbines and farms with the ability to withstand tsunamis remains an open and challenging problem. Also, many future studies will be needed to investigate their dynamics under real and measured data.

With this motivation, the hydrodynamic and aerodynamic effects of the 30 October 2020 İzmir-Samos tsunami on a hypothetical NREL 5 MW monopile offshore wind turbine were investigated numerically in this study. To our best knowledge, the effects of the 30 October 2020 İzmir-Samos tsunami on offshore wind turbines have not been studied in the literature. This study aims to investigate the typical dynamics of NREL 5 MW Monopile offshore wind turbines in the Aegean Sea as a pioneering study. Similar dynamics are expected to be observed in a possible tsunami event in the near future. The data used for the study were obtained from UNESCO’s station in Bodrum. The Fast Fourier Transform-inverse Fast Fourier Transform (FFT-IFFT) method was used to filter the tsunami data from the tidal effects in the region following [22]. Then, the hydrodynamic and aerodynamic effects of the NREL 5 MW Monopile offshore wind turbine, subjected to daily wave elevation data including pre- and post-tsunami effects, were investigated using QBlade. The results of the study and its impact on the early warning methods were discussed. Although our results are given for the 30 October 2020 İzmir-Samos tsunami, which is relatively small, it can shed light on future studies in the Aegean Sea region and can be used as a milestone for future analysis of turbines subjected to measured tsunami loading.

2. Methodology

2.1. Study Area

The data used in the study are the tsunami data resulting from the İzmir earthquake that occurred on 30 October 2020 at 12:51 p.m. UTC. The seismicity map of the earthquake is shown in Figure 1 [23]. As seen in Figure 1, the epicenter of the earthquake and the locations of 5068 aftershocks are shown [23]. The magnitude of the earthquake that occurred 23 km south of İzmir was measured as 6.9 Mw [24,25]. The epicenter of the earthquake is near the island of Samos. The Kaystrios fault is considered to be the primary seismogenic fault of the earthquake [24]. The Kaystrios fault, together with the surrounding Ikaria, Fourni, and Pythagorean arcs, forms a complex fault system [24]. Geodetic, seismic, and tsunami data were used in the analysis of the earthquake. Although the global magnitude and impact of the earthquake and the tsunami that occurred as a result of the earthquake were not big compared to earthquakes and tsunamis that occurred in other parts of the world, it was observed that it had serious effects locally. It is observed that floods and damages occurred in locations close to the region as a result of the tsunami. The 30 October 2020 İzmir-Samos tsunami data were measured by many different stations in the region [26]. Figure 2 shows the epicenter and four of these stations [26].

The dataset used for the study includes wave elevations recorded by the Bodrum station between 00:00 on 30 October 2020 and 00:00 on 31 October 2020. The sampling time is 0.5 min and tsunami wave height at this station is on the order of 7 cm. The records at the Bodrum station are obtained with an acoustic echo sounder. The wave elevation data taken from Bodrum station were filtered from tidal effects using FFT-IFFT routines as described in [22]. The wave elevation time series obtained as a result of the FFT-IFFT method is shown in Figure 3 where the * sign indicates the occurrence of the earthquake event.

2.2. Offshore Wind Turbine

The NREL 5 MW wind turbine, which is frequently used in studies on offshore wind turbines, was also used in this study. The analysis of the NREL 5 wind turbine was performed by Jonkman [27]. The geometrical and structural properties of the wind turbine and the properties of the monopile platform were obtained from sample programs in QBlade [28]. The geometrical structure of the single blade of the NREL 5 MW monopile offshore wind turbine and its 3D rendering are depicted in Figure 4. Also, the dimensions of geometric area are shown in Figure 5.

In QBlade, the length of the wind turbine blade in the model used is 61.5 m, the rotor diameter is selected to be 126 m, and the swept area of the blade is 12,461.91 ${\mathrm{m}}^2$. It is seen that the values given in the program are consistent with a study conducted by Jonkman [27]. In the study conducted by Jonkman, it was stated that the hub height of the wind turbine was 90 m, and the cut-in, rated, and cut-out wind speeds were 3 m/s, 11.4 m/s, and 25 m/s, respectively. The cut-in and rated rotor speed values were 6.9 rpm and 12.1 rpm, respectively, and the rated speed value was 80 m/s [27].

