A fibre stress-based parameter for thermomechanical fatigue life predictions of titanium matrix composites

被引:0
|
作者
Johnson, WS [1 ]
Calcaterra, JR
机构
[1] Georgia Inst Technol, Sch Mat Sci & Engn, Atlanta, GA 30332 USA
[2] USAF, Res Lab, VAVS, Wright Patterson AFB, OH 45433 USA
关键词
titanium; metal matrix composite; thermomechanical fatigue; life prediction; elevated temperature;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Titanium Matrix Composites (TMCs) are envisioned for use in the next generation of advanced aircraft and their engines. To ensure a smooth transition to industry, fatigue life prediction methodologies, which can account for random variations in mechanical and thermal loads, must be developed. To facilitate the development of such a model, fatigue testing has been conducted at Georgia Tech. on [0/+/-45/90](s) and [90/+/-45/0](s) laminates of SCS-6/Timetal 21S. The tests were done at temperatures of 400, 500 and 650 degrees C, with hold times of 1, 10 and 100 s superimposed at the maximum stress. The purpose of the tests was to separate the effect of time-dependent deformation from the effect of environmental degradation. Using the results of these tests, and results generated at NASA-Lewis Research Center (LeRC) and the US Air Force's Wright Laboratory, a model has been developed which is based on the stress in the load-carrying fibres. The stress is modified by an effective stress concentration factor that is due to matrix cracking and a factor that includes the effect of hold times. It is a single term model that is intended for treating any variations in mechanical and thermal loads. Verification of this model is achieved by predicting fatigue lives for specimens subjected to spectrum loads performed at NASA-Lang]ey Research Center (LaRC) and vacuum tests completed at Georgia Tech. The model is compared to five methodologies previously developed for life prediction, and is shown to have significantly better predictive power while reducing the number of empirical constants and curve fitting parameters necessary to collapse the data.
引用
收藏
页码:479 / 492
页数:14
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