Reliability Prediction and Cost Optimization for Composites Including Periodic Proof Tests in Service.

Abstract

An exploratory reliability analysis of composites under periodic proof tests in service is presented. The ultimate strength of composites is a random variable having a two-parameter Weibull distribution. A residual strength model is employed to describe the strength degradation of composites under service loads. Fatigue failure occurs as soon as the residual strength of composites is exceeded by service loads, such as gust turbulence for transport-type aircraft and maneuver loads for fighter aircraft. Both the gust and maneuver loads are considered as random loads and their exceedance curves obtained from field data are used in the present analysis. Meanwhile, the composites are subjected to periodic proof tests in order to eliminate weak components and to ensure an acceptable level of reliability. Taking into account all the random variables (ultimate strength and residual strength), strength degradations, service loads, proof tests and renewal processes, the probability of structural failure in service is derived. It is demonstrated by numerical examples that significant cost savings and reliability improvement for composite structures can be achieved by the application of the optimal periodic proof test.

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Document Details

Document Type
Technical Report
Publication Date
Nov 15, 1976
Accession Number
ADA040076

Entities

People

  • Jann N. Yang

Organizations

  • Virginia Tech

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Bonded Joints
  • Composite Materials
  • Data Science
  • Distribution Functions
  • Epoxy Laminates
  • Failure Mode And Effect Analysis
  • Fighter Aircraft
  • Laminates
  • Materials
  • Materials Laboratories
  • Probability Density Functions
  • Random Variables
  • Statistical Distributions
  • Structural Components
  • Turbulence

Readers

  • Aviation Science / Aeronautics.
  • Reinforced Composite Materials
  • Statistical inference.