Efficient Sensitivity Methods for Probabilistic Lifing and Engine Prognostics

摘要

Probabilistic engine health management (PHM) is expected to be a go- forward approach for the USAF and other DoD agencies to enable dramatic improvements in the assessment and management of military assets. As a result, accurate and information-rich probabilistic lifing methods are essential to assess the benefits of technology insertion programs for PHM. As such, under this program three technology thrusts were investigated: a) sensitivity methods probability-of-failure estimates with respect to POD curve parameters, b) complex variable methods for sensitivity analysis, and c) probabilistic sensitivity analysis with respect to bounds of truncated distributions.