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Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees

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  • Vijay Tulsiani
  • Yacov Y. Haimes
  • Duan Li

Abstract

Risk and uncertainty are integral parts of modern technology, and they must be managed effectively to allow the development of reliable, high‐quality products. Because so many facets of technology and society involve risk and uncertainty, it is essential that risk management be handled in a systematic manner. Fault‐tree analysis is one of the principal methods used in the analysis of systems’safety. Its detailed and systematic deductive structure makes it a valuable tool for design and diagnostic purposes. Point probability and the minimization of the expected failure probability have, until recently, dominated fault‐tree analysis. A methodology that incorporates uncertainty analysis, conditional expected risk, and multiple objectives with fault‐tree analysis is presented. A computer software package termed the “Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees,” which translates the new methodology into a working decision‐support system, is developed. DARE Using Fault Trees is a flexible computer code that is capable of analyzing the risk of the overall system in terms of the probability density function of failure probability. Emphasis is placed on the uncertainty and risk of extreme events. A comparative study between existing codes for fault‐tree analysis and DARE demonstrates the strengths of the methodology. A case study for NASA's solid rocket booster is used to perform the comparative analysis.

Suggested Citation

  • Vijay Tulsiani & Yacov Y. Haimes & Duan Li, 1990. "Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees," Risk Analysis, John Wiley & Sons, vol. 10(4), pages 521-538, December.
  • Handle: RePEc:wly:riskan:v:10:y:1990:i:4:p:521-538
    DOI: 10.1111/j.1539-6924.1990.tb00537.x
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    Cited by:

    1. P. Kuzminski & J. S. Eisele & N. Garber & R. Schwing & Y. Y. Haimes & D. Li & M. Chowdhury, 1995. "Improvement of Highway Safety I: Identification of Causal Factors Through Fault‐Tree Modeling," Risk Analysis, John Wiley & Sons, vol. 15(3), pages 293-312, June.

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