Model-Based Structural Health Monitoring of Fatigue Damage Test-Bed Specimens

Abstract

This research project represents a preliminary investigation into a comprehensive analytical, numerical, and experimental framework for the monitoring and life-cycle assessment of the structural integrity and performance of aluminum hull structures. Aluminum plate specimens were designed and fabricated to facilitate the investigation of system identification and damage detection methodologies, both of which are key components of future life-cycle analyses. The design of the plate specimens was intended to include the geometric complexity commonly found in aluminum hull ships. A powerful Bayesian probabilistic model was applied to validate its potential applicability for damage identification around critical weld zones where fatigue failure is likely to initiate. Extensive numerical simulation and experimental testing was conducted to validate the model-based approach to crack damage detection in aluminum plate structures.

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Document Details

Document Type
Technical Report
Publication Date
Nov 15, 2011
Accession Number
ADA556761

Entities

People

  • Jerome Lynch
  • Kincho H. Law
  • Masahiro Kurata

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Bayesian Networks
  • Computational Science
  • Damage Detection
  • Detection
  • Engineering
  • Finite Element Analysis
  • Life Cycles
  • Littoral Combat Ships
  • Materials
  • Mechanics
  • Probabilistic Models
  • Probability
  • Ship Hulls
  • Simulations
  • Structural Health Monitoring
  • Structural Properties
  • Test Beds

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Materials Science (Mechanical Engineering).

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference