bluuebunny/crossref_metadata_2025_split huggingface dataset:
Instantaneous mesh load factor (Kγ
) measurements in a wind turbine gearbox using fiber-optic strain sensors
Authors: Gutierrez-Santiago Unai , Keller Jonathan , Fernández-Sisón Alfredo , Polinder Henk , Van Wingerden Jan-Willem 
Published: June 2024

Abstract
The mesh load factor, Kγ
, describes how loads are shared between planet gears and has become one of the key design challenges in modern wind turbine gearboxes. Planet load sharing directly impacts tooth root stresses, a critical driver of torque density and gearbox reliability. Experimental evaluation of Kγ
is typically performed from sun gear tooth root strain gauge measurements, which are complex. Furthermore, such measurements can only provide an average value of load sharing. The present study describes an alternative method to evaluate the mesh load factor in wind turbine gearboxes based on fiber-optic strain sensors installed on the outer surface of the fixed ring gear. We present the results of an extensive measurement campaign to evaluate this novel sensing solution installed on the input planetary stage of a 2-MW wind turbine gearbox at the National Renewable Energy Laboratory’s Flatirons Campus (Colorado, USA). The number of strain sensors on the ring gear was selected as an integer multiple of the number of planets, which has enabled an instantaneous evaluation of the mesh load factor. The effect of operating conditions on the planet load-sharing behavior of the gearbox has been investigated. The mesh load factor measured for operating conditions close to rated was below 1.05, well below IEC 61400-4 standard requirements.
Applying motion compensation to offshore wind lidar reconstructed wind measurements
Authors: Benzo C , Delbos F , Yahiaoui S 
Published: June 2024

Abstract
Floating lidar systems present an effective and advantageous solution for offshore wind speed measurements, providing wind speed and direction data at multiple heights with easy deployment to provide widespread wind information around an area. One of the causes of apprehension, however, concerns buoy motion which induces overestimations of turbulence intensity and potentially imprecise measurements of horizontal wind speed. This research aims to reduce this uncertainty by applying motion compensation to three wind field reconstruction techniques (scalar, vector, and hybrid) to assess the amelioration on horizontal wind speed and turbulence intensity; especially how motion compensation can improve scalar and hybrid outputs. A three-month dataset of a floating lidar system (FLS) was compared to a nearby fixed lidar. The results demonstrate that motion compensation provides an improvement for horizontal wind speed measurement but inflates the overestimation of turbulence intensity from the floating lidar system. Though scalar reconstruction measurements provide slightly more accurate data compared to hybrid reconstructed measurements, motion compensation helps limit the bias disparity; ergo, applying motion compensation reduces the differences in bias for scalar and hybrid reconstructed measurements. This study results in two conclusions. Basic motion compensation provides a notable amelioration for horizontal wind speed FLS measurements, yet further research must be conducted to find a suitable method to improve turbulence intensity. Additionally, the scalar reconstruction method still slightly outperforms hybrid reconstruction in offshore measurement results, but motion compensation aids in limiting the differences between the two.
The lidar probe volume averaging effect: A wind tunnel investigation in streamwise turbulence with continuous-wave lidar
Authors: Uluocak Sinem , Theuer Frauke , Neuhaus Lars , Zúňiga Inestroza Manuel Alejandro , Hulsman Paul , Kühn Martin 
Published: June 2024

Abstract
The main limitation of lidars to capture the turbulence is the filtering of small-scale fluctuations within the probe volume, which is far less significant with conventional anemometers. In this study, the probe volume averaging effect on the streamwise turbulence statistics is investigated in the wind tunnel. Different turbulent flows, which exhibit distinct turbulence intensities and integral length scales are generated and subsequently captured using a short-range continuous-wave WindScanner with different probe volumes. Hot wire measurements are performed as a reference. The results indicate that the turbulence intensity (TI) is underestimated using conventional lidar methods compared to the hot wire measurements. The relative error increases with the increasing ratio of probe volume over integral length scale (l
p
/L) which is the indication of probe volume averaging. The TI is underestimated by 4 % at l
p
/L = 0.5 and by 63 % at the largest tested l
p
/L = 11.3 with the conventional lidar method. However, the TI estimated from the averaged Doppler spectrum of the lidar compensates for the probe volume averaging effect and shows a better agreement with the hot wire measurements with an average overestimation of 7.8 %. This study shows that the continuous-wave lidars have the potential to estimate the TI under different flow conditions using the averaged Doppler spectrum method.
Framework for Design Validation of Control Algorithms used on Mechanical Hardware-in-the-Loop Nacelle Test Rigs
Authors: Feindt Oliver , Siddiqui Muhammad Omer , Zuga Adam , Thomas Philipp 
Published: June 2024

