Floating offshore wind (FOW) is a renewable energy source that is set to play an essential role in addressing climate change and the need for sustainable development. However, due to the increasing threat of climate emergency, more wind turbines are required to be deployed in deep water locations, further offshore. This presents heightened challenges for accessing the turbines and performing maintenance, leading to increased costs. Naturally, methods to reduce operational expenditure (OpEx) are highly desirable. One method that shows potential for reducing OpEx of FOW is LIDAR-assisted pitch control. This approach uses wind velocity measurements from a nacelle-mounted LIDAR to enable feedforward control of floating offshore wind turbines (FOWTs) and can result in reductions to the variations of structural loads. Results obtained from a previous study of combined feedforward collective and individual pitch control (FFCPC + FFIPC) are translated to OpEx reductions via reduced component failure rates for future FOW developments, namely, in locations awarded in the recent ScotWind leasing round. The results indicate that LIDAR-assisted pitch control may allow for an up to 5% reduction in OpEx, increasing to up to 11% with workability constraints included. The results varied across the three ScotWind sites considered, with sites furthest from shore reaping the greatest benefit from LIDAR-assisted control. This work highlights the potential savings and reduction in the overall levelised cost of energy for future offshore wind turbine projects deliverable through the implementation of LIDAR-assisted pitch control.

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Due to increasing environmental concerns and global energy demand, the development of Floating Offshore Wind Turbines (FOWTs) is on the rise. FOWTs offer a promising solution to expand wind farm deployment into deeper waters with abundant wind resources. However, their harsh operating conditions and lower maturity level compared to fixed structures pose significant engineering challenges, notably in the design phase. A critical challenge is the time-consuming hydromechanics analysis traditionally done using computationally intensive Computational Fluid Dynamics (CFD) models. In this study, we introduce Artificial Intelligence-based surrogate models using state-of-the-art Machine Learning algorithms. These surrogate models achieve CFD-level accuracy (within 3% difference) while dramatically reducing computational requirements from minutes to milliseconds. Specifically, we build a surrogate model for characterizing the hydrodynamic response of a floating spar-type offshore wind turbine (including added mass, radiation damping matrices, and hydrodynamic excitation) using computationally efficient shallow Machine Learning models, optimizing the trade-off between computational efficiency and accuracy, based on data generated by a cutting-edge potential-flow code.

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The global installed capacity of floating offshore wind turbines is projected to increase by at least 100 times over the next decades. Station-keeping of floating offshore renewable energy devices is achieved through the use of mooring systems. Mooring systems are exposed to a variety of environmental and operational conditions that cause corrosion, abrasion, and fatigue. Regular physical in-service inspections of mooring systems are the golden standard for monitoring their health status. This approach is often expensive, inefficient, and unsafe, and for this reason, researchers are focusing on developing tools for digital solutions for real-time monitoring. Floating offshore renewable energy devices are usually equipped with a wide range of sensors, some low-cost, low/zero maintenance, and easily deployable (e.g., accelerometers on the tower), contrary to others (e.g., direct tension mooring line measurements), producing real-time data streams. In this paper, we propose exploiting the data coming from the first type of sensors for mooring systems health status nowcasting. In particular, we will first rely on state-of-the-art supervised shallow and deep learning models for predicting the health status of the different sections of the mooring lines. Then, since these supervised models require types and amount of data that are seldom available, we will propose new shallow and deep weekly supervised models that require a very small amount of data regarding worn mooring lines. Results will show that these last models can potentially have practical applicability and impact for real-time monitoring of mooring systems in the near future. In order to support our statements, we will make use of data generated with a state-of-the-art digital twin of the mooring system, OrcaFlex, for a floating offshore wind turbine reproducing the physical mechanism of the mooring degradation under different loads and environmental conditions. Results will show errors around 1% in the simplest scenario and errors around 4% in the most challenging one, confirming the potentiality of the proposed approaches.