2.3. Aerodynamics of Wind Turbine

QBlade uses steady blade element momentum (BEM) and unsteady blade element momentum (UBEM) theories to calculate aerodynamic loads acting on wind turbines [29]. Their summaries are presented herein.

2.3.1. Blade Element Momentum Theory

BEM theory is an approach that is easy to use and provides consistent and reliable results in steady situations [29]. Actuator disc theory can be used for the BEM approach. In actuator disc theory, the flow can be assumed to be unsymmetrical, incompressible, and steady [29]. According to the approach, the rotor region is considered as an actuator disc, and it is assumed that the pressure decreases uniformly within this area and the velocity values change continuously [29]. It is assumed that there is no tangential velocity component [29]. It is assumed that the pressure is equal to the atmospheric pressure at the boundaries in front of and behind the rotor region, which is far from the rotor area [29]. If all these assumptions are made, the aerodynamic power and thrust force of the rotor can be calculated. The velocity components can also be calculated with the conservation of mass and conservation of momentum [30]. The induction factor value required to calculate the velocity component in the rotor region given by Equation (1) as

$$u=(1-a)u_{\infty }$$

(1)

where a is the induction factor, u is air velocity passing through rotor region, and $u_{\infty }$ represents the free field wind velocity. Equations (2) and (3) formulate the rotor performance coefficients for power and thrust force respectively as

$$C_P=4a{(1-a)}^2$$

(2)

and

$$C_T=4a(1-a).$$

(3)

These calculations can be performed analytically which can be used for the derivation of important criteria of the blade element momentum theory such as the Betz criterion. According to this theory, the blade is divided into subsections. The loads acting on the blade divided into these subsections are calculated separately. While making this calculation, it is assumed that the flow in that section is two-dimensional and in the plane of the blade profile. In this way, the drag, lift, and moment coefficients acting on the airfoil cross-section, as well as the relative speed value, can be determined and the forces acting on the airfoil can be calculated [29]. The BEM approach is two-dimensional and some improvements need to be made to perform three-dimensional analysis [29]. One of these improvements is the Prandtl tip loss factor calculations [31]. The Prandtl tip loss factor was used in the analysis conducted for this study as discussed in [32].

2.3.2. Unsteady Blade Element Momentum

The classical BEM approach provides appropriate and consistent results for steady flows. However, it is observed that it does not produce sufficiently accurate results in complex cases (atmospheric boundary conditions, turbulence, or the effect of the tower) [29]. Due to these and similar conditions that will affect the analysis, it is necessary to know the position of the blade at each time step for the solution. The non-rotating coordinate systems are placed at the base of the tower and nacelle [29]. Coordinate axes are defined for each rotating blade and shaft region. In this way, the instantaneous velocities seen on the blades can be calculated [33]. A dynamic inlet flow model is used to add a time delay to the cross-sectional rotor induction [32,34].

2.4. Hydrodynamics of Wind Turbine

In this section, the theories that provide the basis for the hydrodynamic analyses performed using QBlade are explained. The theoretical information in this section is obtained from the QBlade website [35]. QBlade uses potential flow theory and the Morison equation to calculate hydrodynamic forces.

2.4.1. Potential Flow and Boundary Conditions

Using potential flow theory wave forces and moments can be calculated. Since the flow is assumed to be irrotational according to the potential flow theory, the velocity potential value used to define the velocity field obeys Laplace’s differential equation. The velocity field is calculated by Equation (4).

$$\overline{v}=\nabla \varphi ={\displaystyle \frac{\partial \varphi }{\partial x}}{\overline{e}}_x+{\displaystyle \frac{\partial \varphi }{\partial y}}{\overline{e}}_y+{\displaystyle \frac{\partial \varphi }{\partial z}}{\overline{e}}_z$$

(4)

Three boundary conditions are needed to solve the governing equation [36]. The first boundary condition is at the free water surface. Equation (5) shows the first combined boundary condition at the free water surface

$${\displaystyle \frac{\partial \varphi }{\partial z}}-{\displaystyle \frac{{\omega }^2}{g}}\varphi =0$$

(5)

where $\omega$ represents the discrete frequency, g is gravity acceleration. The Equation (5) is valid at $z=0$. The second boundary condition is the kinematic bottom boundary condition given either by Equation (6) for deep water as

$$\nabla \varphi \to 0$$

(6)

or by Equation (7) for finite water depth as

$${\displaystyle \frac{\partial \varphi }{\partial z}}=0.$$

(7)