Abstract
Full scale multi-MW Wind Energy Converter (WEC) nacelles including the mechanical and electrical components as well as the main and converter control systems, are tested at the Dynamic Nacelle Testing Laboratory (DyNaLab) at Fraunhofer IWES. A Hardware-in-the-Loop environment emulates the missing rotor and accurately applies torque to the nacelle via a motor and the test rig drivetrain. In a current nacelle test campaign, several structural changes have been made to reduce the necessary adaptor tolerances of the test rig interface and to include the nacelle hub. These changes can potentially impact the system’s dynamic response and controller performance. This paper presents the current research with a focus on improving the control algorithms for accurate application of the rotor torque by implementing a simulative validation framework. The objectives of this framework include addressing the impact of modifications to the test rig drivetrain, variations in the nacelle adaptor, and communication delays between real-time simulation models, the test rig, and the WEC controller prior to performing tests on the real system. The methodology shown therefore involves three steps: controller design using a simplified multi-mass torsional model of all components necessary for testing, validation with a high-fidelity virtual test bench model and testing the resulting controller performance during the commissioning phase for the actual test. Overall, this approach is expected to reduce the commissioning duration, enhance the performance of the test rig, and identify the limitations in achieving stable torque control before the application to the real wind turbine nacelle on the test rig.
Correlation of Blade Loading with SpinnerLidar-Measured Inflow
Authors: Herges Tommy , Houck Dan , Kelley Christopher 
Published: June 2024

Abstract
The Rotor Aerodynamics, Aeroelastics, and Wake (RAAW) project’s main objective was collecting data for validation of aerodynamic and aeroelastic codes for large, flexible rotors. These data come from scanning lidars of the inflow and wake, met tower, profiling lidar, blade deflection from photogrammetry, turbine SCADA data (including root bending loads), and hub-mounted SpinnerLidar inflow measurements. The goal of the present work is to analyze various methods to align the SpinnerLidar inflow data in time and space with individual blade loading. These methods would prove a way of analyzing turbine response while estimating the flowfield at each blade and provide a way of improving turbine response understanding using field data in real time, not just from simulations. The hub-mounted SpinnerLidar measures the inflow in the rotor frame meaning the locations of the blades relative to the measurement pattern do not change. The present work outlines some methods for correlating the SpinnerLidar inflow measurements with root bending loads in the rotor frame of reference accounting for both changes in wind speed and rotor speed from the measurement location one diameter upstream to each blade.
Introducing a partial bottom-up model for onshore wind turbine CAPEX estimation
Authors: Reichartz T , Jacobs G , Oertmann A , Blickwedel L , Schelenz R 
Published: June 2024

Abstract
European wind turbine manufacturers are under significant cost pressure. To minimize risk in investment and development decisions, it is crucial to identify cost drivers, especially given the high volatility of resource prices. This study presents a cost model that breaks down the component costs of onshore horizontal axis gearbox or direct drive wind turbines. Individual sub-models are developed for each component, using existing models where available. Production costs of steel towers, rotor blades and gearboxes are modeled, following a bottom-up approach. The calculated main investment costs for a 4.4 MW onshore wind turbine in 2023 are 1311 €/kW. These results are approximately 15 % higher than those of a previous study conducted in Germany in 2022. The increase is attributed to price developments, high inflation, and the fact that manufacturers have been selling turbines at a loss, thus underestimating turbine costs in the recent past. The model is a valuable tool for researchers, OEMs, and policy makers to analyze manufacturing and material costs. It facilitates informed decision-making about future research needs in the face of economic challenges.
Wind farm modelling of tilted rotors
Authors: Vimalakanthan Kisorthman , Bot Edwin , Engels Wouter 
Published: June 2024

