A Simulation Process for Determining Reliability of Cyclic Random Loaded Structures

Abstract

A unique application of the Monte Carlo method was developed for determining reliability vs. cycles to failure of the M60 tank torsion bar. In applying the method, material torsional fatigue and spectrum loads were modelled such that variability in the functional parameters and operational loads were represented. Random torsional displacement values obtained from the amplitude displacement distributions applied to the fatigue equations resulted in an exponential distribution for cycles to failure of the in service bar. The number of simulations in the Monte Carlo process was determined from a convergence criteria involving stability of the third and fourth moments of the cycles to failure distribution. Reliability vs. bar life computations indicated a negligible amount of life after flaw initiation. Assuming a design change involving a twenty percent reduction in bar stresses increased the life estimates by a factor of three. An increase in reliability can also be realized if computations are made by assuming a bar has been in operation for a specified number of cycles. A comparison of minimum life (ninety nine percent probability of survival) between predicted and in service results showed excellent agreements (less than eight percent difference).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADP003849

Entities

People

  • D. Neal
  • T. Deangelis
  • W. Matthews

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Agreements
  • Amplitude
  • Crack Propagation
  • Cracks
  • Cycles
  • Data Science
  • Design Criteria
  • Displacement
  • Equations
  • Experimental Data
  • Fatigue Tests (Mechanics)
  • Materials
  • Monte Carlo Method
  • Probability
  • Reliability
  • Survival
  • Torsion Bars

Fields of Study

  • Engineering

Readers

  • Mathematics or Statistics
  • Structural Dynamics.
  • Structural Health Monitoring of Composite Structures.