期刊
COMPOSITES PART B-ENGINEERING
卷 39, 期 4, 页码 694-703出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compositesb.2007.05.006
关键词
probabilistic analysis; CMC vane; cumulative distribution function; probability density function; scatter; Weibull distribution; strength; proportional limit; design requirements; ceramic matrix composite
To demonstrate the advanced composite materials technology under development within the NASA Ultra-Efficient Engine Technology (UEET) Program, it was planned to fabricate, test, and analyze a turbine vane made entirely of silicon carbide-fiber-reinforced silicon carbide matrix composite (SiC/SiC CMC) material. The objective was to utilize a five-harness satin weave melt-infiltrated (MI) SiC/SiC composite material to design and fabricate a stator vane that can endure 1000 h of engine service conditions. The vane was designed to withstand a maximum temperature of 1315 degrees C (2400 degrees F) within the substrate and the hot surface temperature of 1482 degrees C (2700 degrees F) with the aid of an environmental/thermal barrier coating (EBC/TBC) system. Furthermore, the vane was designed such that the expected maximum stresses to be encountered were kept within the proportional limit strength of the material. Any violation of this design requirement was considered as the failure. This paper presents results of a probabilistic analysis and reliability assessment of the vane. Probability of failure to meet the design requirements was computed using the probabilistic analysis methods embedded in the NESSUS software. In the analysis, material properties, strength, and pressure loading were considered as random variables. The variations in properties and strength were based on the actual experimental data. In the present analysis, the pressure loads were considered normally distributed with a nominal variation. A temperature profile on the vane was obtained by performing a computational fluid dynamics (CFD) analysis and was assumed to be deterministic. The results suggest that for the current vane design, the chance of not meeting design requirements is about 1.6%. Published by Elsevier Ltd.
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