The third boundary condition is related to the Sommerfeld condition, according to which wave energy is radiated in all directions as a result of the disturbance caused by an object in water. Three different assumptions have been made here for the following point. The first of these is that the floating body does not make small motions while leaving the equilibrium position, and if it does, it is ignored. The second assumption is that the solutions are harmonic. The final assumption is that the floating body submerged the fluid with density $\rho$. The equation of motion suggested by Cummins [37] as a result of his work is shown in Equation (8).

$$(M_{ij}+A_{ij}^{\infty }){\ddot{x}}_j\left(t\right)+{\int }_{-\infty }^t{K}_{ij}(t-\tau ){\dot{x}}_j\left(\tau \right)d\tau +C_{ij}{x}_j\left(t\right)=F_j^{\omega }\left(t\right)-F_j^e(x,\dot{x},t)$$

(8)

In this formula, $F_j^m$ is external force caused by mooring effect, $F_j^{\omega }$ external force caused by waves, $A_{ij}^{\infty }$, $C_{ij}$, $K_{ij}$ are matrix of added mass, hydrostatic stiffness and radiation damping respectively, $M_{ij}$ shows the inertia of the floater.

2.4.2. Morison Equation

In QBlade, the Morison wave force was used to calculate the hydrodynamic wave force acting on cylindrical structures. The program uses two different Morison forces. The first Morison force is the normal force acting at the center of the structure. The second Morison force is the axial force acting at the end of the structure. The equation used for the calculation of the Morison force acting at the center of the cylinder is given by Equation (9) as

$$F_M^n=\rho \pi {({\displaystyle \frac{D}{2}}+R_{MG})}^{2}L((C_a^n+C_p^n){\dot{u}}^n-C_a^n{\ddot{X}}^n)+{\displaystyle \frac{1}{2}}\rho (D+R_{MG})L{C}_d^n(u^n+{\dot{X}}^n)|u^n-{\dot{X}}^n|$$

(9)

where D is the diameter of the cylinder body, L is the length of the cylinder body, $R_{MG}$ is the marine growth thickness, $F_M^n$ is the normal hydrodynamic Morison wave force, ${\ddot{X}}^n$ is the normal velocity of the center of the cylinder element, $u^n$ is the normal flow velocity, $C_a^n,C_p^n,C_d^n$ is the normal added mass coefficient, normal dynamic pressure coefficient, normal drag coefficient respectively. The equation used for the hydrodynamic axial Morison wave force calculation is shown in Equation (10):

$$\begin{array}{c}\hfill F_M^{ax}=\rho {\displaystyle \frac{2\pi }{3}}{({\displaystyle \frac{D}{2}}+R_{MG})}^3{C}_a^{ax}({\dot{u}}_{ax}-{\ddot{X}}^{ax})+\\ \hfill C_p^{ax}{p}_{dyn}^{ax}\pi {({\displaystyle \frac{D}{2}}+R_{MG})}^2+{\displaystyle \frac{1}{2}}\rho \pi {(D+R_{MG})}^2{C}_d^{ax}(u^{ax}+{\dot{X}}^{ax})|u^{ax}-{\dot{X}}^{ax}|\end{array}$$

(10)

where $u^{ax}$ is the axial flow velocity, $F_M^{ax}$ is the axial hydrodynamic Morison wave force, ${\ddot{X}}^{ax}$ is the axial velocity of the center of the cylinder element, $C_a^{ax},C_p^{ax},C_d^{ax}$ is the axial added mass coefficient, axial dynamic pressure coefficient, axial drag coefficient respectively.

In QBlade, the cylindrical element is divided into sub-elements to calculate the hydrodynamic forces. The Morison wave force acting on each subdivided element is calculated and applied at each time step. It can be determined whether the sub-elements are underwater or not using the wave elevation. Also, wave kinematic values that are u and $\dot{u}$ can be calculated by using QBlade. These values are necessary to calculate Morison wave forces.

3. Results and Discussion

In this section, the results of the analysis conducted in the study are examined. First, BEM analysis is performed and the accuracy of the analysis is examined by comparing the values obtained in the study with the studies conducted in the literature. Then, the hydrodynamic and aerodynamic effects of the tsunami wave affecting the NREL 5 MW monopile offshore wind turbine are examined.

