A methodology of wind turbine blade design has been established with PROPID code, which is an aerodynamic blade design tool developed by UIUC. PROPID code can design and analyze a wind turbine blade in a steady state flow. The methodology of wind turbine blade design includes an initial blade concept design, airfoil selection, basic design, and detailed design steps. Inverse design and performance analysis of the 2.3 MW U113 wind turbine blade was performed to verify the wind turbine blade design methodology. The differences in calculated power between PROPID code and GH Bladed code are under 1.0% in all wind conditions. Both blade shape design and performance analysis results using PROPID code are accurate. The aerodynamic characteristics of a U113 blade were investigated by computational fluid dynamics. Separation flow was captured by a Reynolds-averaged Navier-Stokes steady flow simulation using ANSYS CFX code. The numerical aerodynamic analysis methodology was verified by comparing the analysis results through CFD with BEMT-based program GH Bladed code results. Therefore, the blade design methodology will be applied to develop a super-capacity 20 MW wind turbine blade in the future.

When a wind turbine is designed, the dynamic stability of the system as well as the dynamic characteristics of the main components such as blades, hub, main shaft and tower must be evaluated. In particular, the natural frequencies of a blade, as a main load-generating component, need to be measured and assessed by component level testing. In conventional practice, the natural frequencies of a blade are determined as the measured frequencies near the reference frequencies provided by FE analysis results. But the reference frequencies are also uncertain since designers have difficulty distinguishing the torsional mode shape among the analysis results due to the complexity of its mode shape. So, in conventional practice, the determination of a measured torsional frequency inevitably contains uncertainty. Therefore, a novel method to definitely determine the torsional frequencies from the experimental data itself is necessary. In this paper, a new methodology to measure the torsional frequency of a blade was studied from the perspective of a modal test procedure, data processing method and mode determination logic. Finally, the validity of the method that can measure torsional frequency without reference FE analysis results was verified by applying it to an actual large wind turbine blade

Conventionally, a monopile that has reached the end of its design life is required to be removed. While monopiles have been left on site due to economic and technical reasons, cases of decommissioning monopoles have recently been reported, and a decommissioning market is emerging. This paper introduces a new type of monopile with decreased pull-out resistance by prior lifting up of a wedge segment installed on the outer wall of the monopile; consequently, the monopile can be dismantled easily from the operation site. The study conducted several numerical investigations, using finite element analysis, of the effect of segment pull-out for the monopile. After pulling out several segment sizes in the numerical model represented by soil element deletion corresponding to the segment volumes, the pull-out forces were compared to those of the conventional monopile. The results showed that for a segment with a thickness of 5 cm and circumferential angle of 30°, the pull-out resistance of the proposed monopile was reduced by 32.5% relative to that of a conventional monopile. Also, the results indicated that an increase in the segment angle was a more effective way to reduce resistance than that of the thickness.

In this paper, a semi-supervised machine learning technique applied to actual field vibration data acquired from Jeju-do wind turbines for predictive diagnosis of abnormal conditions of offshore wind turbines is introduced. Semi-supervised machine learning, which combines un-supervised learning with supervised learning, can be used to perform anomaly detection in situations where sufficient fault data cannot be obtained. The signal processing results using the spectrogram of the original signal were shown, and external data were used to overcome the problem that disturbance reactions easily occurred due to the imbalance between the number of normal and abnormal data. Out of distribution (OOD), which uses external data, is a technology that is regarded as abnormal data that is unlikely to occur in reality, but we were able to use it by expanding it. By rearranging the distribution of data in this way, classification can be performed more robustly. Specifically, by observing the trends of the abnormal score and the change in the feature of the representation layer, continuous learning was performed through a mixture of existing and new data.

Although wind turbines have obtained type certification according to international standards and are released to the market, they cannot be regarded as design evaluations that consider site characteristics. Therefore, it is necessary to study the site-specific load analysis method based on the meteorological data measured at the candidate site. In this study, site-specific load calculation was performed based on the meteorological data from the Jeju Haengwon mast. Analysis results were compared and analyzed with the results calculated by IEC design Class (IIA). For the fatigue loads at the blade root and tower base, the site-specific condition was lower than the IEC IIA, but in the case of the ultimate load, the site-specific condition showed higher results in some design load cases (DLCs). Selecting a wind turbine suitable for a site through load evaluation considering site conditions can prevent the reduction of operation and maintenance (O&M) costs and the power loss caused by downtime. Finally, it is expected to contribute to the project's levelized cost of energy (LCOE) reduction.

This paper deals with the structural analysis of wind turbine blades considering the bi-modulus property of CFRP, known as a more economic and efficient material for very large blades. The bi-modulus property is an unique characteristic of CFRP that shows higher tensile modulus than compressive modulus. Due to this characteristic, it is needed to apply the bi-modulus property to the computational analysis of CFRP blades to achieve more accurate results. In this paper, a novel method is proposed to apply the bi-modulus property of CFRP in a numerical simulation. To demonstrate the bi-modulus effect in FE analysis, the actual bi-modulus of CFRP was measured and applied to the structural analysis of a wind turbine blade. Moreover, the effects of the proposed method were evaluated by comparing the analysis results with actual full-scale blade static test results. As a result, it was verified that the proposed method could appropriately simulate the bi-modulus during FE analysis. Moreover, the accuracy of blade structural analysis was improved in accordance with the application of the bi-modulus property.

This paper presents a rational methodology to calculate the bending moment distribution for fatigue tests of wind blades using the pairs of the strain gauges attached on the surfaces of wind blades. The methodology is based on the equation for the strains as functions of their positions and bending stiffness under the pure bending of the asymmetric cross section of a beam. The equation is used to simultaneously calculate flapwise and edgewise bending moment distribution of the wind blade brought by single or even dual axis fatigue tests. The appropriate position and selection scheme of strain gauges on a blade section were proposed through the observation of the strains on blade surfaces simulated with the finite element analysis for the full 3D shell model of a 100m-length-grade wind blade. The blade bending moment distribution calculated from the strains using the proposed methodology has shown to have very small dependency on the gauge positions and selections of the gauge pairs.

This study performed a numerical analysis on the effect of platform shape and damaged mooring lines on the movement of the semi-submersible floating offshore wind turbines (FOWT). The NREL 5 MW-OC4-DeepCwind semi-submersible wind turbine was selected as the reference model. In order to find the effect of the semi-submersible floating platform shape, the dynamic movement and feasibility of three different models were observed with and without the presence of turbine blades. In addition, extreme conditions were considered by having one of the mooring lines detached to determine the effects on the FOWT. As a result, the remaining mooring lines deviated to change the surge and sway motion, which could cause a collision with nearby marine structures, and the variation of yaw angle might lead to critical accidents such as rollover. Since the response of the floating platform after receiving mooring line damage may vary depending on the mooring pattern, the location of the mooring damage, and the direction of the wind and waves, detailed simulations showed substantial variation of damage patterns.

A stabbing system is an underwater jointing structure for positioning the jacket substructure for offshore wind power on top of a pile foundation that is already installed in the seabed. In this paper, the structural safety of the stabbing system currently being developed in South Korea was evaluated through finite element analysis. For this study, conformity of the finite element modeling technique for a gripper (hydraulic cylinder) was reviewed, and the structural safety of the stabbing system was evaluated based on the stress safety factor under three design load combinations (combinations of vertical, shear, and moment loads). From the analysis, it was verified that the pile foundation and the stabbing system mounted on top of it are structurally safe according to the stress safety factor, and there will be no interference between major structural components (i.e., guide cone and pile foundation) due to rotation of the guide cone at the end of the jacket leg.