bluuebunny/crossref_metadata_2025_split huggingface dataset:
An open-source Python-based tool for Mann turbulence generation with constraints and non-Gaussian capabilities
Authors: Dimitrov Nikolay , Pedersen Mads , Hannesdóttir Ásta 
Published: June 2024

Abstract
This study presents Hipersim, an efficient, open-source, Python-based turbulence box generation tool. Hipersim combines Mann turbulence generation, application of constraints, and non-Gaussian turbulence generation, features that have not been available previously in a single package. The output of the tool is compatible with popular aeroelastic simulation tool formats (Hawc2 and TurbSim). Hipersim also has significantly better computational efficiency than earlier tools, as well as the possibility for parallelization. The source code is publicly accessible, and the tool is also available to install as a Python library. The present paper outlines the capabilities of Hipersim, explains some of the distinctive features of its implementation, and provides brief validation and comparison with similar tools.
Evaluation of turbulence characteristics in WRF simulations at WiValdi wind park
Authors: Kilroy Gerard , Englberger Antonia , Wrba Linus , Bührend Lukas , Wildmann Norman 
Published: June 2024

Abstract
In this work we evaluate WRF-LES simulations at the WiValdi wind park at Krummendeich, North Germany. To accurately resolve fine-scale turbulence, we employ a high-resolution nested innermost grid with 5 m horizontal grid spacing. The main aim is to accurately reproduce realistic turbulent characteristics observed in neutral and stable atmospheric boundary layers. The so-called cell-perturbation method to accelerate the development of fine-scale three-dimensional turbulence is tested, and results are compared to in-situ observations and to another highly idealized numerical model running in LES mode.
While WRF without additional modifications is capable of reproducing the mean wind fields at the WiValdi wind park, it is unable to reproduce the turbulent characteristics observed. With the cell-perturbation method included, results are significantly improved, with turbulent characteristics much closer to observations.
Examining relative impacts of atmospheric and oceanic factors on offshore wind farms
Authors: Williams H H , Aiyer A K , Deike L , Mueller M E 
Published: June 2024

Abstract
Accurate understanding and prediction of how ocean waves affect offshore wind farms are critical to their siting, design, and operation. This study presents a computational framework for simulating finite offshore wind farms using Large Eddy Simulation (LES) and a Dynamic Wave Spectrum Model (Dyn-WaSp). Implementation of the Dyn-WaSp with and without a correction for swell modes is compared to a static roughness (wave phase-averaged) model, which has a similar computational cost. Impacts of the different wave models on the wind’s mean velocity and turbulent kinetic energy profiles in the finite offshore wind farm are examined, and ideal available power at hub height is compared. The dynamic wave spectrum model is shown to predict lower mean velocities in comparison to the phase-averaged approach and predicts higher shear and turbulent kinetic energy, suggesting that loading on turbines is greater than would be estimated by a static roughness model.
Surge motion-induced dynamic inflow effects in floating offshore wind turbines: A State Prediction Model
Authors: Meng Qingshen , Yu Wei 
Published: June 2024

Abstract
The impact of surge motion on aerodynamic unsteadiness in modern floating offshore wind turbines (FOWT) is a well-recognized phenomenon. When coupled with advanced controllers integrated into these turbines, it can lead to fluctuations in power output. This paper introduces a state-space model that incorporates dynamic inflow effects resulting from surge motion and a PID pitch controller. Additionally, an observation equation is formulated to predict the system power output. Through time series validations, the proposed state-space model demonstrates its ability to accurately capture power responses influenced by surge motions. The developed model serves as a valuable tool for the comprehensive analysis of FOWT, allowing for the exploration of the intricate interplay between unsteady aerodynamics, advanced control mechanisms, and power output.
Applicability of a Simplified Model of a 15MW Wind Turbine for a Mooring Fatigue Study
Authors: Pergler P. , Potier G. , Barrier P. , Le Guennec S. , Capaldo M. , Féron M. 
Published: June 2024

