bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examination of Consistent Application of Interfacial Fracture Energy Versus Mode-Mixity Curve for Delamination Prediction
Authors: Samet David , Trilochan Rambhatla V. N. N. , Sitaraman Suresh K. 
Published: December 2019

AbstractExperimentally characterized critical interfacial fracture energy is often written as an explicit trigonometric function of mode-mixity and is used to determine whether an interfacial crack will propagate or not under given loading conditions for an application. A different approach to assess whether an interfacial crack will propagate is to employ a failure locus consisting of the critical fracture energies corresponding to different fracture modes, represented by an implicit formulation. Such a failure locus can be linear, elliptical, among other shapes. As it is nearly impossible to obtain isolated GIc or GIIc values through experimentation, extrapolations are used to determine these two extreme values based on intermediate experimental data. However, the magnitude of these extreme values as well as the shape of the two forms of failure curves are at risk of being inconsistent should proper care not be taken. An example of such an inconsistency would be to use a trigonometric formulation to obtain the extreme values through extrapolation and then employ those values in simulation through an elliptical failure. In this work, we have employed a series of commonly used interfacial fracture energy measurement techniques over a range of mode-mixities for a metal/polymer interface to demonstrate the potential discrepancy in the two approaches and to underscore the need for a consistent approach in evaluating interfacial crack propagation.
Biaxial Stress Relaxation of Vaginal Tissue in Pubertal Gilts
Authors: Pack Erica , Dubik Justin , Snyder William , Simon Alexander , Clark Sherrie , De Vita Raffaella 
Published: December 2019

Abstract
Pelvic organ prolapse (POP) is a condition characterized by displacement of the vagina from its normal anatomical position leading to symptoms such as incontinence, physical discomfort, and poor self-image. Conservative treatment has shown limited success and surgical procedures, including the use of mesh, often lead to severe complications. To improve the current treatment methods for prolapse, the viscoelastic properties of vaginal tissue need to be characterized. We determined the biaxial stress relaxation response of vaginal tissue isolated from healthy pubertal gilts. Square specimens (n = 20) with sides aligned along the longitudinal directions (LD) and circumferential direction (CD) of the vagina were biaxially displaced up to 5 N. The specimens were then kept at the displacements corresponding to 5 N for 20 min in both the LD and CD, and the corresponding strains were measured using digital image correlation (DIC). The stresses in the LD and CD were found to decrease by 49.91 ± 5.81% and 46.22 ± 5.54% after 20 min, respectively. The strain in the LD and CD increased slightly from 0.080 ± 0.054 to 0.091 ± 0.064 and 0.050 ± 0.039 to 0.058 ± 0.047, respectively, but these changes were not significant (p &gt; 0.01). By using the Peleg model, the initial decay rate and the asymptotic stress during stress relaxation were found to be significantly higher in the LD than in the CD (p≪0.001), suggesting higher stress relaxation in the LD. These findings may have implications for improving current surgical mesh, mechanical devices, and physical therapy used for prolapse treatment.
Investigating the Influence of MCP Uncertainties on the Energy Storage Capacity Requirements for Offshore Windfarms
Authors: Mifsud Michael D. , Farrugia Robert N. , Sant Tonio 
Published: December 2019

Abstract
Recent studies have shown that the intermittency of wind energy can be mitigated by means of an energy storage system (ESS). Energy can be stored during periods of low energy demand and high wind availability to then be utilised during periods of high energy demand. Measure-Correlate-Predict (MCP) methodologies are used to predict the wind speed and direction at a wind farm candidate site, hence enabling the estimation of the power output from the wind farm. Once energy storage is integrated with the wind farm, it is no longer only a matter of estimating the power output from the windfarm, but it is also important to model the behaviour of the ESS in conjunction with the energy demand. The latter is expected to depend, amongst other factors, on the reliability of the MCP methodology used.
This paper investigates how different MCP methodologies influence the projected time series behaviour and the capacity requirements of ESS systems coupled to offshore wind farms. The analysis is based on wind data captured by a LiDAR system installed at a coastal location and from the Meteorological Office at Malta International Airport in the Maltese Islands. Different MCP methodologies are used to generate wind speed and direction time series at a candidate offshore wind farm site for various array layouts. The latter are then used in WindPRO® to estimate the time series power production for each MCP methodology and wind farm layout. This is repeated with actual wind data, such that the percentage error in energy yield from each MCP methodology is quantified, and the more reliable methodology could be identified. While it is evident that the integration of storage will reduce the need for wind energy curtailment, the reliability of the MCP methodology used is found to be crucial for proper estimation of the behaviour of the ESS.
Research on Underwater Vehicle for Monitoring of Offshore Wind Generation Systems
Authors: Yamamoto Ikuo , Morinaga Akihiro , Lawn Murray 
Published: December 2019

