Concurrent Structural Fatigue Damage Prognosis Under Uncertainty

Project: Research project

Grant Details


Statement of Work at ASU Objectives The overall goal of the proposed project is to develop, validate and demonstrate a general damage prognosis and uncertainty management methodology for fatigue damage prognosis of aircraft structures. Two major objectives are identified: To establish a novel concurrent analysis framework for structural fatigue damage prognosis, which is based on a new small time scale formulation of materials and a coupled hierarchical state-space model of structural dynamics; To apply a rigorous probabilistic methodology for uncertainty quantification, probabilistic fatigue life prediction, and reliability updating using monitoring data. Multi-scale modeling and prognosis are well-defined research goals for the USAF [1]. The PI is aware of the current MURI project on structural health monitoring [21], which significantly advances the prognostic health management of Air Force systems. The MURI project covers a broad range of topics from micro-structural modeling to system applications and from advanced sensing technology to sophiscated signal processing methods. It is not intended to cover so many topics in this YIP proposal, which is not possible for a three-year project. Instead, the PI tries to limit the scope of this proposal on concurrent structural level prognosis. A few distinct features of the proposed study are briefly listed below. o The proposed study is based on a novel small time scale formulation of fatigue damage, which is fundamentally different than existing cycle-based classical fatigue theory. One benefit of this formulation is that the structural dynamics and material fatigue damage accumulation can be solved concurrently, which is not feasible for the cycle-based approach; o Advanced sensing technique is beyond the scope and the proposed study focuses on how to interpret the sensor data in a rigorous and systematic way. The usage monitoring data is integrated using the coupled hierarchical state-space model and the inspection data is integrated using the proposed Bayesian updating scheme. The proposed Bayesian- Information theory aims to use and interpret the sensor data in a statistically meaningful way. o The probabilistic life prediction used a new inverse reliability method, which directly calculates the remaining life under a specified reliability/risk level. This method is very different than most Monte Carlo simulation-based or forward reliability method (e.g., firstorder reliability method) and is very efficient for structural level prognosis in real time. This method has not been explored for fatigue prognosis to the best knowledge of the PI.
Effective start/end date8/22/123/31/14


  • DOD-USAF-AFRL: Air Force Office of Scientific Research (AFOSR): $227,654.00