Application of different damage modeling approaches for use with composite materials and composite material structures has grown with increasing computational ability. However, assumptions are often made for "worst case" scenarios with these modeling techniques In order to develop a tool that will allow for accurate analysis of a complete structure, modeling approaches must be optimized by including defects of different parameters. It was the optimization of these approaches that was investigated herein with specific application toward establishing a protocol to understand and quantify the effects of defects in composite wind turbine blades. A systematic, three-round study of increasing complexity was performed to understand the effects of three typical blade manufacturing defects while investigating continuum, discrete, and combined damage modeling. Through the three rounds of the benchmark material testing, significant coupon level testing was performed to generalize the effects of these defects. In addition, material properties and responses were analyzed and then utilized as material inputs and correlation criteria for each analytical technique. A standard defect case was initially used for each modeling technique and correlation was compared both qualitatively and quantitatively. While each modeling type offered certain attributes, a combined approach yielded the most accurate analytical/experimental correlation. Thus, a unique comparison of several different analytical approaches to composites with respect to manufacturing for consistency, accuracy, and predictive capability allowing for improved blade reliability and composite structural assessment.
NomenclatureBRC = Blade Reliability Collaborative MSUCG = Montana State University Composites Group BMT = Benchmark Material Testing OP = Out-of-plane wave IP = In-plane wave CDM = Continuum Damage Model DDM = Discrete Damage Model UMAT = User Material Subroutine σ = Stress ε = Strain u = Displacement