3.1. Validation of BEM Analysis

There are some analysis results for the NREL 5 MW wind turbine used in various studies in the literature. In this section, the results of the study by Jonkman [27], the study by Zhao et al. [38] and the study by Zhang and Wang [39] are compared. For comparison purposes, it is assumed that the turbine rotates at 10.3 rpm and the wind speed is 9 m/s. In addition, Prandtl-type root losses [40] are taken into account in the analysis to account for the losses in the tip and root regions. Power (W)–rotational speed (RPM) and torque (Nm)–rotational speed (RPM) graphs obtained as a result of the analysis carried out with the BEM method using Qblade are depicted in Figure 6 and Figure 7, respectively.

As seen in Figure 6, the power value corresponding to 10.3 RPM was calculated as 2.65 MW. In the study conducted by Jonkman [27], this value was approximately 2.67 MW, in the study conducted by Zhao et al. [38], this value was 2.89 MW, and similarly in the study conducted by Zhang and Wang [39], this value was 2.80 MW which commensurate with our findings.

As seen in Figure 7, the torque value corresponding to 10.3 RPM was measured as 2453.24 kNm as a result of BEM analysis. In the study conducted by Jonkman [27], this value was approximately 2474.50 kNm, in the study conducted by Zhao et al. [38], this value was 2682.00 kNm, and finally in the study conducted by Zhang and Wang [39], this value was 2596.96 kNm. It was observed that the results obtained with the BEM approach were accurate, as previously stated.

3.2. Hydrodynamic and Aerodynamic and Analysis of NREL 5 MW Monopile Wind Turbine Under the Effect of Tsunami Wave

In this section, the effect of the tsunami caused by the earthquake in the İzmir-Samos region of the Aegean Sea on 30 October 2020, on the NREL 5 MW monopile wind turbine was investigated hypothetically. In the analysis, the wind speed was assumed to be constant at 10 m/s. The selection of such a relatively high wind speed close to the rated wind speed enables us to observe the effects of the tsunami passage on the power production, if any. Although a constant wind speed is assumed, the findings of this paper can be easily generalized to other wind speeds, including transient data. The tsunami time series is taken as discussed above. As a result of the analysis, the aerodynamic power time series value of the NREL 5 MW monopile offshore wind turbine on 30 October 2020, is illustrated in Figure 8.

As seen in Figure 8, the tsunami had no significant effect on the aerodynamic power of the NREL 5 MW monopile wind turbine, which also makes it quite difficult to determine the passage of the tsunami from power time series, if not impossible. Our study also reveals the hydrodynamic properties of the NREL 5 MW offshore wind turbine under the influence of the tsunami. The total Morison wave force time series values of the NREL 5 MW wind turbine acting in the x-direction on the global axis for 30 October 2020, is shown in Figure 9.

As seen in Figure 9, the total Morison wave force value in the x-direction on the global axis appears to have grown even larger after the tsunami interaction with the monopile. When the Figure 9 is examined, the converged results indicate that pre-tsunami peak force of 1594.76 N increases to 3514.47 N due to passage of the İzmir-Samos tsunami. A 2.20-fold increase in the $X_g$ parameter is observed due to tsunami with a 7 cm of waveheight at the Bodrum station, indicating a significant change. Similarly, the total Morison wave force was also examined in the z-direction on the global axis, which is depicted in Figure 10. Both of the force-time series depicted in these graphs clearly indicate the cyclic effect of the tsunami on the amplified hydrodynamics of the monopile with similar spectral features. Thus, these time series can also be used to detect the passage of tsunamis offshore.

It is observed in Figure 10 that there is an increase in the total Morrison wave force value in the global axis z-direction as well as in the x-direction after the tsunami. Another important hydrodynamic feature is the inertia force. Thus, we also examine the change of hydrodynamic inertia forces in the x- and z-directions. The change of hydrodynamic inertia forces in the x-direction is shown in Figure 11.

