Perturbation methods for the reliability analysis of wind-turbine blade failure due to flutter. Issue 156 (September 2016)

• Record Type: Journal Article
• Authors: Pourazarm, Pariya; Caracoglia, Luca; Lackner, Matthew; Modarres-Sadeghi, Yahya
• Is Part Of: Journal of wind engineering and industrial aerodynamics. Issue 156(2016)
• Page Start: 159
• Page End: 171
• Publication Date: 2016-09
• Subjects: Wind-pressure -- Periodicals; Buildings -- Aerodynamics -- Periodicals; Pression du vent -- Périodiques; Constructions -- Aérodynamique -- Périodiques; Buildings -- Aerodynamics; Wind-pressure; Periodicals
• DOI: 10.1016/j.jweia.2016.07.011
• Languages: English
• ISSNs: 0167-6105

Abstract

Abstract: A new reliability framework is proposed to study the influence of uncertainty in various system parameters on the onset of coupled-mode flutter for large wind turbine blades. This study is the first comprehensive example of application of reliability analysis to wind turbine blade instability, affected by various sources of uncertainty. The randomness in flow forces, through a random lift coefficient, and in the structural properties is investigated. The probability of flutter is estimated using a recursive search procedure and four reliability models: First Order Reliability Method (FORM), First Order Reliability Method including the effect of unsteadiness in the aeroelastic loads (FORM-C), Second Order Reliability Method (SORM) and Weighted Average Reliability Method (WARM). Flutter probabilities are compared against the results of Monte Carlo simulations. All methods provide accurate probability approximation in regions close to the mean value of the critical flutter speed and flutter frequency. Among the four methods, the WARM provides the closest approximation to the Monte Carlo simulations in all regions of the variables. It is shown that failure probabilities can be found through an iterative procedure, which could be converted to a simplified formula in future standards for the design of wind turbine blades. Highlights: A new reliability method for the onset of flutter in large wind turbine blades. The new method is called Weighted Average Reliability Method (WARM). WARM is more accurate than the existing reliability methods. The computing time is much lower with WARM compared with Monte Carlo.