Predictive Modeling of Structural Sensing for Aerospace Applications
Abstract
A methodology for multi-scale multi-domain predictive simulation of structural sensing in metallic aerospace structures was developed. The methodology is able to predict the signal response of structural sensors as a function of the structural state and/or the presence of structural flaws or damage, in linear and nonlinear regimes. The approach has been to combine analytical solutions with numerical analysis (e.g., finite element method, FEM) into a hybrid global-local (HGL) analysis. This novel approach allows one to keep the computational effort at a manageable level while preserving the fidelity needed to capture the local interaction between ultrasonic guided waves and structural damage. This fundamental research project has high relevance to USAF because it has produced a methodological framework for coupling global and local models to achieve the concurrent analysis of the structure in interaction with coupled-field phenomena and efficient treatment of nonlinearities. The results of this project can be used to generate virtual data sets for testing data-driven models and filling data gaps will allow the autonomous model updating of the digital-twins models to predict future performance for new mission profiles.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 03, 2015
- Accession Number
- AD1008009
Entities
People
- Victor Giurgiutiu
Organizations
- University of South Carolina