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Floating offshore wind turbines (FOWTs) are still in the pre-commercial stage and, although different concepts of FOWTs are being developed, cost is a main barrier to commercializing the FOWT system. This article aims to use a shape parameterization technique within a multidisciplinary design analysis and optimization framework to alter the shape of the FOWT platform with the objective of reducing cost. This cost reduction is then implemented in 30 MW and 60 MW floating offshore wind farms (FOWFs) designed based on the static pitch angle constraints (5 degrees, 7 degrees and 10 degrees) used within the optimization framework to estimate the reduction in the levelized cost of energy (LCOE) in comparison to a FOWT platform without any shape alteration–OC3 spar platform design. Key findings in this work show that an optimal shape alteration of the platform design that satisfies the design requirements, objectives and constraints set within the optimization framework contributes to significantly reducing the CAPEX cost and the LCOE in the floating wind farms considered. This is due to the reduction in the required platform mass for hydrostatic stability when the static pitch angle is increased. The FOWF designed with a 10 degree static pitch angle constraint provided the lowest LCOE value, while the FOWF designed with a 5 degree static pitch angle constraint provided the largest LCOE value, barring the FOWT designed with the OC3 dimension, which is considered to have no inclination.

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Floating offshore wind turbines are perceived as a techno-economically attractive solution due to their huge potential, however, their Levelised Cost of Energy (LCoE) has the potential to be further reduced, making it more competitive with current technology. The Multidisciplinary Design, Analysis, and Optimisation (MDAO) method is considered a promising way to reduce LCoE. The substructure is expected to accounts for around 35% of the capital cost hence optimisation frameworks have been applied to this area in numerous studies. A difficulty with this method is creating a flexible and robust framework which can model all platform types (i.e., waterplane, ballast, and mooring stabilised configurations), which, simultaneously, remains computationally affordable. In this work, a concept selection method to rank the platform types based on their suitability for a given site is provided. The approach allows a reduction of the design space for an MDAO approach, creating substantial computational time savings. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a Multi-Criteria Decision Analysis (MCDA) method which is used in this work to rank the platform types in order of relevance for a given site. This technique allows a decision to be made when there are conflicting parameters such as cost and performance. The parameters are prescribed a weighting value by the user, representing the importance based on their specific point of view. In order to determine which platform is appropriate for a specific site, a number of criteria were set related to the site’s water depth, tidal range, soil condition, and wave height. This determines which platform is most suitable based on the physical parameters related to the site. The ranking can be found by combining the weighting of each parameter, the criteria related to the site, and the physical characteristics of each site. In order to support our proposed method, a case study considering the recent Scotwind lease is performed, showing that the derived best solutions are largely in agreement with the platform types considered by the developers.@en

Floating Offshore Wind Turbines (FOWT) can harness the abundant wind resource in deep-water offshore conditions. However, they face challenges in harsh, unsheltered marine environments. The mean hydro- and aerodynamic loads coupled with fluctuating stochastic wind and wave loads contribute to varied failure mechanisms. Therefore, the serviceability, ultimate, and fatigue limit states are vital in ensuring the safety and reliability of FOWT. This paper investigates how specific loads and states drive the design of a spar-type support structure, utilising a computationally efficient frequency-domain model. This approach combines quasi-static aerodynamic and mooring models with a potential-theory-based radiation-diffraction solver. The serviceability criteria concern the platform and tower top displacements and accelerations. The ultimate and fatigue limit states are assessed for the tower base, the waterline section, and the mooring lines, including the effects of yielding under the bending moment and compressive axial load, column buckling, and tension-tension effects in the mooring lines. The full factorial design of experiments is employed to investigate the non-trivial relationships between the limit states and the various features of the support structure. The results demonstrate that the design of the spar platform above the waterline is mainly driven by fatigue, which results from significant dynamic tilt and increased stress concentration at the platform-tower intersection. On the other hand, the catenary mooring lines' design is mainly driven by the requirements of maximum offset (serviceability limit state) and fatigue.

