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ASME Turbo Expo 2007 Power for Land, Sea, and Air May 14-17, 2007, Montreal, Canada GT2007-27935 RELIABILITY PREDICTION OF MONOLITHIC STRUCTURAL CERAMICS WITH UNCERTAINTIES X. Luo, G.V. Srinivasan, and W.K. Tredway United Technologies Research Center, East Hartford, CT 06108 ABSTRACT Reliability prediction of monolithic structural ceramics involves stress analysis through Finite Element Analysis and a probability of failure prediction code such as CARES that considers the strength of ceramics as a statistical (Weibull) distribution. Though the strength is considered as a statistical distribution, stress in a given volume or surface element is discrete in current practice. However, uncertainties in FEA input such as material properties or boundary conditions make the predicted stress uncertain, thereby resulting in predicted reliability being uncertain as well. A probabilistic framework has been developed for reliability prediction to estimate component reliability by treating the uncertainties in loading, boundary conditions, and material properties as random variables. The framework consists of an automated, closed loop process integrating algorithms for assessing failure probability due to general randomness. Efficient and accurate computational methods for reliability analysis have been implemented in the framework for significant savings in computation time. The methodology is demonstrated on a gas turbine component. The analysis shows that reliability is compromised significantly by a design based on mean values of the random parameters, while an overly conservative design based on worst case scenario will result in rejection of too many components at unnecessarily high proof test loads. This method ultimately leads to the determination of an optimum proof test level to assure component reliability amidst several sources of uncertainties in reliability prediction. INTRODUCTION The unique properties of advanced ceramics such as high- temperature strength, environmental resistance, and low density provide the potential for greatly increased fuel efficiency and reduced weight and emissions in aerospace and industrial gas turbine engine applications. Consequently, research and development activities have focused on improving ceramic material processing and properties as well as on establishing a sound design methodology. Being brittle with no plasticity makes these materials vulnerable for catastrophic failure. Variability in size and distribution of inherent flaws in ceramics makes their failure probabilistic in nature. Therefore, optimization of design requires the ability to accurately predict a component's load resistance and reliability. It is economically prohibitive to test a statistically significant number of ceramic components in actual operating environments for the intended life-time to obtain the reliability. Hence a probabilistic model based on physics of failure has to be used to predict reliability of these components. Methods of quantifying reliability in ceramics and the corresponding failure probability have been investigated by few [1-4]. The result of one such effort led by NASA Glenn (formerly NASA Lewis) Research Center is a computer software named CARES (Ceramics Analysis and Reliability Evaluation of Structures) [5]. This CARES software is used in this study for reliability determination. The reliability evaluation methodology combines linear elastic fracture mechanics theory that relates strengths of ceramics to size, shape, and orientation of critical flaws; a characteristic flaw size distribution function that accounts for the size effect on strength via the weakest-link concept; and a time- dependent strength degradation caused by sub-critical crack growth. Current Practice in Determining Ceramic Component Reliability Inherent in this methodology is that the component integrity is a function of the entire field solution for stresses and is not based only on the most highly stressed point (contrary to metals). Hence stress state prediction for the whole component via Finite Element Analysis (FEA) is required. Probabilistic 125 Copyright © 2007 by ASMEPDF Image | ADVANCED MICROTURBINE SYSTEMS Final Report for Tasks 1 Through 4 and Task 6
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