Abstract
This study explores the benefits of tilted rotors in wind farms, focusing on a 3x3 grid of 10MW turbines and a 153-turbine farm modelled after the Hollandse-Kust West site with 15MW turbines. Computational Fluid Dynamics models ranging from mid to higher order, including FarmFlow (Parabolic RANS), TNO-VBM (RANS), and NREL-SOWFA (LES), were validated against CL-Windcon wind tunnel measurements.
Comparisons between low and high-order CFD models reveal good agreement, with LES indicating increased wake mixing. Tilted rotor simulations align well, except for the lower-order model, deviating at extreme tilt angles. Positive tilts in a 3x3 farm result in a 10% increase in sub-rated wind farm yield and a 26% reduction in peak thrust loads during post-rated conditions. However, for larger wind farm clusters, tilting the rotors can increase the production of some parts within while its overall production is not increased. The investigated results depend on the tested scenario, thus further exploration is recommended.
Using high sensitivity DC accelerometers for torque estimation on a wind turbine gearbox
Authors: Smeets V , Bosmans J , Gallas S , Kirchner M , Geens L , Ortmann S , Naets F 
Published: June 2024

Abstract
In this paper we propose a novel approach to estimate the torque on a wind turbine gearbox using single-axis high sensitivity DC accelerometers. The torque estimator uses an Augmented Extended Kalman Filter (AEKF), combining physics-based models with measurement data. The accelerometer sensor model is derived by analysing the measurements, leading to the identification of two torque-driven acceleration contributions: acceleration due to force excitation and acceleration due to a change in measurement direction. For the latter, two different sources, with distinct frequency content, are capable of changing the measurement direction. The first source corresponds to rigid body motion (f < 0.15Hz), the second one to ring gear deformation (0.15 < f < 4Hz). Using this information, the measured signal can be filtered to target specific acceleration contributions. The first torque estimation approach targets frequencies from 0.15 to 4Hz and produces a Normalised Mean Absolute Error (NMAE) of 2.12%. The second approach targets frequencies up to 0.15Hz, and will estimate the rigid body deflection angle. The torque is calculated through a linear identified relation between the rigid body angle and applied input torque. This approach yields an NMAE of 2.59%. This leads to the conclusion that high sensitivity DC accelerometers are a valid option for estimating torque on a wind turbine gearbox. These torque monitoring approaches will pave the way for advanced condition monitoring strategies and the calculation of remaining useful lifetime of the gearbox.
Simulation of a conventionally neutral boundary layer with two-equation URANS
Authors: Baungaard M , Van Der Laan M P , Kelly M , Hodgson E L 
Published: June 2024

Abstract
Simulating conventionally neutral boundary layers (CNBLs) with the unsteady Reynolds-Averaged Navier-Stokes (URANS) technique is investigated in this paper using a modified two-equation linear eddy viscosity turbulence model. For CNBLs over a flat and uniform surface, as typically used as the inflow to wind farm simulations, the governing equations of URANS can be solved with a one-dimensional solver, which makes the simulation of a typical CNBL five to six orders of magnitude faster than with large-eddy simulation (LES) approaches. However, URANS on the other hand requires more modelling than LES, and its accuracy is heavily dependent on the turbulence model employed. Through a cross-code study of a CNBL case with data from five different LES codes, it is found that the length-scale limiter of the employed turbulence model should be removed to correctly predict the atmospheric boundary layer (ABL) height evolution and the qualitative shape of various atmospheric profiles. A parametric study of simulations with varying initial ABL height further demonstrates the prediction capabilities of URANS, although a comparison with LES data shows that modelling of turbulence anisotropy and near-surface turbulence could be improved.
Feasibility analysis of a novel conical plain bearing with rotating segments as wind turbine main bearing
Authors: Euler J , Jacobs G , Zweiffel U , Jakobs T , Decker T , Röder J 
Published: June 2024

