bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detecting abnormal small-scale events by nacelle lidar at the AD8-180 prototype turbine
Authors: Meyer Paul Julian , Adorno Ramiro , Wegner Anna , Gottschall Julia 
Published: June 2024

Abstract
Identifying anomalous wind events that lead to high aerodynamic loads is essential for mitigating extreme loading on wind turbines. Building upon a recently published method, we herein introduce an extended methodology for early small-scale abnormal wind event detection employing a pulsed nacelle-lidar, potentially triggering preemptive control actions within the wind turbine system. The extended method integrates the consideration of multiple measurement ranges within the induction zone and the evaluation of a horizontally asymmetric wind detection parametrized through a difference in lidar line-of-sight (LoS) measurements. A comparative assessment of various detection algorithms is conducted, leading to the identification of optimal parameter configurations and an evaluation of their reliability. With the proposed methodology, the false positive rate can be reduced with respect to the original methodology, although not all extreme loading events are detected.
Dynamic wake conditions tailored by an active grid in the wind tunnel
Authors: Onnen D , Neuhaus L , Petrović V , Ribnitzky D , Kühn M 
Published: June 2024

Abstract
Well characterized test environments are required for novel wind turbine and wind farm control concepts. Aeroelastic simulations are mostly used to model turbine aerodynamic and structural response. For wind farm control, also the wake behaviour needs to be represented, including the impacts of dynamic wind direction changes, wake meandering and the interaction of wakes with the atmospheric boundary layer. This paper shows how wake-like inflow conditions can be emulated with an active grid in a wind tunnel, exciting a broad band of turbulent scales. The artificial wake conditions can be used as inflow for an exposed model turbine. A focus is put on the meandering dynamics, which are driven by large transversal turbulence patterns in the atmospheric boundary layer. Following the conjecture of the Dynamic Wake Meandering (DWM) model, such turbulent scales must have the size of multiple rotor diameters, to impact the entire wake deficit like a passive tracer. In conventional wind tunnel experiments, such spatial scale ratios are hard to reach, since wind tunnel sizes are bounded while the model turbines must be sufficiently large to have appropriate aerodynamic scaling and instrumentation. In this work, quasi-stochastic meandering trajectories are created, using scaled Ornstein-Uhlenbeck processes. Thus, the intrinsically stochastic process of wake meandering is made repeatable. The paper focuses at a thorough characterization of the inflow conditions with both lidar and hot-wire measurements, considering wake shape and spectral features. The results show an approximately axi-symmetric Gaussian deficit, which meanders as a coherent structure while having spectral features similar to a turbine wake.
Multiscale-simulation method for the wear behaviour of planetary journal bearings in wind turbine gearboxes
Authors: Decker Thomas , Jacobs Georg , Graeske Carsten , Röder Julian , Lucassen Mattheüs , Lehmann Benjamin 
Published: June 2024

Abstract
Wind energy is one of the most important renewable energy sources. To maintain competitiveness wind energy needs to be cost effective. Increasing the performance of wind turbines can help to reduce the total cost of wind energy. The power output can be increased by an increase in turbine rotor size since the power increases disproportionately with the rotor diameter. The increase in rotor size inherently comes with an increase in overall wind turbine size to cope with the increasing loads. Since the nacelle weight cannot be increased without limitation, e.g. due to the effect on the tower and costs, an increase in power density is necessary. The usage of journal bearings instead of rolling bearings for the application in planetary gearboxes in wind turbines is one way to increase the power density and reliability of the drivetrain. When designed and operated correctly, journal bearings have a longer service lifetime than rolling bearings. Wear simulations aid in the design of journal bearings. This work presents a simulation method for the wear prediction of planetary journal bearings in wind turbine gearboxes. The method is validated with measurements on a component test rig. The transfer to the wind turbine gearbox is shown by means of simulation.
Towards vortex-based wind turbine design using GPUs and wake accommodation
Authors: Blondel Frédéric , Joulin Pierre-Antoine , Guern Caroline Le 
Published: June 2024

Abstract
Vortex methods are often cited as a promising alternative to the classical Blade Element Momentum (BEM) theory for wind turbine design, overcoming some of its limitations such as imposing steady-state, uniform, and aligned inflows. BEM assumptions are being questioned, especially for large rotors with very flexible blades or even floating wind turbines. However, vortex methods are not yet widespread due to their computational costs. The following work demonstrates how free vortex wake methods using filament discretizations can become an affordable and viable alternative to BEM. This is achieved by combining filament number reduction as well as graphical processing units (GPUs) computations. The efficiency and accuracy of the proposed approaches are demonstrated against simple test cases, including an elliptical wing and a rigid horizontal axis wind turbine (HAWT). Finally, the approaches are applied to the aero-hydro-servo-elastic simulation of floating horizontal axis wind turbines.
Synthesis of realistic non-homogeneous non-Gaussian turbulent wind fields
Authors: Gallego-Castillo C , Elagamy M , Cuerva-Tejero A , Lopez-Garcia O , Avila S 
Published: June 2024

