scholarly journals Investigation and Validation of Numerical Models for Composite Wind Turbine Blades

2021 ◽  
Vol 9 (5) ◽  
pp. 525
Author(s):  
William Finnegan ◽  
Yadong Jiang ◽  
Nicolas Dumergue ◽  
Peter Davies ◽  
Jamie Goggins
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Natural Frequencies ◽  
Numerical Models ◽  
Experimental Testing ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Static Testing ◽  
Design Life ◽  
Design And Manufacture

As the world shifts to using renewable sources of energy, wind energy has been established as one of the leading forms of renewable energy. As the requirement for wind energy increases, so too does the size of the turbines themselves, where the latest turbines are 10 MW with a turbine diameter in excess of 190 m. The design and manufacture of the blades for these turbines will be critical if they are to last for the design life, where the accuracy of the numerical models used in the design process is paramount. Therefore, in this paper, three independent numerical models have been created using three available finite element method packages—ABAQUS, ANSYS, and CalculiX—and the results were compiled. Following this, the accuracy of the models has been evaluated and validated against the results from an experimental testing campaign. In order to complete the study, a 13 m full-scale wind turbine blade has been used, which has been subjected to static testing in both the edgewise and flapwise directions. The results from this testing campaign, along with the blade mass and natural frequencies, have been compared to the results from the independent numerical models. The differences in the models, along with other sources of error, have been discussed, which includes recommendations on the development of accurate numerical models.

Numerical models for robust shape optimization of wind turbine blades

2016 ◽  
Vol 87 ◽  
pp. 849-862 ◽  
Author(s):  
Damir Vučina ◽  
Ivo Marinić-Kragić ◽  
Zoran Milas
Keyword(s):  
Shape Optimization ◽  
Wind Turbine ◽  
Numerical Models ◽  
Turbine Blades ◽  
Wind Turbine Blades

Predictions of Structural Testing Characteristics for Wind Turbine Blades

2009 ◽  
Author(s):  
Michael Desmond ◽  
Darris White
Keyword(s):  
Wind Turbine ◽  
Fatigue Testing ◽  
Turbine Blades ◽  
Structural Testing ◽  
Wind Turbine Blades ◽  
Static Testing ◽  
Extreme Load ◽  
Design Loads ◽  
Certification Requirements ◽  
Blade Loads

Static and fatigue structural testing of wind turbine blades provides manufacturers with quantitative details in order to improve designs and meet certification requirements. Static testing entails applying extreme load cases through a combination of winches and weights to determine the ultimate strength of the blade while fatigue testing entails applying the operating design loads through forced hydraulics or resonant excitation systems over the life cycle of the blade to determine durability. Recently, considerable efforts have been put forth to characterize the reactions of wind turbine blades during structural testing in order to develop load and deflection predictions for the next generation of blade test facilities. Incorporating years of testing experience with historical test data from several wind turbine blades, curve fits were developed to extrapolate properties for blades up to one hundred meters in length. Furthermore, conservative assumptions were employed to account for blade variations due to inconsistent manufacturing processes. In short, this paper will outline the predictions of wind turbine blade loads and deflections during static and fatigue structural testing.

Seagull in Wind Turbine Airfoil Blade Design Application Bionic

2013 ◽  
Vol 380-384 ◽  
pp. 4336-4339
Author(s):  
Hua Xin ◽  
Chun Hua Zhang ◽  
Qing Guo Zhang ◽  
Ping Wang
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Simulation Analysis ◽  
Turbine Blades ◽  
Clean Energy ◽  
Aerodynamic Performance ◽  
Blade Design ◽  
Wind Turbine Blades ◽  
Bionic Blade ◽  
Turbine Blade Design

Wind energy is an inexhaustible, an inexhaustible source of renewable and clean energy. Present due to the energy crisis and environmental protection and other issues, the use of wind more and more world attention. The wind turbine is the best form of wind energy conversion. Wind turbine wind turbine blades to capture wind energy is the core component of the blade in a natural environment to run directly in contact with air, with seagulls wings generate lift conditions are similar, so the gull wings airfoil and excellent conformation, with wind turbine blade design designed by combining the bionic blades. Through numerical simulation analysis found bionic blade aerodynamic performance than the standard blade aerodynamic performance has improved.

scholarly journals Second-generation composites from recycled wind turbine blades

2019 ◽  
Author(s):  
Azadeh Tavousi Tabatabaei ◽  
Seyed Hossein Mamanpush
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Second Generation ◽  
Turbine Blades ◽  
Clean Energy ◽  
Wind Turbine Blades ◽  
Environmental Attributes ◽  
The Us ◽  
The World

