The Prediction of Fatigue Sensitivity to Void Content for 3D Reinforced Composites

Three dimensional fabrics have seen increasing use lately as composite reinforcements. Advantages over prepreg or chopped fiber processes can include cost, handling, consistent quality, impact behavior, and resistance to delamination [1]. To gain acceptance in the transportation industry it is imperative that properties including dynamic and fatigue behavior be designable. A Progressive Failure Analysis (PFA) was developed jointly by Alpha Star Corp and NASA to predict fatigue life of composites and determine their damage mechanisms so that the life could be extended. The title of this software package is GENOA^™, and it was used to focus on the three dimensional fabric called 3WEAVE^™ made by 3TEX, Inc. It was discovered through fatigue testing that void content greatly affected fatigue life for the 3D E-glass fabric reinforcing a polyurethane modified vinyl ester resin called Dion 9800 from Reichhold. This is a common characteristic for most structural materials. The challenge was to predict this behavior and characterize the accumulation of damage. First, the S-N curves for the neat resin and fiber reinforcement were “reverse engineered” to match the composite’s experimental fatigue life. Calculated S-N curves were then used to predict the fatigue life of the composite with two different void contents: 2% and 10%. The simulation accurately predicted the fatigue life for both scenarios and showed the higher void content decreased the fatigue life by a factor of 40. Additionally, the software demonstrated that the damage and failure mechanisms change depending on the void content. Virtual testing has the potential to decrease lead times in commercializing composite products by assisting in the design optimization and verifying product durability without having to resort to expensive rig and road durability testing.