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• W3100160596 endingPage "111007" @default.
• W3100160596 startingPage "111007" @default.
• W3100160596 abstract "In this paper, we are interested in taking into account uncertainties for keff computations in neutronics. More generally, the material of this paper can be applied to propagate uncertainties in eigenvalue/eigenvector computations for the linear Boltzmann equation. In [1], [2], an intrusive MC solver for the gPC based reduced model of the instationary linear Boltzmann equation has been put forward. The MC-gPC solver presents interesting characteristics (mainly a better efficiency than non-intrusive strategies and spectral convergence): our aim is to recover these characteristics in an eigenvalue/eigenvector estimation context. This is done in practice at the price of few well identified modifications of an existing Monte Carlo implementation." @default.
• W3100160596 created "2020-11-23" @default.
• W3100160596 creator A5028131333 @default.
• W3100160596 creator A5034346612 @default.
• W3100160596 date "2022-05-01" @default.
• W3100160596 modified "2023-10-17" @default.
• W3100160596 title "Efficient uncertain keff computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models" @default.
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• W3100160596 doi "https://doi.org/10.1016/j.jcp.2022.111007" @default.
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