Abstract
A compact low cost lightweight ROV (Remotely operated underwater vehicle) has been developed to assist in the monitoring of offshore wind generation systems. The ROV successfully dove 76 meters to check the condition of the spa to the base and associated moorings of a floating offshore wind generator (Goto, Nagasaki, Japan). An abundance of sea life was also observed around the base as the base provides a kind of artificial reef which fosters a marine ecosystem. The design philosophy of this ROV and overall system are described in this paper including the proposed addition of robotic arms.
Disparity Analysis for Three Floating Wind Turbine Aerodynamic Codes in Comparison
Authors: Sant Tonio , Micallef Daniel 
Published: December 2019

Abstract
This paper compares the predictions from three independent aerodynamic simulation tools modelling the time varying rotor thrust and shaft power of floating offshore wind turbines (FOWTs) under different sea wave conditions. These include a Blade-Element-Momentum (BEM) model, a Free-Wake Vortex model (FWM) and a Navier-Stokes based Actuator Disc (AD) model. The study is based on the NREL1 5 MW baseline FOWT installed on the OC4 DeepCWind semi-submersible platform. The rotor speed is maintained constant throughout the analysis, though different rotor tip speeds and sea wave heights and periods are considered. While the three aerodynamic models apply different approaches for modelling the wake, they are all based on a blade element theory (BET) approach for simulating the blade loads. A common set of static aerofoil data is used and corrections to the data for unsteady effects such as dynamic stall are ignored. Thus disparity between the predictions for the surging rotor is primarily due to the different numerical approaches used for modelling the FOWT wake. The time-averaged rotor thrust and power coefficients predicted by the three models were found to be in close agreement with one another at low tip speed ratios and the sea state was found to have marginal effect on these results. However, the disparity in such predictions between the three models was found to increase at high tip speed ratios, with the FWM and the AD models yielding the largest and smallest rotor thrust and power coefficients, respectively. Furthermore, the AD model was observed to exhibit the highest sensitivity to sea state, with a significant increase in the time averaged power coefficient being predicted at the most extreme wave condition.
The amplitudes in the thrust and power expressed as a percentage of the corresponding time-averaged values estimated by the three aerodynamic models were found to be in close agreement with one another for the optimal and high tip speed ratios. However, at low tip speed ratios, the BEM predictions were significantly smaller than those estimated by the FWM and AD models.
Numerical Modeling and Prediction of the Significant Parameters for Wind Monitoring
Authors: Radulescu Victorita 
Published: December 2019

Abstract
Romania has a high wind potential, representing more than 14,000 MW. After significant investments of over 5 billion euros made starting 2010, many wind farms were developed in regions with efficient potential, from the South-East part of the country. Nowadays, in January 2018, in Romania were registered 3025 MW produced by wind energy, representing around 30% of the total generated energy. To establish the efficient areas for future wind power plants a massive campaign of wind’s monitoring was developed, in the entire country. The paper presents a solution of the numerical modeling for the registered environmental data, significant atmospheric parameters. The complex realized database will allow future implementations of wind power plants. The data measured and stored refer at wind intensity and direction, pressure, temperature, humidity, solar radiation, and drew points, performed during four years with masts of height 70 m, situated at distance of 20 km each other. By numerical modeling is created a correlation and prediction of the measured data, plotted in correspondence to each elevation of the measuring stations. It was also analyzed the perturbations induced by the masts presence. Firstly, are mentioned some aspects referring to the masts installation, the solution adopted for a proper distribution through the analyzed area. The database elaboration was a challenge, due to the large amount of data recorded at intervals of 10 minutes (some parameters at 10 seconds) for a period of four years, for more than 12 parameters instantly. Besides these, there were stored and some other data referring at daily produced energy with some existent wind turbines. They will be considered as data input for future developments, with new generations of turbines, more efficient. It is created an original method to compact the database in order to use small amounts of computer memory. With the daily collected data was made and stored separately the average, maximum, and minimum wind velocity, for each day and month, from the measurements at time interval of 10 minutes. The relations between the values registered are within classification areas CL-4 and CL-8, allowing performing illustrations of over-prediction and under-prediction. The wind velocities under 4 m/s are stored in a separate folder because they are not useful in wind turbine functioning. These values are used only for estimation the future wind farms efficiency. The uncertainties are analyzed and are assessed the limits of errors, for the land classification CL-4. There are presented numerical results, some conclusions, and references.
Machine Learning-Aided Assessment of Wind Turbine Energy Losses due to Blade Leading Edge Damage
Authors: Cavazzini Anna , Minisci Edmondo , Campobasso M. Sergio 
Published: December 2019