Abstract
This paper presents a sequential method for generating synthetic non-homogeneous non-Gaussian turbulent wind fields with a prescribed time-space covariance structure. The proposed methodology is based on the optimisation of restricted multivariate autoregressive (VAR) models, and the quantile-to-quantile transform between statistical distributions. The considered case study is a non-homogeneous non-Gaussian turbulent wind field over the roof of a high rise building simulated with LES. Results show a notably good matching in terms of the reproduced wind statistical distributions, Covariance Matrix Function (CMF) and Cross Power Spectral Density Matrix (CPSDM). In addition, the synthetic wind field reproduced accurately the recirculation bubble close to the roof. The main advantages of the proposed method are that, once the VAR model is computed, the synthesis of several realisations is computationally very cheap, which is useful for performing several aeroelastic simulations of the same analysis case, as suggested by the standards. The critical point is that, to characterise the statistical features for a specific case study (such as wind turbine wakes or turbulence due to obstacles), an LES simulation of the wind field is required as input. The software employed in this work is open source and it is available on GitHub.
Stabilization of SIMPLE-like RANS solvers for computing accurate gradients using the complex-step derivative method
Authors: Dicholkar A , Lønbæk K , Zahle F , Sørensen N N 
Published: June 2024

Abstract
The Reynolds-averaged Navier-Stokes (RANS) approach in Computational Fluid Dynamics (CFD) is increasingly vital for aerodynamic design across wind turbines, gas turbines, aircraft, and rotorcraft. Enhancing the process through CFD-based design optimization requires numerous design variables, favoring gradient-based methods for better scalability than gradient-free methods. This research uses numerical differentiation techniques, particularly the complex-step derivative method, to compute gradients. Challenges arise during aerodynamic shape optimization when unconventional shapes disrupt RANS solver assumptions, causing convergence failures. These failures undermine optimization, prompting the need to enhance solver convergence for robust optimization. The modified-Boostconv method is a residual recombination method bolstering unstable eigenvalues to stabilize convergence of iterative solvers for nonlinear systems of equations. This study extends the modified-Boostconv method to combine it with the complex-step derivative technique, creating robust optimizations via RANS-CFD with accurate gradients, even for these numerically unstable cases. The main issue encountered during the complexification of the modified-Boostconv method is how to correctly ensure that the model reduction leading to the least-squares problem satisfies the complex-step derivative method. We test whether the dot product operation involved in the model reduction should be a Hermitian or non-Hermitian inner product. The problem is first tested for a simple analytical case using the logistic equation in combination with the modified-Boostconv method. It shows that the non-Hermitian inner product should be used. This is also confirmed with a similar study using the RANS solver.
Investigation of Nonlinear Effects in the Tower Structure of Wind Turbines and Their Influence on System Behavior
Authors: Witter S , Schelenz R , Jacobs G 
Published: June 2024

Abstract
In multibody simulation (MBS) software, large structural components such as the tower are often modeled as flexible bodies using the Craig-Bampton method. While being very computationally efficient, nonlinear effects cannot be modelled in this way. The flange connections between the segments of tubular steel towers are one such source of nonlinearity. The magnitude of this nonlinearity increases with damages at the flanges as flange gaping becomes more common. The nonlinearities in the flanges lead to a changing stiffness and hence changing eigenfrequencies of the structure as a function of its deformation. In this paper, a nonlinear model of a tower with and without damages is being developed and validated based on an FEM model. The model is assembled from linear flexible bodies linked with nonlinear rotatory springs. The damages considered are broken bolts as well as axially symmetric angular flange gaps. It is shown that the MBS model closely emulates the FEM model including all nonlinear effects. The nonlinear tower model is incorporated into an existing MBS model of a commercial wind turbine in the 4 MW range. The eigenfrequencies of the full turbine model are being calculated using the build-in eigenvalue solver in Simpack. The results show a small but measurable decrease in eigenfrequencies compared to the linearized model, which scales with the extend of the damage.
Superelement-based acceleration of finite-element simulations of wind turbine rotors
Authors: Schleich F , Chen Z , Graßmann M , Balzani C , Stammler M 
Published: June 2024