Abstract
Further expansion of wind energy is a key aspect for the transition towards renewable energy production. Operational expenditures constitute a significant portion of the cost of wind energy. One key aspect within these costs are maintenance costs. Main bearings of wind turbines suffer from comparably high failure rates. The exchange of a wind turbine main bearing is especially costly, as the rotor is dismounted and the drivetrain needs to be dismantled. Currently all commercially available wind turbine main bearings are roller bearings. One approach to reduce the operational costs is to develop segmented plain bearings as wind turbine main bearings. The segmented design allows for repair on tower without dismantling the drivetrain. In this work a novel, flexible plain bearing concept as wind turbine main bearing is presented. Key feature of this novel concept are its sliding segments that are mounted to the rotating main shaft. In contrast to designs which segments are mounted to the still standing housing, the rotatable shaft allows the segments to be rotated into intended positions for inspections or maintenance. In case of failure, faulty segments can be exchanged in a preferred service position, which provides easy access. The novel concept is evaluated using elasto-hydrodynamic-multi-body simulations and compared to the already established FlexPad concept.
Buckling behavior of rotor blade sandwich panels with spatially distributed material uncertainties
Authors: Prigge F , Balzani C 
Published: June 2024

Abstract
The study evaluates the impact of material uncertainties on the buckling behavior of sandwich panels in wind turbine rotor blades. The analysis is limited to linear buckling and is performed using stochastic finite element Monte Carlo simulation on a rectangular and flat submodel of the rotor blade’s trailing edge panel. The finite element model of the panels is simply supported on all edges. To generate the spatial material property distributions, the Karhunen-Loève expansion is used in combination with Latin hypercube sampling. The results compare the effects of various correlation lengths of the spatial distributions. The buckling loads vary in correlation to the average panel stiffness caused by the random distributions. The spatial distribution has a less dominant effect, reducing the mean value of the buckling load results. The amount of reduction in buckling load is highest when the correlation length of the distribution is close to the harmonic half-wave of the dominant buckling shape.
Federated Learning and Unlearning as Enablers of Wind Turbine Digital Twins
Authors: Stadtmann Florian , Rasheed Adil 
Published: June 2024

Abstract
Real-time capable models are paramount for the successful adaptation of digital twin technology into industries such as wind energy, but high-fidelity physics-based models cannot achieve the required speed, while data-driven and hybrid methods require large amounts of training data which is typically confidential. In this work, the combination of federated learning with hybrid modeling is proposed to train fast and reliable models across multiple confidential data sets owned by different stakeholders. The approach is demonstrated on physics-guided neural networks to estimate the lift and drag of wind turbine airfoils. A scenario is devised where multiple confidential data subsets are confined to different client devices. It is shown that the physics-guided neural networks can be trained through federated learning across those devices and data subsets and that the resulting models can recover and even surpass the accuracy of a model that is trained conventionally by merging the data subsets on a single device. The presented approach is highly scalable and can be easily adapted to many other applications. This work also discusses federated unlearning methods, which allow data owners to remove all traces of a data subset used in training if they decide to revoke their contribution.
Large-eddy simulation study on wave-wake interactions past an offshore wind turbine
Authors: Ciri Umberto 
Published: June 2024

