• DocumentCode
    2794894
  • Title

    System reliability assessment using covariate theory

  • Author

    Wallace, Jon M. ; Mavris, Dimitri N. ; Schrage, Daniel P.

  • Author_Institution
    Georgia Tech, Atlanta, GA, USA
  • fYear
    2004
  • fDate
    26-29 Jan. 2004
  • Firstpage
    18
  • Lastpage
    24
  • Abstract
    A method is demonstrated that utilizes covariate theory to generate a multi-response component failure distribution as a function of pertinent operational parameters. Where traditional covariate theory uses actual measured life data, a modified approach is used herein to utilize life values generated by computer simulation models. The result is a simulation-based component life distribution function in terms of time and covariate parameters for each failure response. A multivariate joint probability covariate model is proposed by combining the covariate marginal failure distributions with the Nataf transformation approach. Evaluation of the joint probability model produced significant improvement in joint probability predictions as compared to the independent series event approach. The proposed methods are executed for a nominal aircraft engine system to demonstrate the assessment of multi-response system reliability driven by a dual mode turbine blade component failure scenario as a function of operational parameters.
  • Keywords
    covariance analysis; probability; reliability theory; Nataf transformation approach; covariate marginal failure distributions; covariate theory; dual mode turbine blade; joint probability predictions; life distribution function; multiresponse component failure distribution; multiresponse system reliability; multivariate joint probability covariate; nominal aircraft engine system; simulation-based component; system reliability assessment; Computational modeling; Computer simulation; Distribution functions; Hazards; Input variables; Life estimation; Life testing; Predictive models; Reliability; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability, 2004 Annual Symposium - RAMS
  • Print_ISBN
    0-7803-8215-3
  • Type

    conf

  • DOI
    10.1109/RAMS.2004.1285417
  • Filename
    1285417