Durability and Damage Tolerance Analysis Approaches for Wind Turbine Blade Trailing Edge Life Prediction: A Technical Review

The size of wind turbine blades is increasing rapidly, and they are being installed in remote offshore locations. Consequently, it is essential to focus on improving the design and maintenance procedures in the blade industry to meet the growing demand. Of particular concern is the long-term operational performance of the wind turbine blade trailing edge. In this paper, we discuss the application of durability and damage tolerance analysis (DADTA) approaches to trailing edge service life prediction. DADTA is mandated in the aerospace sector to support airworthiness certification and to provide an updated life prediction of the structure based on the different stages of their service life. The DADTA framework has two main parts: durability and damage tolerance analysis. The durability part uses a structural fatigue approach based on a damage accumulation method during the initial design phase to predict the lifespan of a structure without defects. On the other hand, the damage tolerance analysis part uses a fracture mechanics approach and a damage growth method to update the lifespan prediction of a structure during the operation stages. This is achieved by utilizing sensors and inspection data as inputs while the structure is in service. Both these methods are comprehensive and have merits; however, their broad adoption in the wind turbine blade industry is still lacking. The current paper provides an extensive review of these methods and shows how these can be applied to the wind turbine blade industry, specifically for predicting the structural design life of the trailing edge of composite wind turbine blades. The review includes (a) defining wind turbine trailing edge failure modes, (b) trailing edge design procedures, and (c) a detailed discussion of the application of durability and damage tolerance analysis for trailing edge life prediction. Overall, this review paper would be of special interest to blade designers and would guide researchers and engineers interested in life prediction methodologies based on DADTA approaches for wind turbine blades.