AIRFRAME DIGITAL TWIN (ADT) Delivery Order FA8650-17-F-2219: Scalable, Accurate, Flexible, Efficient, Robust, Prognostic and Probabilistic Individual Aircraft Tracking (SAFER-P2IAT) Full-Scale Demonstration Experiment

Abstract

Improving the accuracy of structural diagnosis and prognosis to make better maintenance decisions is accomplished through more realistic structural analysis of fatigue crack growth, including sources of uncertainty into predictions, and fusing usage and inspection data to update and reduce uncertainty. A set of methods for uncertainty quantification and updating form the basis of the framework. Modularity supports transition to other platforms and reliability problems. Uncertainty in inputs and outputs is described by parametric or non-parametric probability distributions. Criteria for performing inspections can be established based on probabilities of events.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2019
Accession Number
AD1093390

Entities

People

  • Dale Ball
  • Elias Dakwar
  • Genghis Khan
  • Isaac Asher
  • Jochen Hoffmann
  • Kevin Ryan
  • Liping Wang
  • Randy Longtin
  • Robert Shannon

Organizations

  • General Electric

Tags

Communities of Interest

  • Air Platforms
  • Cyber

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Aircrafts
  • Airframes
  • Bayesian Networks
  • Computational Science
  • Flight Recorders
  • Information Science
  • Mathematical Filters
  • Mechanics
  • Neural Networks
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Reliability
  • Surveys

Readers

  • Aerospace Engineering
  • Computational Modeling and Simulation
  • Structural Health Monitoring of Composite Structures.