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Floating Offshore Wind Turbines (FOWT) can be installed at the sites of the most abundant wind resource. However, the design uncertainties and risks must be reduced to make them economically competitive. The design and optimisation methodologies for FOWT support structures adopted up to date tend to follow a sequential analysis strategy. Since the FOWT system involves multiple distinct, highly coupled disciplines, its analysis and design are challenging. This paper presents an efficient implementation of a coupled model of dynamics in an optimisation process by applying a Multidisciplinary Design Analysis and Optimisation (MDAO) methodology. The coupling effects studied include the interdependence of the mean offset of the platform and the aerodynamic and mooring loads, as well as the velocity of the platform and the viscous damping. The trade-off between the solution accuracy and efficiency for the coupled and uncoupled models was quantified, and a range of iterative solvers were compared. The study showed that the coupling between the platform offset and the mooring and thrust loads has a significant influence on the values of the responses, converging at higher surge and pitch offsets, higher mooring loads, and at lower thrust. These non-conservative results demonstrated the criticality of the two-way coupling between the platform excursion and the mooring loads. Notably, the coupled solution was achieved at a relatively low increase in the total solution time (+16%), due to the high efficiency of Broyden's method.

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The deployment of offshore wind in the UK has seen a rapid increase in the past decade and will continue to increase with the securement of the recent Scotwind sites. Floating platforms will be utilised for 60% of these new sites, creating opportunities to try new platform typologies and further solidify the validity of existing concepts. Since there is no consensus on the platform typology, the cost will vary; however, it is predicted to be double the price of traditional fixed platforms. Finding the most optimal solution in terms of cost and performance is key to keeping cost low, allowing the technology to be more competitive. A technique which has been used in other industries is multi-objective optimisation, searching a large design space much more quickly than traditional methods. By carrying out a multi-objective approach, the optimal platform geometry can be identified over the Pareto Frontier, considering conflicting objectives such as cost and performance. The aim of this work is to review the existing literature on multi-objective optimisation of floating offshore wind (FOW) platforms, highlighting the gaps and shortfalls in the current literature. This review highlights the majority of work has been carried out for the 5 MW NREL turbine on a SPAR platform, utilising a genetic algorithm. Cost reduction has been noted as the main objective, however, the models found within the literature are simplistic, with a number of assumptions. The overall findings of this work highlight future work that could be improved: cost models, the inclusion of an energy production model linked to the platform motion, the requirement for analysis of larger turbines and the potential for a concept selection tool to reduce computational time.

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Floating Offshore Wind Turbines (FOWT) can harness the abundant offshore wind resource at reduced installation requirements. However, a further decrease in the development risks through higher confidence in the design and analysis methods is needed. The dynamic behaviour of FOWT systems is complex due to the strong interactions between the large translational and rotational motions and the diverse loads, which poses a challenge. While the methods to study the FOWT's general responses are well established, there are no methods to describe the highly complex time-dependent rotational motion patterns of FOWT. For a rigid body in general plane motion, an Instantaneous Centre of Rotation (ICR) can be identified as a point at which, at a given moment, the velocity is zero. However, it is common to assume a centre of rotation fixed in space and time, arbitrarily set at the centre of floatation or gravity. Identification of the ICR is crucial as it may lead to better motion reduction methods and can be leveraged to improve the designs. This includes better-informed fairlead placement and the reduction of aerodynamic load variability. In this paper, we propose a two-fold approach for the identification of the ICR: an analytical solution in the initial static equilibrium position, and a time-domain numerical approach for dynamic analysis in regular and irregular waves to understand the motion patterns and ICR sensitivity to environmental conditions. Results show that the ICR of FOWT depends on wave frequency and, at low frequencies, on wave height, due to the nonlinear viscous drag and mooring loads. An unexpected but interesting result is that the surge-heave-pitch coupling introduced by the mooring system leads to a dynamic phenomenon of signal distortion known as ”clipping” in the nonlinear audio signal processing area, which, through the introduction of higher harmonics, is responsible for the ICR sensitivity to motion amplitude.

