Characterization and Modeling of the Effect of Environmental Degradation on Interlaminar Shear And Flexure Strength of Carbon/Epoxy Composites

摘要

A mechanism-based modeling methodology is being developed for prediction of long-term durability of composites for emerging facilities in different climatic zones. The objective of the research is to develop a predictive tool using the Arrhenius principles adapted to the TTS (Time Temperature Superposition) to measure degradation of carbon-fiber/epoxy composite under hygrothermal exposure and applied tensile stress. The hygrothermal conditions capture the synergistic effects of field exposure and extreme temperatures, viz., hot/dry, hot/wet, cold/dry, and cold/wet. Short term tests are performed to determine the Interlaminar Shear Strength (ILSS) and the Flexural Strength of environmentally aged composite specimens in accordance with ASTM D2344-84 and ASTM D7264 respectively. Unidirectional carbon/epoxy specimens were manufactured for short beam shear tests while specimens of [0_2/90_2]_(2s) configuration were manufactured for flexure tests using Vacuum Assisted Resin Transfer Molding (VARTM). A unique strain fixture has been designed to apply constant strain on the specimens during ageing and applies a simple methodology to eliminate excessive creep in the specimens.A two-dimensional cohesive layer constitutive model with a cubic traction-separation law is being developed in order to predict the life of the composite under the above mentioned conditions. Viscoelastic behavior of the cohesive material and the associated damage parameters are being incorporated in the model. The model simulates the test conditions and predicts the progressive failure mechanism of the specimen as observed in the tests, under various loading conditions. The model will also incorporate synergistic interactions between temperature, moisture and stress effects and predict degradation in strength as a function of different ageing conditions and ageing time. Model predictions will be benchmarked using test data.