As seen in Figure 11, there is a change in the hydrodynamic inertia force after the tsunami. The fact that the value change after the tsunami is greater than the value change before the tsunami shows the hydrodynamic properties of the tsunami with approximately 7 cm of wave height at the Bodrum station. When the Figure 11 is analyzed, the results shows that maximum pre-tsunami force of 1521.32 N increases to 3279.69 N because of passage of the İzmir-Samos tsunami. It is seen that approximately 2.16-fold increase in the $X_I$ parameter owing to tsunami with a 7 cm of waveheight at the Bodrum station. The time-dependent change of hydrodynamic inertia forces in the z-direction as well as in the x-direction was investigated. The change of hydrodynamic inertia forces in the z-direction is shown in Figure 12.

As Figure 12 confirms, there is a change in the value of hydrodynamic inertia force in the z-axis as well as in the x-axis due to the tsunami. The fact that the value change of hydrodynamic inertia force after the tsunami is greater than the value change before the tsunami shows the effect of the tsunami. Finally, in order to observe the moments induced by the 30 October 2020 İzmir-Samos tsunami, the bending moments at the roots in the y-axis were examined. The results obtained as a result of the examination are shown in Figure 13.

As seen in Figure 13, it was observed that the bending moments in the roots changed with time, however, the tsunami had no significant effect on this change.

The physical justification of these phenomena can be given as follows. The horizontal displacement velocity of the turbine is much smaller compared to the rated wind speed, and thus does not provide a significant difference in the net air inflow velocity to the rotor’s swept area, leading to an insignificant change in the rated power. In the bending moment case, the magnitude of oscillations of the bending moment induced by the İzmir-Samos tsunami is much smaller compared to the bending moment of the hydrostatic case, and thus hardly recognizable relatively. The dynamic pressure response factor quickly diminished with depth and forces exerted multiplied by the moment arm gave only small changes in the total bending moment. As a result of the analysis, it was seen that the tsunami did not have any significant effect on rated power, aerodynamics and bending moments on the NREL 5 MW monopile offshore wind turbine. However, the total Morison wave force and the hydrodynamic inertia forces significantly changed due to the tsunami–monopile interaction, showing similar cyclic behavior with amplified forces. The force and acceleration sensors installed on the monopiles can also be used to measure and detect tsunamis. Force, moment and wake detection using smart sensing techniques can be a major tool for such analysis [41]. However, the power time series and bending moments do not appear to be the ideal parameters for such purposes.

4. Conclusions

In this study, the hydrodynamic and aerodynamic properties of floating wind turbines under the effect of tsunamis were investigated. For this purpose, the dataset containing the time series of wave elevation formed in the region of the 30 October 2020, earthquake’s İzmir-Samos (Aegean) tsunami from UNESCO’s Bodrum station was used. Since the wave elevation in the dataset also included the tidal effect, the dataset was purified from the tidal effect by applying the FFT-IFFT methods. Considering a hypothetical NREL 5 MW monopile offshore wind turbine, BEM analysis was performed to measure the accuracy of the analysis, and the obtained results were compared with the values in the literature and discussed. As a result of the comparison, it was seen that the values obtained were accurate. Later, the analysis was performed and discussed using the tsunami elevation data filtered from the tidal effect and QBlade. When the analysis results were examined, although no apparent change was observed in the aerodynamic and structural properties of the NREL 5 MW monopile offshore wind turbine due to the tsunami effect, significant changes were observed in its hydrodynamic properties. It was observed that the total Morrison forces in the x- and z-directions on the global axis significantly increased after the tsunami occurred, showing similar cyclic and spectral patterns where some shifts due to nonlinear interactions are expected. It was also observed that the hydrodynamic inertia force value on the x- and z-axes exhibited a similar effect after the tsunami–monopile interaction occurred, just like the total Morrison force. Our findings can be used to examine the effects of tsunami forces on the hydrodynamics and aerodynamics of offshore wind turbines, especially in the Aegean Sea. Also, they can shed light on developing devices to trace back the passage of the tsunamis from structural health monitoring data, which requires sensor optimization and health monitoring data analysis as part of possible future studies. A possible research direction is to examine the dynamics of offshore wind turbines under the effect of different atmospheric conditions involving steady and unsteady cases, and different tsunamis observed in the literature, which can have significantly larger wave heights, periods, and propagation speeds. Such analysis may be performed not only for the NREL 5 MW monopile offshore wind turbine, but other wind turbines used in the applications. In the future, we also aim to extend our findings to the prediction of offshore turbines’ structural parameters and develop measurement/early warning systems for tsunamis using some deep learning algorithms such as the long short-term memory (LSTM) algorithm.