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As new offshore wind development sites move further from shore and existing sites enter their post-subsidy operating period, it is expected that operational expenditure (OpEx) will increase. In order to overcome these challenges, a more flexible and cost-effective maintenance solution is needed. One such solution is opportunistic maintenance (OM). This work provides an overview of the maintenance strategy used within other industries before providing an in-depth review of the work specific to offshore wind. The existing literature fails to agree on the specific definition of the term. This work proposes an all-encompassing definition of the term, reviewing maintenance ‘opportunities’ and their corresponding ‘action/response’. The review found that maintenance opportunities are either internal or weather-based, with each opportunity having a pre-determined trigger/response. This work proposes the introduction of a market-based opportunity, which has not been previously considered. As offshore wind farms now face increasing curtailment and negative pricing threats, this new OM framework, OM+, view these periods as maintenance opportunities. OM+ also provides a new definition for recording and reporting availability — moving from time/energy-based availability to market-based availability.

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The drive for the cost reduction of floating offshore wind turbine (FOWT) systems to the levels of fixed bottom foundation turbine systems can be achieved with creative design and analysis techniques of the platform with free-form curves to save numerical simulation time and minimize the mass of steel (cost of steel) required for design. This study aims to compare four parametric free-form curves (cubic spline, B-spline, Non-Uniform Rational B-Spline and cubic Hermite spline) within a design and optimization framework using the pattern search gradient free optimization algorithm to explore and select an optimal design from the design space. The best performance free-form curve within the framework is determined using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The TOPSIS technique shows the B-spline curve as the best performing free-form curve based on the selection criteria, amongst which are design and analysis computational time, estimated mass of platform and local shape control properties. This study shows that free-form curves like B-spline can be used to expedite the design, analysis and optimization of floating platforms and potentially advance the technology beyond the current level of fixed bottom foundations.

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The development and deployment of offshore wind farms in the last decade have seen a dramatic increase, now totalling 743 GW globally (Global Wind Energy Council, 2022). This rapid increase is expected to further continue now with the potential to explore deeper sites with the adoption of floating offshore platforms. Proof of this growth has recently been seen with an impressive 60% of the 25 GW Scotwind leasing sites planning to install floating platforms in the next ten years (Crown estate, 2022 [1,2]). One main disadvantage of the advancement offshore is uncertainty and the potential increase in costs due to more complex structures and greater distances to shore. The cost increase for floating platforms is expected to be two to three times more expensive than traditional fixed support structures (Eric Paya, 2020). Thus, this work aims to review existing analytical cost models found within the literature to best determine their level of accuracy and compare the assumptions which have been made. Leading on from this review, a collection of all data found in the reviewed literature is presented, which leads to a data analysis that determines the variation across literature and the potential causes. Assessing this literature shows a wide range of model considerations, often leading to assumptions with little or no data to be validated against. Hence, high levels of variation and a lack of consensus on the cheapest floating platform were noted. All aspects of costs related to floating offshore wind systems vary heavily throughout the literature.

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As the installed capacity of individual turbines increases, so do costs associated with manufacture and maintenance. One proposed solution to this problem is the Multi-Rotor System (MRS) which utilises many small rotors to yield the same energy capture as a single large turbine. The operational advantage of the MRS is the built in redundancy between rotors on the same structure. However, despite this advantage, an increase in number of components is likely to result in an increase in transfers. This work examines the balance between additional crew and vessel requirements for such a structure against the expected savings in downtime due to redundancy and small rotor power rating. Three scenarios are analysed to determine the distribution of the failures which contribute to downtime. The study aims to find the optimal vessel fleet which limits downtime without drastically increasing direct operational expenditure (OpEx). As site size increases, the impact of global failures, which shut down the whole asset, is lessened. However, there is a significant increase in the number of vessels required to reduce downtime to <10% of the total OpEx. While a large fleet can offer significant downtime savings, there are practical limitations and challenges which must be acknowledged.