Abstract
Large-eddy simulations (LES) of the flow past an offshore wind turbine under different underlying wave fields have been performed. A one-way coupling between the air and water flows has been realized through a hybrid immersed-boundary/level-set method. The velocity in the water domain is forced with the potential flow solution, while the response of the atmospheric boundary layer to the changes in the sea-surface height (tracked by the level-set equation) is simulated with a LES approach coupled to a rotating actuator disk model to mimic the effect of the wind turbine. A parametric study has been performed varying the wave period and wavelength while keeping the amplitude constant, resulting in different wave age parameters ranging from young developing waves to old swell waves. The wave field has a significant effect on the lower region of the atmospheric boundary layer, slowing down the wind field in proximity of the air-water interface and considerably increasing the local turbulence kinetic energy (TKE). The interaction between the wave evolution and the TKE results in a non-monotonic trend of the wake recovery rate with the wave age, when compared to the baseline value in the wake of a turbine over a flat wall. Both developed waves results in a lower recovery rate, whereas intermediate-age waves present a larger value than the baseline. The increased TKE in the lower layers of the rotor revolution induces an increased fluctuating component in the power production and blade loads. Nevertheless, for the parameters considered in this study, the spectra of the blade loads do not show a clear signature at the wave frequency, but the increased fluctuating component occurs over a broad range of frequencies.
Effects on the resolution of the near-wake by the use of different meshes using RANS and URANS
Authors: Aa Madsen M H , Zahle F , Sørensen N N , Bottasso C L 
Published: June 2024

Abstract
This work compares the wake resolution for several meshes in order to find an accurate yet computationally efficient grid. The mesh is identified through a parametric study where the wake resolution is gradually increased using up to 55 million cells. The mesh is designed in order to support CFD-based shape design, considering not only the wind turbine power but also an improved wake recovery. Furthermore, a comparison between steady-state and transient RANS formulations is presented. The proposed meshing should allow for extending a recently published CFD-based shape design focusing on wind turbine power, to also include wake behavior in an optimization context.
SEAHOWL: Partitioned Multiphysics and Multifidelity Modelling of Wind Turbines with Monolithically Coupled Elastodynamics
Authors: De Lataillade Tristan , Yu Wenchao , Pallud Maxime , Capaldo Matteo 
Published: June 2024

Abstract
We introduce SEAHOWL (Servo-Elasto-Aero-Hydro Offshore Wind Lab), a novel multiphysics multifidelity simulation framework for large-scale onshore, offshore, and floating wind turbines. For structural dynamics, multibody and finite element problems are coupled monolithically and solved within a single system of equations through Project Chrono, providing high numerical stability and optimal coupling accuracy. Combined with partitioned multiphysics, modularity is at the heart of the framework with various numerical methods and solvers (internal or external) available for each physics. This flexibility allows for the selection a target trade-off between numerical accuracy and computational efficiency on a use-case basis. Simulations showcased here have been selected through the prism of industrial R&D challenges, covering: controller response and loads over the operational wind range, 3P effect for different levels of fidelity for the blades, floating wind turbine response under irregular waves and turbulent wind, and innovative multibody application for 3P fatigue mitigation. SEAHOWL is cross-validated against the reference OpenFAST whole-turbine simulator from NREL, showing overall good agreement while differences between the two frameworks are highlighted.
Opensource machine learning metamodels for assessing blade performance impairment due to general leading edge degradation
Authors: Castorrini A. , Ortolani A. , Minisci E. , Campobasso M. S. 
Published: June 2024

Abstract
Blades leading edge erosion can significantly reduce annual energy production of wind turbines. Accurate estimates of the resulting blade performance impairment are paramount to predict the resulting energy losses and enable cost-informed decisions on optimal maintenance and operational strategies, maximizing energy production and reducing maintenance costs. Computational Fluid Dynamics (CFD) is a robust approach for predicting the performance losses due to LEE. However, the impact of the damage on blade aerodynamics varies depending on damage pattern, extent and location. Therefore, direct CFD simulation of a sufficiently general set of damaged blades is computationally not viable in industrial applications, since the energy loss assessment needs to be performed for hundreds of turbines at many times of the wind farm operation. To address this issue, previous studies showed how CFD can be used to train machine learning metamodels of the perfomance of damaged blade sections, enabling the definition of multi-fidelity energy loss prediction systems. This study presents improved metamodels, using validated CFD to generate training datasets that cover a more general and wider range of erosion patterns, from low-amplitude roughness to severe grooves. In order to provide the industry with additional erosion geometry-linked tools for estimating energy yield losses, and foster further research and development in this area, the developed meta-models have been made available online with unrestricted access.