1 / 16

Distribution of Defects in Wind Turbine Blades &

Distribution of Defects in Wind Turbine Blades & Reliability Assessment of Blades Containing Defects Authors: Henrik Stensgaard Toft, Aalborg University Kim Branner, Risø-DTU Peter Berring, Risø-DTU John Dalsgaard Sørensen, Aalborg University / Risø-DTU. Contents. Introduction

martha-sanford
Download Presentation

Distribution of Defects in Wind Turbine Blades &

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Distribution of Defects in Wind Turbine Blades • & • Reliability Assessment of Blades Containing Defects • Authors: • Henrik Stensgaard Toft, Aalborg University • Kim Branner, Risø-DTU • Peter Berring, Risø-DTU • John Dalsgaard Sørensen, Aalborg University / Risø-DTU

  2. Contents • Introduction • Distribution of Defects in Wind Turbine Blades • Influence of Delaminations and Reliability Assessment • Non Destructive Inspection • Conclusion • Future Work

  3. Introduction • Uncertainties in calculation of the load carrying capacity for wind • turbine blades. • Material properties • Physical uncertainty (Aleatory) • Statistical uncertainty (Epistemic) • Finite Element calculation • Model uncertainty (Epistemic) • Failure criteria • Model Uncertainty (Epistemic)

  4. Introduction • Uncertainties – captured by partial safety factors. • Local production defects are not taken into account ! • Quality control of the production process • Non Destructive Inspection (NDI) of the blades • Stochastic models for the distribution of defects. • The models are set up on an empirical basis and have not yet been • calibrated against observations from blade manufacturing and testing.

  5. Production Defects • Local production defects: • Delaminations Voids • Wrinkles Defects in glued joints • Matrix cracks • Influence parameters: • Type of defect • Size of defect • Position of defect • Delaminations: • Areas of poor or no bonding • between adjacent plies.

  6. Distribution of Defects – Model 1 • Defects are completely random distributed in the blade. • The blade can be considered as a 2-dimensional planar region A since • defects tend to occur in a layer or in the interface between two layers. • The number of defects in the region A follows a Poisson distribution • The distribution of defects is an independent random sample from a uniform distribution

  7. Distribution of Defects – Model 2 • Defects occur in clusters which are randomly distributed in the blade. • The “parent” defects follow model 1 • Each “parent” defect produces a number of “offsprings” following a Poisson distribution • The position of the “offspring” defects relative to their “parents” is independently and identically distributed according to a bivariate probability density function. (Normal distribution)

  8. Distribution of Defects Model 2 Random Cluster Distribution • Model 1 • Completely Random Distribution

  9. Load Carrying Capacity of Main Spar • Transverse strains in main spar – Failure defined according to: • Maximum Strain • First Ply Failure

  10. Production Defects – Delaminations • Size refers to percent of plate width • Through thickness position 20% * The value is estimated.

  11. Influence of Delaminations • Delamination at the most critical position in the main spar cap. • Size refers to percent of cap width. Influenced only by strength reduction in the transverse direction. Buckling stability increased by the aerodynamic shell.

  12. Reliability Assessment of Blades Containing Defects • Reliability of blade containing defects: • The limit state function cannot be used directly. • factor characteristic load can be increased before blade failure (characteristic material properties) Influence of specific defects introduced by reduction factor on the load carrying capacity.

  13. Reliability Assessment of Blades Containing Defects • Reliability of main spar with delamination at the most critical position. • Target reliability index in IEC 61400-1,  = 3.09, PF = 10-3 per year.

  14. Non Destructive Inspection Probability of Detection (PoD) • Updated probability of failure: • Defects are assumed perfect repaired. Delamination size without/with NDI

  15. Conclusion • Probabilistic models for the distribution of defects have been proposed and can be calibrated to observations. • Probability of failure increased by large delaminations. • (strength reduction in transverse direction is estimated) • Updating of PF by Non Destructive Inspection. • Future work • Quantify uncertainties in stochastic models for reliability. • Local defects influence on material properties in fatigue.

  16. Distribution of Defects in Wind Turbine Blades • & • Reliability Assessment of Blades Containing Defects • Authors: • Henrik Stensgaard Toft, Aalborg University • Kim Branner, Risø-DTU • Peter Berring, Risø-DTU • John Dalsgaard Sørensen, Aalborg University / Risø-DTU

More Related