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The development of novel energy technologies to meet net zero carbon emission is essential in the provision of solutions to realize an increasing worldwide demand for renewable energy. Floating Offshore Wind Turbine (FOWT) is one of the emerging technologies to exploit the vast wind resources available in deep waters within the offshore wind sector. However, as a result of the complexity of a FOWT system, bringing FOWT technology up to speed requires a detailed understanding of the different disciplines within the system and the relationship between the FOWT system and the dynamics of the marine environment; hence, the need for Multidisciplinary Design Analysis and Optimization (MDAO) of the system. This paper reviews the MDAO of FOWT substructures/platforms proposed in the literature. This review covers an overview of floating offshore wind turbine substructures’ concepts, the design using geometric shape parameterization techniques and the analysis approaches (time and frequency domain) for response assessment of the FOWT system. It also provides a comprehensive review of MDAO frameworks for FOWT substructures. Regarding the optimization aspect, a review of some optimization algorithms used for floating offshore wind turbine substructure is provided, i.e., from the global search heuristic and meta-heuristics algorithms to the local search gradient-based optimization algorithms. This work further identifies the research gaps in MDAO for FOWT substructures. The main proposed future research areas to address these gaps are: increasing design space richness by adopting more advanced parametrization techniques to represent the platform geometry (and other characteristics), utilize surrogate/meta models to replace the most computationally expensive high-fidelity models needed for quick sensitivity studies before detailed analyses on selected models are conducted, and exploring the upscaling of the geometric design parameters of an optimal shape parameterized FOWT platforms derived from existing designs which can be coupled with new generation highly rated and heavier turbines.

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The upscaling of wind turbines results in fewer units per installed MW reducing infrastructure and maintenance costs of offshore wind farms. Multi rotor systems (MRS), comprising many wind turbine rotors on a single support structure, are potentially a means to maximize the upscaling benefit in achieving larger unit capacities than is feasible or economic with the conventional, 3-bladed horizontal axis wind turbine (HAWT). The MRS has an inherent upscaling advantage which, for a system with many rotors compared to a single rotor, reduces the total weight and cost of rotor-nacelle assemblies by a large factor. An innovative MRS design is presented based on vertical axis wind turbine (VAWT) rotors of the 2-bladed, H-type. Many disadvantages of VAWT design compared to HAWT in a single rotor system (reduced power performance and higher drive train torque, for example) are resolved in the MRS configuration. In addition, reduced component number and simpler components is advantageous for reliability and O&M cost. This MRS concept has many synergies arising from the choice of VAWT rotors. Results comprise a high-level evaluation of system characteristics and the first stage of more detailed investigation of aerodynamics of the high aspect ratio VAWT.

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As the UK takes a step towards a greener, cleaner future aiming to be net zero by 2050, continuous development of the power network is required. A clear solution is offshore wind, having already proved its feasibility and success in nearshore sites. However, a large majority of near shore sites in the UK are already being utilised. The next step is to move into deeper waters and utilise the stronger, more consistent wind resources. A solution could be floating offshore wind which is still in its infancy, with only a few operational floating wind farms installed. Building upon the multidisciplinary design, analysis, and optimisation framework (MDAO) for floating offshore wind turbines (FOWT) being developed at the University of Strathclyde, called FEDORA, the aim of this work is to refine the LCoE model adopted by FEDORA, and applying it to perform the optimisation of the floating offshore OC3 SPAR. There is limited data on cost, therefore Hywind Scotland Pilot Park will be used as a basis for the LCoE model, allowing the results to be validated. This model is not restricted to SPARs, as it establishes a general methodology to calculate the life cycle cost of floating offshore wind farms. Utilising the improved cost model this work finds four optimised SPAR structures for four different maximum angles of inclination which can be experienced in the wind turbines operation. The improved cost model has a much higher accuracy, highlighting the initial cost model underestimates the cost of the SPAR structure by around half.

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New wind turbine technologies and designs are being explored in order to reduce the cost of energy from offshore wind farms. Two potential routes to a lower cost of energy are the X- Rotor Concept (XRC) and Multi-Rotor System (MRS) turbines. A key cost saving for both Novel concepts included in this paper is operation and maintenance (O&M) costs savings. The major component replacement cost for conventional horizontal axis, XRC and MRS turbines are examined and the benefits of the concepts are provided in this paper. A review on existing decision support systems for offshore wind farm O&M planning is presented with a focus on how applicable these previous models are to novel turbine concepts, along with analysis of how the influential factors can be modified to effectively model XRC and MRS.

