Research into Simulator Realism Gaps using Machine and Causal Learning

Abstract

Problem: USAF in prior years indicated (1) simulating realistic flight dynamics and tests for more complex system behavior is increasingly difficult, and (2) avionics changes can now require an unacceptable two years of regression testing. More efficient testing while maintaining realism is imperative. The technical limitation rests in the inability to analyze/simulate avionics system behavior, conditioned by hundreds of parameters, to achieve realistic flight dynamics and early identification of issues.

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Document Details

Document Type
Technical Report
Publication Date
Jun 13, 2022
Accession Number
AD1172647

Entities

People

  • Robert W. Stoddard

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Air Platforms
  • Biomedical

DTIC Thesaurus Topics

  • Active Duty
  • Aircrafts
  • Airplanes
  • Anomaly Detection
  • Artificial Intelligence
  • Avionics
  • Case Studies
  • Causal Reasoning
  • Complex Systems
  • Data Analysis
  • Department Of Defense
  • Engineering
  • Flight Recorders
  • Flight Testing
  • Information Science
  • Machine Learning
  • Neural Networks
  • Recording Systems
  • Robots
  • Simulations
  • Simulators
  • Software Development
  • Statistics
  • Universities

Fields of Study

  • Computer science

Readers

  • Aviation Science / Aeronautics.
  • Systems Analysis and Design