Sensitivity Analysis of Load Application Methods for Shell Finite Element Models

  • Wilson Javier Veloz ParraEmail author
  • Younes Aoues
  • Didier Lemosse
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)


Wind turbine blades are subjected to wind pressure and inertial loads from their rotational velocity and acceleration, that depends on the external environment and the turbine control (start-up, normal energy production, shut down procedures, etc.). Several numerical tools are developed to compute the applied loads to the wind turbine blades. These numerical tools are generally based on multiphysics simulation (aeroelasticity, aerodynamics, turbulence, etc.) and multibody beam finite element model of the whole turbine. However, when we are interested in optimizing the structural blades, we need to use shell finite element models in the structural analysis. Thus, the loads estimated by using the beam element are transformed into a 3D distribution pressure loads for the shell element. Several Load Application Methods are developed in the literature. However, in the context of the structural reliability analysis and optimization of the wind turbine blades, the suitable method should be selected with respect to his sensitivity to uncertain input parameters. This study present, a sensitivity analysis of the output of two load application methods for shell finite element models, with respect to uncertain input parameters as loads and material properties. The Morris method is used to carry out a sensitivity analysis. Both load application methods are sensitive to the change of the thickness in the materials and have a greater effect than the distributed loads applied by section.


Load application Sensitivity analysis Morris method Shell finite element model 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Wilson Javier Veloz Parra
    • 1
    Email author
  • Younes Aoues
    • 1
  • Didier Lemosse
    • 1
  1. 1.Normandie Univ, INSA Rouen Normandie, LMNRouenFrance

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