A Method for Modeling System-Driven Uncertainty during Probabilistic Part Life Analyses

40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, Ft. Lauderdale, FL, July 11-14, 2004.Probabilistic part life analyses of turbine components have typically been conducted in an ad-hoc fashion with respect to the influence of the system. While this approach greatly simplifes the analysis, signifcant errors and misleading results are possible. However, directly modeling the system analyses in a fully probabilistic and integrated fashion can be prohibitive in terms of the infrastructure required. An effcient approach to characterizing and quantifying the system-driven input for probabilistic part life assessments is proposed. The approach is demonstrated for a turbine blade operating in a medium size commercial transport jet. The results of this demonstra- tion illustrate how the component parameters and failure mechanisms can be qualitatively identifed and the complex probabilistic input modeled as driven by the system behavior