An information—Theoretic basis for uncertainty analysis: Application to the QUASAR severe accident study

Autor:	E. Schmidt, H. Nourbakhsh, M. Khatib-Rahbar, S.D. Unwin, M. Lee, E. Cazzoli, R. Davis, C.K. Park
Rok vydání:	1989
Předmět:	Accident (fallacy) Operations research Basis (linear algebra) Judgement Probabilistic logic Maximization Safety Risk Reliability and Quality Information theory Industrial and Manufacturing Engineering Uncertainty analysis Mathematics
Zdroj:	Reliability Engineering & System Safety. 26:143-162
ISSN:	0951-8320
DOI:	10.1016/0951-8320(89)90071-9
Popis:	The probabilistic characterization of uncertainty can be problematic in circumstances where there is a paucity of supporting data and limited experience on which to base engineering judgement. Information theory provides a framework in which to address this issue through reliance upon entropy-related principles of uncertainty maximization. We describe an application of such principles in the USNRC-sponsored program QUASAR (Quantification and Uncertainty Analysis of Source Terms for Severe Accidents in Light Water Reactors).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0511b896595dd21b514833cdea2652de https://doi.org/10.1016/0951-8320(89)90071-9 Zobrazit plný text záznamu