Machine learning‐based efficient stress intensity factor calculation for aeroengine disk probabilistic risk assessment under polynomial stress fields

Volume: 45, Issue: 2, Pages: 451 - 465
Published: Nov 4, 2021
Abstract
In probabilistic failure risk assessment, the accuracy and efficiency of the stress intensity factor calculation are important. The universal weight function method has been widely adopted for efficiency, but this method still has some debatable parts. For accurate and efficient stress intensity factor prediction, two approaches for machine learning techniques are specially designed. Three tests are conducted for the first approach where...
Paper Details
Title
Machine learning‐based efficient stress intensity factor calculation for aeroengine disk probabilistic risk assessment under polynomial stress fields
Published Date
Nov 4, 2021
Volume
45
Issue
2
Pages
451 - 465
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.