@inproceedings{921c8835981d417f9b0d077e775e8dbe,
title = "Fuel reliability analysis using BISON and RAVEN",
abstract = "The investigation of operational limits for nuclear fuel is a challenging subject and at the same time important to ensure reliability and safety of the nuclear energy production. The parametric and probabilistic analysis of failure is a very expensive process that might require thousands of simulations while exploring the input space by altering the input parameters. This paper will demonstrate how RAVEN is a suitable tool to perform such analysis. While RAVEN is fully capable to perform the needed parametric analysis, it can also use artificial intelligence to speed up the reliability/safety evaluation. In particular artificial intelligence algorithms are used to accelerate the search of the limit/reliability surfaces. This paper will review the concept of limit surface and its numerical representation, and will explain how support vector machine type algorithms are used to speed up the limit surface search. The limit surface location is then used to perform evaluation of the failure probability. This last step is examined in detail from the point of view of its numerical implementation.",
author = "C. Rabiti and J. Cogliati and G. Pastore and Gardner, \{R. J.\} and A. Alfonsi",
year = "2015",
language = "English",
series = "International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015",
publisher = "American Nuclear Society",
pages = "286--293",
booktitle = "International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015",
note = "2015 International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015 ; Conference date: 26-04-2015 Through 30-04-2015",
}