Abstract
Estimating reliably and rapidly the losses of wind turbine annual energy production due to blade surface damage is essential for optimizing maintenance planning and, in the frequent case of leading edge erosion, assessing the need for protective coatings. These requirements prompted the development of the prototype system presented herein, using machine learning, wind turbine engineering codes and computational fluid dynamics to estimate wind turbine annual energy production losses due to blade leading edge damage. The power curve of a turbine with nominal or damaged blade surfaces is determined respectively with the open-source FAST and AeroDyn codes of the National Renewable Energy Laboratory, both using the blade element momentum theory for turbine aerodynamics. The loss prediction system is designed to map a given three-dimensional geometry of a damaged blade onto a damaged airfoil database, which, in this study, consists of 2700+ airfoil geometries, each analyzed with Navier-Stokes computational fluid dynamics over the working range of angles of attack. To avoid the need for lengthy aerodynamic analyses to assess losses due to damages monitored during turbine operation, the airfoil force data of a damaged turbine required by AeroDyn are rapidly obtained using a machine learning method trained using the pre-existing airfoil database. Presented results focus on the analysis of a utility-scale offshore wind turbine and demonstrate that realistic estimates of the annual energy production loss due to leading edge surface damage can be obtained in just a few seconds using a standard desktop computer, highlighting the viability and the industrial impact of this new technology for wind farm energy losses due to blade erosion.
Effect of Nacelle Drag on the Performance of a Floating Wind Turbine Platform
Authors: Son Daewoong , Louazel Pauline , Yu Bingbin 
Published: December 2019

Abstract
Wind forces acting on an offshore wind turbine are transferred to the bottom of the tower and consequently to the floating structure. Thus, drag forces acting on each component of the wind turbine such as the blades, the nacelle, and the tower must be accounted for properly in order to evaluate the performance of the supporting platform. In the aero-elastic wind turbine simulation tool FAST v.7, the nacelle drag component, however, has not been implemented, which means that only the drag forces on the tower and on the blades are represented. In this work, the front and side nacelle drag forces are modelled in FAST v.7 via different drag contributions. This paper will examine the behavior of a floating offshore semisubmersible platform, the WindFloat, for different Rotor-Nacelle-Assembly (RNA) yaw-misalignments with emphasis on the nacelle drag component.
Simulation of an Offshore Wind Turbine Using a Weakly-Compressible CFD Solver Coupled With a Blade Element Turbine Model
Authors: Elie Baptiste , Oger Guillaume , Le Touzé David 
Published: December 2019

Abstract
The present study addresses the first steps of development and validation of a coupled CFD-BE (Blade Element) simulation tool dedicated to offshore wind turbine farm modelling. The CFD part is performed using a weakly-compressible solver (WCCH). The turbine is taken into account using FAST (from NREL) and its effects are imposed into the fluid domain through an actuator line model. The first part of this paper is dedicated to the presentation of the WCCH solver and its coupling with the aero-elastic modules from FAST. In a second part, for validation purposes, comparisons between FAST and the WCCH-FAST coupling are presented and discussed. Finally, a discussion on the performances, advantages and limitations of the formulation proposed is provided.
Analysis of Environmental Conditions for the Conceptual Design of a 200 MW Floating Offshore Wind Farm in the East Sea, Korea
Authors: Shin Hyunkyoung , Yu Youngjae , Pham Thanh Dam , Ahn Hyeonjeong , Seo Byoungcheon , Kim Junbae 
Published: December 2019

Abstract
Due to global climate change, concern regarding the environment is greater than ever. Also, the energy industry is constantly developing and investing in new and renewable energy to reduce carbon emissions. Korea is planning to increase the proportion of renewable energy generation to 20% by 2030, in accordance with the 3020 renewable energy policy. This will involve 16.5 GW (34%) from wind energy, with a capacity from offshore wind energy of approximately 13 GW. Considering domestic technological wind resource potential (33.2 GW), it seems to be a sufficient target amount. However, in order to start the wind power generation business, the installation area must be analyzed for environmental information, for the evaluation of the wind resource and the early-stage concept design. Because it is difficult to conduct long-term measurements of the entire sea area, the environmental conditions are generally estimated from short-term measurement data and long-term reanalysis data. In this study, the environmental conditions of the East Sea of Korea were selected, and a comparative analysis was performed on the meteorological agency’s oceanic meteorology buoy data, ERA-5 reanalysis data obtained from ECMWF, and NASA’s MERRA-2 data. The extreme sea states of 50 years and 100 years were analyzed by extreme statistical analysis. Finally, environmental conditions required for the basic design of wind turbines were selected following IEC and DNV standards.
A Modified Free-Wake Vortex Ring Model for the Aerodynamics of Floating Offshore Wind Turbines
Authors: Dong Jing , Viré Axelle , Ferreira Simao , Li Zhangrui , van Bussel Gerard 
Published: December 2019