The demand for wind and other forms of clean energy is increasing in the US and throughout the world. Wind energy is also expected to provide 14.9% of the global electricity demand by 2020. Under this scenario, a significant amount of wind turbine blades (WTBs) will continue to burden our current landfills until a viable recycling strategy is found. Repurposing or recycling of end- of-use wind turbine blade material will provide both economic and environmental attributes.

scholarly journals Physical De-Icing Techniques for Wind Turbine Blades

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6750
Author(s):  
Valery Okulov ◽  
Ivan Kabardin ◽  
Dmitry Mukhin ◽  
Konstantin Stepanov ◽  
Nastasia Okulova
Keyword(s):  
Energy Consumption ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Energy Resources ◽  
The Arctic ◽  
Wind Turbine Blades ◽  
Optimal Methods ◽  
Superhydrophobic Coatings

The review reflects physical solutions for de-icing, one of the main problems that impedes the efficient use of wind turbines for autonomous energy resources in cold regions. This topic is currently very relevant for ensuring the dynamic development of wind energy in the Arctic. The review discusses an effective anti-icing strategy for wind turbine blades, including various passive and active physical de-icing techniques using superhydrophobic coatings, thermal heaters, ultrasonic and vibration devices, operating control to determine the optimal methods and their combinations. After a brief description of the active methods, the energy consumption required for their realization is estimated. Passive methods do not involve extra costs, so the review focuses on the most promising solutions with superhydrophobic coatings. Among them, special attention is paid to plastic coatings with a lithographic method of applying micro and nanostructures. This review is of interest to researchers who develop new effective solutions for protection against icing, in particular, when choosing systems for protecting wind turbines.

Preliminary Design of Wind Turbine Blades for Manufacture Using Local Capabilities

2001 ◽  
Author(s):  
Sarim N. Al-Zubaidy ◽  
Jacqueline Bridge ◽  
Alwyn Johnson
Keyword(s):  
Energy Source ◽  
Growth Rate ◽  
Wind Energy ◽  
Wind Turbine ◽  
Fluid Dynamic ◽  
Turbine Blades ◽  
Design Procedure ◽  
Wind Turbine Blades ◽  
Horizontal Axis Wind Turbine ◽  
Average Deviation

Abstract In the past ten to fifteen years wind energy remerged on the world scene with a very healthy growth rate, it has outstripped photovoltaics (solar cells) as the world’s fastest growing energy source, with a growth rate in excess of 30 percent per annum. No longer just a “nice idea for the future” Wind energy is becoming a mainstream energy source for many countries. The proposed paper will present a procedure (using numerical methods) for the design and analysis of Horizontal Axis Wind Turbine (HAWT) rotors. To ascertain the accuracy and to determine where further improvements could be initiated; numerical findings were then compared with published experimental test data and the compression showed an average deviation of less than 3% and therefore the simplifying assumptions made for the prediction of fluid behavior over an airfoil section was justified. Once the approach was validated and standardised a comprehensive airfoil design was produced. A computational fluid dynamic code coupled with a simple numerical algorithm aided the inverse design procedure. The final design was well proportioned and was theoretically able to meet the stated objective function and satisfied all the imposed constraints (manufacturing and geometrical). The geometrical data was then generated in a form suitable for manufacture using manually and numerically controlled machines.

scholarly journals PSO-BP Neural Network-Based Strain Prediction of Wind Turbine Blades

Materials ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 1889 ◽  
Author(s):  
Xin Liu ◽  
Zheng Liu ◽  
Zhongwei Liang ◽  
Shun-Peng Zhu ◽  
José A. F. O. Correia ◽  
...  
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Full Scale ◽  
Wind Turbine Blade ◽  
Blade Design ◽  
Wind Turbine Blades ◽  
Static Testing ◽  
Bpnn Model

