Abstract
The frequency of reactor accidents is greatly affected by the likelihood of dependent multiple failures such as common cause failures (CCFs). The ability to quantify and prevent such failures is therefore crucial to the assessment and management of nuclear risks. We recently proposed the statistical correlation model for CCFs with the hope that it could assist in their quantification and aid in the identification of improved defenses against them. Since that time, we have been working to transform the statistical correlation model from an abstract theoretical concept into a practical set of working tools to realize this potentials. This paper reviews the theoretical basis for the statistical correlation model and summarizes the status of current work to develop improved methods and data to implement it in risk assessments and reliability analyses.
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© 1985 Plenum Press, New York
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Hartung, J.A., Ho, H.W., Rutherford, P.D., Vaughan, E.U. (1985). The Statistical Correlation Model for Common Cause Failures. In: Whipple, C., Covello, V.T. (eds) Risk Analysis in the Private Sector. Advances in Risk Analysis, vol 220. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-2465-2_27
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DOI: https://doi.org/10.1007/978-1-4613-2465-2_27
Publisher Name: Springer, Boston, MA
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