An FEM-based AI approach to model parameter identification for low vibration modes of wind turbine composite rotor blades. Issue 5 (2nd November 2017)

• Record Type: Journal Article
• Authors: Navadeh, N.; Goroshko, I. O.; Zhuk, Y. A.; Fallah, A. S.
• Is Part Of: Revue Européenne de mécanique numérique. Volume 26:Issue 5/6(2017)
• Page Start: 541
• Page End: 556
• Publication Date: 2017-11-02
• Subjects: Low-dimensional beam model -- AI -- optimisation algorithm -- vibration coupling -- flapwise vibration -- lead–lag mode; Engineering mathematics -- Periodicals; Mechanics -- Data processing -- Periodicals; Finite element method -- Periodicals; Mechanics -- Mathematical models -- Periodicals; Engineering -- Statistical methods -- Periodicals; 621.05
• DOI: 10.1080/17797179.2017.1382317
• Languages: English
• ISSNs: 1779-7179

Abstract

Abstract: An approach to construction of a beam-type simplified model of a horizontal axis wind turbine composite blade based on the finite element method is proposed. The model allows effective and accurate description of low vibration bending modes taking into account the effects of coupling between flapwise and lead–lag modes of vibration transpiring due to the non-uniform distribution of twist angle in the blade geometry along its length. The identification of model parameters is carried out on the basis of modal data obtained by more detailed finite element simulations and subsequent adoption of the 'DIRECT' optimisation algorithm. Stable identification results were obtained using absolute deviations in frequencies and in modal displacements in the objective function and additional a priori information (boundedness and monotony) on the solution properties.