Abstract
Mooring system of floating wind turbine design, as conditioned by fatigue analysis, requires time-consuming simulations. But to provide relevant solutions for the multiple coming tenders, efficient methodologies need to be developed to design quickly optimal floating platform mooring for specific metocean data and project constraints. This paper presents a comparison between a mooring fatigue assessment calculated with two standard detailed modelling of a 15MW wind turbine and a simplified Drag and Lift Model (DLM) based on global coefficients at hub often used in floating offshore wind preliminary analysis to carry out extreme analysis. The present contribution is here focused on the proper assessment of a quantitative error introduced by the simplified turbine model in the mooring fatigue assessment, and the evaluation of the missing contributions such as 3P excitation or low frequency induced by turbine control. Two different control approaches are assessed here to capture a range of coupled behaviour which have been observed on project. It has been shown that the DLM approach is accurate to carry out analysis under extreme conditions, but also gives relevant fatigue results for the most fatiguing lines. In general, the order of magnitude is consistent even for low damage. All the calculations have been made using DeepLines WindTM software.
CFD simulation of a multi-rotor system using diffuser augmented wind turbines by lattice Boltzmann method
Authors: Watanabe Seiya , Yoshikawa Masaki , Hu Changhong 
Published: June 2024

Abstract
A diffuser-augmented wind turbine (DAWT) achieves greater power generation efficiency by increasing wind speed through the diffuser. Nevertheless, scaling up this technology is difficult because of the considerable amount of wind drag on the diffusers. To overcome this difficulty, a multi-rotor system with two or more wind turbines on the same structure is one approach to increasing wind turbine power output. This research proposes a computational fluid dynamics (CFD) method to evaluate the hydrodynamic performance of a large-scale multi-rotor system of DAWTs. Compared to conventional wind turbines, CFD simulations of DAWTs necessitate higher computational costs because of the need of high-resolution meshes for the diffuser. Furthermore, the computational cost of a multi-rotor system increases with the number of rotors. To address the issue of high computational cost, we use the Lattice Boltzmann Method (LBM), which is well suited to large-scale CFD simulations. A wind turbine is modeled as an actuator line model and a diffuser as a wall boundary. An adaptive mesh refinement approach generates higher resolution meshes near the rotor and diffuser. LBM simulations were conducted for a single DAWT and a multi-rotor system with five DAWTs. The LBM results of the wake velocity and pressure distributions were in agreement with those obtained from wind tunnel experiments and general CFD methods in earlier studies. To investigate the diffuser gap effects, we simulated five DAWTs with diffuser gaps of 5%–25% of the diffuser diameter. The power gain of each DAWT was assessed. Great performance improvements were found with diffuser gaps of 20% and 25% of the diffuser diameter. On average, the five DAWTs achieved a power gain of more than 10%. These findings confirmed the accurate evaluation capability of the proposed CFD method for hydrodynamic characteristics of multi-rotor systems using DAWTs.
Impact of rotational direction on wake replenishment mechanisms of counter-rotating paired vertical-axis wind turbines
Authors: Talamalek Ayoub , Runacres Mark C. , De Troyer Tim 
Published: June 2024

Abstract
Recent studies have shown that the placement of paired vertical-axis wind turbines (VAWTs) in close proximity is a promising approach to design efficient VAWT farm layouts, mainly due to the increased power output. This study aims to experimentally investigate the impact of the rotational direction of paired counter-rotating VAWTs on their wake characteristics and replenishment mechanisms through a quantitative analysis using the momentum balance equation. The results of this study enhance our understanding of the effect of rotational direction on wake dynamics of counter-rotating paired VAWTs and offer valuable insights for optimising the design of VAWT farm configurations.
Lessons learned from 10 years of wind tunnel tests on small wind turbines designed by students
Authors: Schepers J.G. , Adema N.C. , Lipian M. , Kulak M. , Shahid A. , Best A. , Bendre T. , Gallicchio I. , Elsabbagh A. , Mostafa A. , Kim T. , Mikkelsen R. , Gaunaa M. , Teuwen J.J.E. , Rudolf R.T. , Wood D. , Holierhoek J.G. 
Published: June 2024

