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논문 기본 정보

자료유형
학술저널
저자정보
Thacker, Ben H. (Materials Engineering Department, Southwest Research Institute) Huyse, Luc J. (Materials Engineering Department, Southwest Research Institute)
저널정보
테크노프레스 Structural engineering and mechanics : An international journal Structural engineering and mechanics : An international journal 제25권 제3호
발행연도
2007.1
수록면
331 - 345 (15page)

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Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.

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