Isothermal Fatigue, Damage Accumulation, And Life Prediction Of A Woven Pmc

Isothermal Fatigue, Damage Accumulation, And Life Prediction Of A Woven Pmc
Categories: Computers, Monitor
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This dissertation focuses on the characterization of the fully reversed fatigue behavior exhibited by a carbon fiber/polyimide resin, woven laminate at room and elevated temperatures. Nondestructive video edge view microscopy and destructive sectioning techniques were used to study the microscopic damage mechanisms that evolved. The residual elastic stiffness was monitored and recorded throughout the fatigue life of the coupon. In addition, residual compressive strength tests were conducted on fatigue coupons with various degrees of damage as quantified by stiffness reduction. Experimental results indicated that the monotonic tensile properties were only minimally influenced by temperature, while the monotonic compressive and fully reversed fatigue properties displayed noticeable reductions due to the elevated temperature. The stiffness degradation, as a function of cycles, consisted of three stages; a short-lived high degradation period, a constant degradation rate segment composing the majority of the life, and a final stage demonstrating an increasing rate of degradation up to failure. Concerning the residual compressive strength tests at room and elevated temperatures, the elevated temperature coupons appeared much more sensitive to damage. At elevated temperatures, coupons experienced a much larger loss in compressive strength when compared to room temperature coupons with equivalent damage. The fatigue damage accumulation law proposed for the model incorporates a scalar representation for damage, but admits a multiaxial, anisotropic evolutionary law. The model predicts the current damage (as quantified by residual stiffness) and remnant life of a composite that has undergone a known load at temperature. The damage/life model is dependent on the applied multiaxial stress state as well as temperature. Comparisons between the model and data showed good predictive capabilities concerning stiffness degradation and cycles to failure.