Fatigue assessment of a wind turbine blade when output from multiple aero-elastic simulators are available

被引:5
|
作者
Abdallah, Imad [1 ]
Tatsis, Konstantions [1 ]
Chatzi, Eleni [1 ]
机构
[1] Swiss Fed Inst Technol, Inst Struct Engn, Stefano Franscini Pl 5, CH-8093 Zurich, Switzerland
基金
欧洲研究理事会;
关键词
Wind turbine; Aeroelasticity; Uncertainty; Fatigue; Ensemble Aggregation; Data Fusion; Finite Elements; Machine Learning; LIKELIHOOD;
D O I
10.1016/j.proeng.2017.09.509
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Aero-elasticity is a term that refers to the interaction between the aerodynamic, inertial and elastic loads when a structure is exposed to fluid flow such as turbulent wind inflow. Various commercial and research-based simulators are available to compute the wind turbine aero-elastic loads. These aero-elastic simulators are of varying complexity and might bear different underlying assumptions, pertaining to physics, mathematical and computational formulations. However, currently established practice dictates that the adopted aero-elastic simulators are verified and validated on the basis of measurements from test wind turbines. As a result, it is generally hard to establish one simulator as superior to another in terms of their predicted output. The objective in this paper is to statistically aggregate the fatigue load on a wind turbine blade when simultaneous simulations are performed using multiple simulators. The simulators of the wind turbine blade are of varying fidelity, and uncertainty in the modelling and assumptions on the model inputs are implicitly included, and taken into account in the statistical analysis. The main concept followed here is that rather than treating the output of the simulators as individual information sources, we consider them as part of an ensemble, which can be clustered and then aggregated to predict the most likely fatigue load, hence reducing the inherent model-form uncertainty. (C) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:3170 / 3175
页数:6
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