Finite element modeling optimization of wind turbine blades from an earthquake engineering perspective

2020 ◽  
Vol 222 ◽  
pp. 111105 ◽  
Author(s):  
Ahmer Ali ◽  
Raffaele De Risi ◽  
Anastasios Sextos
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Wind Turbine ◽  
Earthquake Engineering ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Element Modeling

Design and Optimization of Composite Offshore Wind Turbine Blades

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
M. Tarfaoui ◽  
O. R. Shah ◽  
M. Nachtane
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Skin Thickness ◽  
Wind Turbine Blades ◽  
Element Analysis

In order to obtain an optimal design of composite offshore wind turbine blade, take into account all the structural properties and the limiting conditions applied as close as possible to real cases. This work is divided into two stages: the aerodynamic design and the structural design. The optimal blade structural configuration was determined through a parametric study by using a finite element method. The skin thickness, thickness and width of the spar flange, and thickness, location, and length of the front and rear spar web were varied until design criteria were satisfied. The purpose of this article is to provide the designer with all the tools required to model and optimize the blades. The aerodynamic performance has been covered in this study using blade element momentum (BEM) method to calculate the loads applied to the turbine blade during service and extreme stormy conditions, and the finite element analysis was performed by using abaqus code to predict the most critical damage behavior and to apprehend and obtain knowledge of the complex structural behavior of wind turbine blades. The approach developed based on the nonlinear finite element analysis using mean values for the material properties and the failure criteria of Hashin to predict failure modes in large structures and to identify the sensitive zones.

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