Numerical Modeling of Inverse Problems for Damage Detection in Aircraft Structures

Abstract

Structural health monitoring (SHM) is a competitive approach for damage detection in aircraft structures, wherein online information is collected and compared with an existing database for the undamaged structure, to obtain real-time information about the presence of damage. The goal of this research is to develop numerical models of inverse problems for damage detection in aircraft structures, which could later be part of an on-board system for SHM. In this work, the numerical modeling has two main branches: (1) The direct problem: a model is required to obtain information on the distribution of the quantity of interest throughout a given damaged structure. The model of the direct problem, using the boundary element method (BEM), is expected to reproduce the reality of an aircraft structure. (2) The inverse problem: a model is required to locate the structural damage given the information on the quantity of interest at particular locations (sensor locations). To increase the reliability of the detection approach, a combination of independent optimization and identification procedures can be used. Some treatment of the model uncertainties is required, due to the stochasticity in the problem variables and parameters.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 16, 2009
Accession Number
ADA513602

Entities

People

  • Ariosto B. Jorge

Organizations

  • Federal University of Itajubá

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Acoustic Propagation
  • Aircrafts
  • Boundary Element Methods
  • Civil Engineering
  • Composite Materials
  • Computational Science
  • Damage Detection
  • Detection
  • Elastic Properties
  • Engineering
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Mathematical Filters
  • Mechanical Engineering
  • Mechanics
  • Reliability
  • Structural Health Monitoring

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Modeling and Simulation
  • Explosive Engineering.