The full-scale static testing of wind turbine blades is an effective means to verify the accuracy and rationality of the blade design, and it is an indispensable part in the blade certification process. In the full-scale static experiments, the strain of the wind turbine blade is related to the applied loads, loading positions, stiffness, deflection, and other factors. At present, researches focus on the analysis of blade failure causes, blade load-bearing capacity, and parameter measurement methods in addition to the correlation analysis between the strain and the applied loads primarily. However, they neglect the loading positions and blade displacements. The correlation among the strain and applied loads, loading positions, displacements, etc. is nonlinear; besides that, the number of design variables is numerous, and thus the calculation and prediction of the blade strain are quite complicated and difficult using traditional numerical methods. Moreover, in full-scale static testing, the number of measuring points and strain gauges are limited, so the test data have insufficient significance to the calibration of the blade design. This paper has performed a study on the new strain prediction method by introducing intelligent algorithms. Back propagation neural network (BPNN) improved by Particle Swarm Optimization (PSO) has significant advantages in dealing with non-linear fitting and multi-input parameters. Models based on BPNN improved by PSO (PSO-BPNN) have better robustness and accuracy. Based on the advantages of the neural network in dealing with complex problems, a strain-predictive PSO-BPNN model for full-scale static experiment of a certain wind turbine blade was established. In addition, the strain values for the unmeasured points were predicted. The accuracy of the PSO-BPNN prediction model was verified by comparing with the BPNN model and the simulation test. Both the applicability and usability of strain-predictive neural network models were verified by comparing the prediction results with simulation outcomes. The comparison results show that PSO-BPNN can be utilized to predict the strain of unmeasured points of wind turbine blades during static testing, and this provides more data for characteristic structural parameters calculation.

scholarly journals Water Droplet Erosion of Wind Turbine Blades: Mechanics, Testing, Modeling and Future Perspectives

Materials ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 157 ◽  
Author(s):  
Mohamed Elhadi Ibrahim ◽  
Mamoun Medraj
Keyword(s):  
Wind Turbine ◽  
Water Droplet ◽  
Prediction Models ◽  
Experimental Testing ◽  
Turbine Blades ◽  
Leading Edge ◽  
Droplet Impact ◽  
Wind Turbine Blades ◽  
Water Droplet Erosion ◽  
Erosion Prediction

The problem of erosion due to water droplet impact has been a major concern for several industries for a very long time and it keeps reinventing itself wherever a component rotates or moves at high speed in a hydrometer environment. Recently, and as larger wind turbine blades are used, erosion of the leading edge due to rain droplets impact has become a serious issue. Leading-edge erosion causes a significant loss in aerodynamics efficiency of turbine blades leading to a considerable reduction in annual energy production. This paper reviews the topic of water droplet impact erosion as it emerges in wind turbine blades. A brief background on water droplet erosion and its industrial applications is first presented. Leading-edge erosion of wind turbine is briefly described in terms of materials involved and erosion conditions encountered in the blade. Emphases are then placed on the status quo of understanding the mechanics of water droplet erosion, experimental testing, and erosion prediction models. The main conclusions of this review are as follow. So far, experimental testing efforts have led to establishing a useful but incomplete understanding of the water droplet erosion phenomenon, the effect of different erosion parameters, and a general ranking of materials based on their ability to resist erosion. Techniques for experimentally measuring an objective erosion resistance (or erosion strength) of materials have, however, not yet been developed. In terms of modelling, speculations about the physical processes underlying water droplet erosion and consequently treating the problem from first principles have never reached a state of maturity. Efforts have, therefore, focused on formulating erosion prediction equations depending on a statistical analysis of large erosion tests data and often with a combination of presumed erosion mechanisms such as fatigue. Such prediction models have not reached the stage of generalization. Experimental testing and erosion prediction efforts need to be improved such that a coherent water droplet erosion theory can be established. The need for standardized testing and data representation practices as well as correlations between test data and real in-service erosion also remains urgent.

scholarly journals GA-BP Neural Network-Based Strain Prediction in Full-Scale Static Testing of Wind Turbine Blades

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1026 ◽  
Author(s):  
Zheng Liu ◽  
Xin Liu ◽  
Kan Wang ◽  
Zhongwei Liang ◽  
José A.F.O. Correia ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Back Propagation ◽  
Health Assessment ◽  
Prediction Method ◽  
Full Scale ◽  
Wind Turbine Blades ◽  
Static Test ◽  
Static Testing ◽  
Input Variables

This paper proposes a strain prediction method for wind turbine blades using genetic algorithm back propagation neural networks (GA-BPNNs) with applied loads, loading positions, and displacement as inputs, and the study can be used to provide more data for the wind turbine blades’ health assessment and life prediction. Among all parameters to be tested in full-scale static testing of wind turbine blades, strain is very important. The correlation between the blade strain and the applied loads, loading position, displacement, etc., is non-linear, and the number of input variables is too much, thus the calculation and prediction of the blade strain are very complex and difficult. Moreover, the number of measuring points on the blade is limited, so the full-scale blade static test cannot usually provide enough data and information for the improvement of the blade design. As a result of these concerns, this paper studies strain prediction methods for full-scale blade static testing by introducing GA-BPNN. The accuracy and usability of the GA-BPNN prediction model was verified by the comparison with BPNN model and the FEA results. The results show that BPNN can be effectively used to predict the strain of unmeasured points of wind turbine blades.

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