Abstract
A modified free-wake vortex ring model is proposed to compute the dynamics of a floating horizontal-axis wind turbine. The model is divided into two parts. The near wake model uses a blade bound vortex model and trailed vortex model, which is developed based on vortex filament method. By contrast, the far wake model is based on the vortex ring method. This is a good compromise between accuracy and computational cost. In this work, the model is used to assess the influence of floating platform motions on the performance of a horizontal-axis wind turbine rotor. The results are validated on the 5MW NREL rotor and compared with other vortex models for the same rotor subjected to different platform motions. It was found that the result from the proposed method are more reliable than the results from BEM theory especially at small angles of attack in the region of low wind speeds, on the one hand, and high wind speeds with blade pitch motions, on the other hand.
Design and Dynamic Analysis of a Compact 10 MW Medium Speed Gearbox for Offshore Wind Turbines
Authors: Wang Shuaishuai , R. Nejad Amir , Moan Torgeir 
Published: December 2019

Abstract
This paper presents the design of a compact gearbox for the DTU 10 MW reference offshore wind turbine. An innovative gearbox concept consisting of a fixed planetary stage with a differential compound epicyclic stage is proposed. Power splitting and compound epicyclic transmission technologies are employed, which could effectively reduce the gearbox’ size. Power transmission principle of the gearbox is described, and power distribution on two transfer paths is derived by the geometrical and mechanical relationships among the components. The gearbox is designed based on the design loads and criteria with reference to the relevant international standards, and all of the critical components, gears and bearings, are designed by performing fatigue limit state (FLS) check. A high fidelity drivetrain dynamic model, consisting of the compact gearbox and one four-point support drivetrain configuration, is established by means of multi-body system (MBS) approach. Then, validation of the power distribution is conducted by the comparison of the simulation results and design values. Resonance analysis of the drivetrain model is conducted by employing Campbell diagram, energy distribtuion of components and time domain simulation approach, and the results show that no resonance phenomenon appears in this drivetrain model during the normal operating conditions. In addition, load sharing performance of the MBS model is assessed, indicating the a favorable dynamic operating behavior of the gearbox. It is believed that such compact design could be good alternative for floating offshore wind turbines.
Experimental Validation of Angular Velocity Measurements for Wind Turbines Drivetrain Condition Monitoring
Authors: Moghadam Farid K. , R. Nejad Amir 
Published: December 2019

Abstract
Drivetrain bearings are seen as the most common reason of the wind turbine drivetrain system failures and the consequent downtimes. In this study, the angular velocity error function is used for the condition monitoring of the bearings and gears in the wind turbine drivetrain. This approach benefits from using the sensor data and the dedicated communication network which already exist in the turbine for performance monitoring purposes. Minor required modification includes an additional moderate sampling frequency encoder without any need of adding an extra condition monitoring system. The additional encoder is placed on the low speed shaft and can also be used as the backup for the high speed shaft encoder which is critical for turbine control purposes. A theory based on the variations of the energy of response around the defect frequency is suggested to detect abnormalities in the drivetrain operation. The proposed angular velocity based method is compared with the classical vibration-based detection approach based on axial/radial acceleration data, for the faults initiated by different types of excitation sources. The method is experimentally evaluated using the data obtained from the encoders and vibration sensors of an operational wind turbine.
Advanced Vibration Signal Processing Using Edge Computing to Monitor Wind Turbine Drivetrains
Authors: Peeters Cédric , Verstraeten Timothy , Nowé Ann , Daems Pieter-Jan , Helsen Jan 
Published: December 2019

Abstract
This paper illustrates an integrated monitoring approach for wind turbines exploiting this Industry 4.0 context. Our combined edge-cloud processing approach is documented. We show edge processing of vibration data captured on a wind turbine gearbox to extract diagnostic features. Focus is on statistical indicators. Real-life signals collected on an offshore turbine are used to illustrate the concept of local processing. The NVIDIA Jet-son platform serves as edge computation medium. Furthermore, we show an integrated failure detection and fault severity assessment at the cloud level. Health assessment and fault localization combines state-of-the-art vibration signal processing on high frequency data (10kHz and higher) with machine learning models to allow anomaly detection for each processing pipeline. Again this is illustrated using data from an offshore wind farm. Additionally, the fact that data of similar wind turbines in the farm is collected allows for exploiting system similarity over the fleet.