Abstract
This article discusses results from an international contest, open for university student teams (bachelor and master), involving the design, construction, and testing of small wind turbines in a large wind tunnel. The wind tunnel has an outlet of 2.85 x 2.85 m allowing a maximum rotor swept area of 2 m2 without significant tunnel effects. Both horizontal and vertical axis wind turbines are part of the competition. The turbines are evaluated by an external jury of industry experts based on criteria such as Annual Energy Production, cut-in wind speed, innovations, design, and sustainability. Although the contest has been initiated in 2013 with an educational focus, it has also evolved into a valuable database for scientific purposes by providing a decade worth of performance measurements for roughly 9-10 various turbine concepts each year. The collected data may serve as a unique validation resource for assessing the accuracy of design codes in modelling diverse turbine concepts thanks to detailed design reports with model descriptions accompanying each turbine (such turbine descriptions are often considered confidential for field measurements). The paper aims to explore the scientific value of this database by comparing calculations with measurements, offering explanations where possible, and reporting intriguing findings on unconventional concepts’ performance. Even though not all observations could be explained fully they provide food for thought. Recommendations are provided for both students to enhance their designs and for contest organizers to elevate the scientific value of the measurements in future contests.
Enhancing Power Output of Ducted Wind Turbines through Flow Control
Authors: Akhter M Z , Shaaban A , Marini A 
Published: June 2024

Abstract
This study focuses on the performance enhancement of a ducted small-scale National Renewable Energy Laboratory (NREL) Phase VI wind turbine, utilizing a Wind Lens diffuser. The investigation is conducted at the critical cut-in wind speed of 5 m/s. The research evaluates the integration of passive flow control devices, including Vortex Generators, Microtab, and Slot, strategically positioned across the Wind Lens to augment the mass flow through the rotor. The results indicate significant amplifications in the turbine output of up to 127%, attributable to airflow manipulation across the diffuser, resulting in increased torque and power output. The study highlights the effectiveness of employed flow control devices in managing turbulence and/or flow separation, thereby enhancing aerodynamics, particularly under low wind conditions. A comprehensive analysis of various parameters such as pressure and flow fields, turbulence, and other relevant metrics is conducted to ascertain their collective influence on rotor aerodynamics. The results demonstrate the potential of these passive flow control devices in advancing small-scale wind turbine technology, especially in regions with low wind potential. Moreover, the design simplicity and cost-effectiveness of these passive flow control devices suggest wider applicability in the renewable energy sector, contributing to the reduction of carbon-intensive energy reliance.
Investigation of the effect of free-stream turbulence on paired vertical-axis wind turbines using wind tunnel testing and an actuator-line model
Authors: Talamalek Ayoub , Damiola Luca , Runacres Mark C. , De Troyer Tim 
Published: June 2024

Abstract
The aerodynamic interaction of vertical-axis wind turbines (VAWTs) in paired configurations can be advantageous in wind farms. However, these turbines operate in the atmospheric boundary layer which is characterised by high turbulence and may also face high-turbulence levels associated with downstream wakes. Therefore, the main goal of this study is to explore the impact of turbulence intensity on the efficiency of paired VAWTs, employing a combination of wind tunnel experiments and an actuator-line model (ALM) integrated in a URANS-based OpenFOAM solver. The present ALM employs aerodynamic coefficients derived from experimental dynamic measurements conducted on a pitching aerofoil. The wind tunnel tests suggest that paired VAWTs operating in turbulent inflow can experience advantages arising from both the mutual aerodynamic interaction between them and the effect of turbulence on the aerodynamic conditions on their aerofoils. Additionally, the ALM sheds light on the mechanisms that contribute to the enhanced power output of isolated and paired VAWTs in turbulent inflow conditions.
Sensitivity analysis of parameters impacting the performance of an energy ship using airborne wind energy
Authors: Frommer Nicole , Cheng Po Wen 
Published: June 2024

