A Coupled Approach to Developing Damage Prognosis Solutions

Abstract

An approach to developing damage prognosis (DP) solution that is being developed at
\nLos Alamos National Laboratory (LANL) is summarized in this paper. This approach integrates
\naadvanced sensing technology, data interrogation procedures for state awareness, novel model
\nvalidation and uncertainty quantification techniques, and reliability-based decision-making
\nalgorithms in an effort to transition the concept of damage prognosis to actual practice. In parallel
\nwith this development, experimental efforts are underway to deliver a proof-of-principle technology
\ndemonstration. This demonstration will assess impact damage and predict the subsequent fatigue
\ndamage accumulation in a composite plate. Although the project focus will be DP for composite
\nmaterials, most of this technology can generalize to many other applications. The unique aspects of
\nthis approach discussed herein include: 1) multi-length scale damage models analyzed on tera-scale
\ncomputer platforms that discretize composites on an individual lamina level, 2) integration of
\nadvanced sensors with Los Alamos’s flight-hardened data acquisition system, 3) damage detection
\nbased on a statistical pattern recognition approach, and 4) reliability-based metamodels with
\nquantified uncertainty that can be deployed on microprocessors integrated with the sensing system
\nfor autonomous damage prognosis.