Determination of Structural Reliability Using a Flaw Simulation Scheme

Abstract

This paper describes structural reliability developed an assumed flaw simulation scheme combined with an idealized linear elastic fracture mechanics model. In the reliability computation, it has been demonstrated that application of this scheme can provide a sensitivity analysis in relation to flaw detection capabilities. To demonstrate the versatility of the method, reliability numbers were obtained for both a simply loaded fragmentation shell and an antitank projectile subjected to a complex stress state. The flaw simulation scheme results are compared to corresponding reliability determinations from conventional Weibull and Warner stress-strength diagram methods. Both the weakest link and series-parallel system are evaluated for desirability in estimating structural reliability. The weakest link approach, which introduces reliability independence between elements, will thereby describe a much more conservative reliability estimate than the series-parallel system which requires at least two adjacent elements to fail in order to have structural failure. Examining the reliability computation for both structures as a function of assumed minimum detectable crack sizes indicated the importance of determining relatively small cracks to obtain acceptable reliability.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1981
Accession Number
ADA112054

Entities

People

  • Donald M. Neal
  • Donald S. Mason

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Computations
  • Data Science
  • Engineering
  • Failure Mode And Effect Analysis
  • Fracture (Mechanics)
  • Information Science
  • Massachusetts
  • Mechanics
  • Monte Carlo Method
  • Orientation (Direction)
  • Probability
  • Reliability
  • Simulations
  • Stress Analysis
  • Stresses
  • United States

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Statistical inference.
  • Structural Health Monitoring of Composite Structures.