Abstract
This study assesses the impact of different model parameters on the power performance of energy ship systems using point-mass models, focusing on two operational modes. The first mode involves a kite operating in a pumping mode with adjustable tether lengths, aided by additional propellers for ship propulsion. It utilizes a quasi-steady kite model coupled with ship motion’s drag force and velocity triangles. The second mode features a kite pulling the ship, while underwater hydraulic turbines harness energy from ship velocity. Derived from a sail-based model, calculations deploy the force balance equation in line with ship motion, considering the drag forces of the ship and hydraulic turbines, alongside the propulsive force resulting from the kite’s interaction with the ship. The investigated parameters influencing the power performance include kite surface, ship length, wind speed, the angle between the ship’s motion direction and wind direction, and, for the pumping mode, ship speed. The power production of the propulsion mode is generally lower, with differences of at least 72%, depending on the combination of considered parameters.
Design, Analysis, and Wind Tunnel Evaluation of Novel Fabric-Covered Rotor Blades in Wind Energy Generation
Authors: Jelili Fatma , Beyer Michael , Ritschel Uwe 
Published: June 2024

Abstract
This paper investigates the performance of a novel fabric-covered rotor blade. The study aims to address the need for cost-effective wind turbine blades by exploring the potential of textile-based materials. The research includes a comprehensive wind tunnel experiment to evaluate the aerodynamic response of the fabric-covered blade, compared to a traditional hard-shell blade. The experimental data are systematically processed and corrected for wind tunnel effects, providing valuable insights into the aerodynamic behavior of the novel blade. The results show that the fabric-covered blade, constructed from PTFE-coated fiberglass fabric, exhibits promising aerodynamic characteristics, with potential applications in reducing manufacturing expenses and enhancing power generation. The study concludes by proposing a novel control strategy leveraging the natural deformation of blades at high wind speeds, suggesting potential applications in limiting power output at high wind speeds. Overall, these findings contribute to the ongoing efforts in developing innovative and cost-efficient solutions for wind energy generation.
Impact of Blade Pitch Actuation System on Wind Turbine Cost and Energy Production
Authors: Pusch Manuel , Phadnis Mandar , Jeong Michael , Qin Chao , Loth Eric , Pao Lucy 
Published: June 2024

Abstract
To minimize the levelized cost of energy (LCOE) of wind turbines, advanced co-design strategies are required that also consider the contribution of active blade pitch control to overall energy production and wind turbine cost. Thereby, the demanded closed-loop performance drives the requirements on the blade pitch actuation system, which needs to be carefully balanced. To enable this, an extended LCOE measure is developed in this paper using stochastic estimates for quantifying pitch actuation cost in terms of pitch power and closed-loop performance in terms of net energy production. Additionally, the impact of blade pitch deflections on structural loads and hence cost is evaluated considering both collective and individual pitch control. The interdependencies between the different design objectives are revealed in a case study carried out on a 25MW wind turbine, demonstrating the guidance for engineers toward cost-effective and efficient wind turbine designs.
Conceptual Design of Offshore Jacket Substructures Using Machine Learning
Authors: Qian Han , Bartels Jan-Hauke , Marx Steffen 
Published: June 2024