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This paper presents the key operations & maintenance (O&M) modelling inputs for fixed-bottom wind (FBW) and highlights the adaptations required for floating offshore wind (FOW) uses. The work also highlights major repair strategies such as tow to shore (T2S) and discusses the limitations and constraints which arise in an operational context. The technical and economic feasibility of such O&M strategies requires rethinking of weather risks and constraints, new vessel technologies and operational costs. The work also collates and reviews existing FBW models which have been adapted for FOW uses and analyses O&M inputs for a tow to shore operation. Findings show that there is ambiguity in literature for tug speeds and disconnection/reconnection times of the turbine system. A performed case study investigates the sensitives of both parameters through a weather window analysis of ScotWind sites. Recommendations for future practises, including additional O&M modelling considerations and inputs for FOW uses are given.

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Meeting climate and air quality targets, while preserving the focus on the reliability and cost-effectiveness of energy, became a central issue for offshore wind turbine engineers. Floating offshore wind turbines, which allow harnessing the large untapped wind resources in deep waters, are highly complex and coupled systems. Subsystem-level optimisations result in suboptimal designs, implying that an integrated design approach is important. Literature saw a few attempts on multidisciplinary design analysis and optimisation of floating wind turbines, with varying results, proving the need for an efficient, and sufficiently accurate, integrated approach. This paper reviews the state-of-the-art approaches to multidisciplinary design analysis and optimisation of floating support structures. The choice of the optimisation framework architecture, support platform design variables, constraints and objective functions are investigated. The techno-economic analysis models are closely examined, focusing on the approaches to achieving the optimum accuracy–efficiency balance. It is shown that the representation of the fully coupled system within the optimisation framework requires the introduction of a more complex multidisciplinary analysis workflow. Methods to increase the efficiency of such frameworks are indicated. Non-conventional support structure configurations can be conceived through the application of more advanced parametrisation schemes, which is feasible together with design space size reduction techniques. The set of design criteria should be extended by operation and maintenance cost, and power production metrics. The main technical limitations of the frameworks adopted so far include the inability to accurately analyse a diverse range of support structure topologies in multiple design load cases within a common framework. The cost approximation models should be extended by the chosen aspects of pre-operational phases, to better explore the benefits of the floating platforms.

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The development of novel energy technologies is considered imperative in the provision of solutions to meet an increasing global demand for clean energy. Floating Offshore Wind Turbine (FOWT) is one of the emerging technologies to exploit the vast wind resources available in deeper waters. To lower the levelized cost of energy (LCOE) or optimise the performance response associated with a FOWT system, a detailed understanding of the different disciplines (Aero-Hydro-Servo-Elastic) within the system and the relationship between the FOWT system and the dynamics of the marine environment is required. This requires an efficient Multidisciplinary Design, Analysis and Optimisation (MDAO) framework for FOWT systems to reduce the capital cost and increase dynamic performance. A key component of any MDAO framework is the shape parameterisation scheme, as it enables the modelling of a large array of platform designs with different geometric shapes using limited number of parameters. This work focuses on the B-Spline parameterisation modelling technique of OC3 spar-buoy and the use pattern search optimization algorithm to select the optimal design variants. The parametrisation technique is implemented in an analysis framework, where a B-spline library from Sesam GeniE is used to model each design representation, and a potential flow frequency domain analysis solver (HydroD/Wadam) is used for the hydrodynamic analysis. Validation of the selected designs within the design space is conducted with a benchmark NREL5MW spar-buoy hydrodynamic response results in literature with the hydrodynamic response of the frequency domain modelling approach using Sesam GeniE and HydroD/Wadam. This analysis process shows a high accuracy in response results between the OC3 spar-buoy in literature and the OC3 spar-buoy model design using B-Spline parametrization technique. Key performance metrics like the cost of materials and root mean square (RMS) of the nacelle acceleration also show improvement with the design variants compared to estimation from OC3 design in literature.

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