Abstract
Large numbers of wind turbine rotor finite-element simulations are required for blade bearing raceway and ring fatigue calculations. Finite-element rotor models come along with a complex nonlinear model behaviour and a high number of degrees of freedom due to the necessity of considering the blade bearing’s surrounding structures. For that reason, accelerating such simulations is of particular interest for the iterative design process. This study focuses on different superelement configurations for the rotor model of the IWT 7.5-164 reference turbine. The blade bearing’s resulting contact forces and contact angles are analysed for 18 load steps throughout an exemplary rotor rotation and the respective model results are compared to each other. The results show that implementing superelements in the rotor model significantly increases the computational efficiency with an acceptable loss of accuracy in terms of the blade bearing’s internal loads. Furthermore, it is shown that such models outperform the acceleration and especially accuracy achieved by the usage of a one-third rotor model.
Integrating COAWST and OpenFAST for wind turbine loading
Authors: Vemuri Adithya , Porchetta Sara , Munters Wim , Gebel Jakob , Nejad Amir , Helsen Jan , Van Beeck Jeroen 
Published: June 2024

Abstract
Modern research endeavors in wind energy have been increasingly focused on achieving accurate representations of wind turbine loading across diverse atmospheric conditions. Recent advancements in numerical weather prediction techniques make it possible to downscale weather conditions for operational use, underscoring the importance of including air-sea interactions using models such as the Coupled-Ocean-Atmosphere-Wave-Sediment Transport model to improve wind energy predictions. Nevertheless, challenges of high computational costs, the elusive ”gray zone” in simulations, and creating accurate wind turbine digital twins for predictive modeling remain.
The current research addresses this challenge by proposing a novel modeling framework integrating the COAWST model with the OpenFAST aeroelastic solver. The current research strives to bridge the gap between the different dynamic regimes involved under diverse atmospheric conditions to achieve real-world representative wind turbine loading. Therefore, a scaled wind turbine model is implemented in the OpenFAST aeroelastic solver. Further, this research tests and discusses the proposed model framework’s capabilities and limitations under extreme weather phenomena.
A multi-fidelity approach for wind farm simulations and comparison with field data
Authors: Yu W. , Euzenat F. , Maheshwari P. , Baiza Martinez L. A. , Eneau C. , Pallud M. 
Published: June 2024

Abstract
The prediction of energy production and structural loads within wind farms is of high interest for wind industries to optimize the wind farm design and control under a variety of atmospheric conditions. However, it is still a key challenge to predict them accurately and efficiently due to the complex interactions between wind turbines and turbulent flows. Nowadays, high-fidelity simulations using Reynolds-Averaged Navier-Stokes (RANS) or Large-Eddy Simulation (LES) coupled with actuator disk or actuator line method are widely developed and used in wind farm analysis, but it still needs a huge computational resource, especially in the application of a commercial wind farm with large number of turbines. In this context, a mid-fidelity simulation tool based on the Dynamics Wake Meandering (DWM) model called FAST.Farm has been developed by National Renewable Energy Laboratory (NREL) in order to tackle this challenge. It allows to capture essential physics at the turbine scale as well as at the farm scale in a computational efficient manner. This study focuses on the calibration of DWM model which is the key to minimize inaccuracies between mid-fidelity and high-fidelity simulations regarding key performance indicators, e.g. thrust and power production. The calibration is made for DTU10MW wind turbine and shows a good improvement in accuracy compared to default parameters. The calibrated DWM model is finally employed to forecast the power generation for two turbines within a reference wind farm. A good improvement on the prediction is also obtained thanks to the calibrated parameters.
Multi-fidelity actuator-line modelling of FOWT wakes
Authors: Firpo Agnese , Sanvito Andrea G , Persico Giacomo , Dossena Vincenzo , Schito Paolo , Zasso Alberto 
Published: June 2024

Abstract
Large Eddy Simulations (LES) are considered the proper tool for predicting the physics of a wind turbine wake, thereby establishing a solid foundation for investigating the interaction among floating turbines within wind farms. In this work the Actuator Line Model, implemented in the OpenFoam environment, is combined with both U-RANS and LES simulations to underline the differences in accuracy when reproducing the near and far wake of a single turbine. Both a fixed-bottom and a surge motion case are tested to highlight the wake phenomena strictly generated by the platform motion. The use of LES simulation becomes fundamental by virtue of its ability to accurately simulate turbulence and mixing with free-stream flow, hence, this research aims at advancing the knowledge of wake dynamics from multiple perspectives while ensuring reliability thanks to the use of the experimental wake data from the UNAFLOW test campaign on the scaled laboratory model of the DTU 10 MW. In the near wake, limited flow unsteadiness and similar mean velocity are predicted by the two models. In the far wake, instead, the LES approach estimates a strong rise of flow unsteadiness which, in case of surge motion, affects the mean velocity value making evident the difference between LES and RANS estimation.
A generalised implementation of eN
transition method for airfoils and wind turbine blades
Authors: Kassem Hassan , Theron Johannes Nicolaas , Höning Leo 
Published: June 2024

