AIRFRAME DIGITAL TWIN SPIRAL 1. Task Order 0002: Scalable Accurate Flexible Efficient Robust - Prognostic and Probabilistic Individual Aircraft Tracking (SAFER-P2IAT) Full Scale Wing Experiment Plans, Requirements, and Development

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
Apr 01, 2017
Accession Number
AD1062259

Entities

People

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

Organizations

  • GE Global Research

Tags

Communities of Interest

  • Air Platforms
  • Cyber
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Aircrafts
  • Airframes
  • Bayesian Networks
  • Computational Science
  • Digital Twins
  • Engineering
  • Geometry
  • Information Science
  • Kalman Filters
  • Mathematical Filters
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Reliability
  • Strain Gages

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Logistics and Supply Chain Management.
  • Systems Analysis and Design