Abstract
The offshore wind sector is mature and has led to standardized design methods for offshore substructures. The conceptual design phase is critical for efficiency and cost-effectiveness and forms the basis for further design iterations. As turbine capacity increases, so does the complexity of offshore substructures, making design more challenging. However, the design process still relies on the expertise of the design engineers. These engineers rely heavily on their experience and intuition when designing, which can lead to biases due to limited information. To address this problem, Machine Learning (ML) techniques offer a promising way to improve the accuracy and efficiency of the conceptual design of offshore substructures. The current study is limited to the conceptual design of jacket substructures and was conducted on a self-developed global dataset of real jackets. The ML-based approach proposed in this study is capable of learning from existing data, recognizing intricate relationships between design variables, and potentially providing more accurate estimates for the initial conceptual design of offshore jacket substructures.
Towards a general tool chain integration platform for multi-disciplinary analysis and optimization in wind energy
Authors: Feng Ju , Sørensen Jens Nørkær 
Published: June 2024

Abstract
To enable easier uptake and flexible usage for the wind energy community, a general tool chain integration platform for multi-disciplinary analysis and optimization, TopDesign, is proposed and developed. This work describes its concept and the initial implementation. The platform is written in Python and provided as an open source framework. The design of this platform puts emphasis on flexibility, usability and extensibility. General model classes with standard interfaces, which can wrap custom tools/models in different formats based on different programming languages, will be provided together with examples that are easy to understand and modify. Coupling tools/models into a system thus becomes an easy task of connecting models by inputs and outputs and defining workflow with a directed graph. To demonstrate the usage of the proposed platform, we implement a wind farm evaluation system by coupling the PyWake model, the FLORIS model and self-written constraint models in the platform and apply it in solving wind farm layout optimization problems with two algorithms, as implemented in an in-house optimization Python library. A case study for a wind farm composed of 9 turbines shows the potential of the proposed platform and methodology.
GNN-based surrogate modeling for collection systems costs
Authors: Souza De Alencar M , Göçmen T , Cutululis N A 
Published: June 2024

Abstract
There are no known polynomial-time algorithms to perform the cable layout optimization (CLO) for the electrical network within a wind power plant (WPP). This means the computational cost for solving the CLO problem grows exponentially with plant size, which often postpones its solution to until after most design decisions are made, thus forgoing some trade-offs that would be beneficial to the plant’s goal. This work presents a method to obtain a fast estimate of the CLO that can be performed at each iteration of the broader optimization framework. The proposed surrogate model comprises of a graph neural network (GNN) regression model, as this architecture resembles the graph nature of the CLO problem. The GNN is trained with a dataset of procedurally generated site instances that are optimized by costly solving an integer linear programming model. While the inference time for GNNs is constant, the features calculation proposed has time complexity O(N log N) (where N is the number of wind turbines). This still means a major speed up for problems of non-trivial size when compared to exact CLO. A simpler feed-forward neural network (FNN) was trained on the same dataset and used as baseline. Both GNN and FNN achieved r
2 scores of 0.997 for the regression on unseen data of actual WPP, with standard deviations of the relative errors of 1.59% for the FNN and 1.66% for the GNN. Although the GNN did not improve on the performance of the FNN, the latter is an original contribution to the state of the art and an useful tool for the integrated optimization of WPP. This work looked only into a sliver of what is possible with GNNs, leaving ample space for improvements in applying that architecture to the CLO problem.
Dynamic interaction of inflow and rotor time scales and impact on single turbine wake recovery
Authors: Andersen S J , Hodgson E L , Aa Madsen M H 
Published: June 2024

Abstract
The entrainment and recovery of wind turbine wakes are highly dependent on atmospheric inflow conditions, which has typically been quantified through the turbulent intensity. However, recent studies have shown that the integral time scales of the inflow has significant impact on the wake recovery. Concurrently, increased power production can also be achieved through intentionally introducing beneficial time scales by altering the control of the individual wind turbines. This study studies the combined impact of the dynamic interaction between dominant inflow and rotor time scales. The results show increased power production of a downstream wind turbine of more than 50% for the largest thrust coefficients and tip-speed ratios (TSR). However, the peak power gain occurs at different downstream positions indicating that combinations of inflow time scales and TSR = 6 result in faster near wake breakdown compared to the same inflow time scales combined with higher thrust coefficient of TSR = 8.