Abstract
Prediction of the boundary layer transition from laminar to turbulent is essential for accurately calculating the aerodynamic forces on airfoils. Yet, it is still a challenging task for most RANS turbulence models (Reynolds-averaged Navier–Stokes) which are build on a fundamental assumption that the flow is fully turbulent. Although there are some derivatives of RANS models that promise to predict transition, the classical eN
method still holds its place as strong alternative, especially at high Reynolds numbers. The eN
method is usually applied in conjunction with boundary-layer codes for flow over 2D airfoils. In wind energy applications of flow over thick airfoils, the high fidelity CFD models play a central role in the analysis and design workflow. This work is an attempt to couple eN
method with an unstructured CFD code, namely OpenFOAM. Most of the previous attempts to achieve this coupling was limited to structured CFD codes and often with boundary-layer codes as an intermediate layer in-between. The newly implemented framework is applied on 2D airfoil cases with Reynolds numbers between 3 and 12 million. The method is extended to also allow for simulations using the Multiple Reference Frame (MRF) approach; this enables the user to calculate laminar-turbulent transition for wind turbine blades in axial flow. The 2D results showed very good agreement with XFOIL and wind tunnel data for forces and transition line prediction. The transition prediction of a 3D single blade of the IEA15MW turbine showed a good agreement with sectionwise transition values. The implemented concept proves the abilities of unstructured CFD based models coupled with the eN
method to predict transition accurately without compromising the robustness of the numerical setup.
Validation of new and existing methods for time-domain simulations of turbulence and loads
Authors: Doubrawa P , Rybchuk A , Friedrich J , Zalkind D , Bortolotti P , Letizia S , Thedin R 
Published: June 2024

Abstract
We seek to obtain a second-by-second match between the simulated and measured structural loads of a utility-scale wind turbine. To obtain the one-to-one load simulations, we start with the furthest upstream component of the modeling chain: the turbulent inflow. We consider new and existing methods to generate constrained-turbulence flow fields. The new method is based on large-eddy simulations (LES) and machine learning (ML). The existing methods include Kaimal-based TurbSim and the superstatistical wind field model. The inflow measurements used to constrain these simulations are obtained with a nacelle-mounted scanning lidar. We compare the flow fields for the different inflow simulation approaches and validate their associated load predictions against measurements collected in the Rotor Aero-dynamics, Aeroelastics, and Wake (RAAW) field campaign. We find that the rotor-position control developed for this study is key in enabling the time match between measurements and simulations. When this control approach is used, the load simulation performance tracks with the inflow simulation fidelity, with LES+ML yielding errors ≤ 4% for the damage-equivalent loads of flapwise bending moment, and tower fore-aft bending moments.
Data-driven time series forecasting of offshore wind turbine loads
Authors: Muhammad Amri Hafiz Ghazali Bin , Marramiero Daniela , Singh Deepali , Van Wingerden Jan-Willem , Viré Axelle 
Published: June 2024

Abstract
Long Short-Term Memory Recurrent Neural Networks (LSTM) are used to build surrogate models to forecast time-series blade loads for both fixed and floating offshore wind turbines. In this paper, we train surrogate models on datasets generated with OpenFAST on the IEA-15MW-RWT under a range of metocean conditions. The aim of the surrogate models is to generate load forecasts inexpensively and accurately such that they can be used in a model predictive controller. Two cases are investigated with different model inputs: one with only measurements available to typical PI controllers and another one with additional wave elevation and deflection measurements (alongside the endogenous variable). The model performances are evaluated and compared. It was found that for the fixed turbine, the models predicted all three blade loads to a high degree of accuracy. The floating turbine surrogate models performed relatively worse, but edgewise and pitching moments are still reasonably accurate. The surrogate model forecasts the flapwise moment to a satisfactory accuracy only in 58% out of 400 test cases. The addition of wave elevation and blade deflection features did not significantly improve the prediction performance of the surrogate, demonstrating that just the information used by current PI controllers may be sufficient for forecasting blade loads.
Insights into the dynamic induction in FOWT surge motion using an actuator-line model
Authors: Sanvito Andrea G , Firpo Agnese , Schito Paolo , Dossena Vincenzo , Zasso Alberto , Persico Giacomo 
Published: June 2024

Abstract
This research investigates the impact of surge motion on Floating Offshore Wind Turbines (FOWTs) through dynamic inflow analyses using an in-house Actuator Line Model (ALM). The study explores surge reduced frequencies in the range from 1 to 10 to analyse the returning wake phenomenon occurring at blade passage frequency. The findings highlight the dampening effect of the rotor thrust and torque by 25% due to induction field inertia. Noteworthy observations include the filter-like effect on the span-wise induced velocity trends: with the frequency increment, the induction field is ’synchronised’ with the apparent wind and forces. The results of the analyses evidence the suitability of the induction parsed in the absolute reference frame to capture the induction field features, amplitude and phase shift, at increasing surge frequencies.