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The Monte Carlo GPT methodology for the analysis of ratios of functionals bilinear with the real and adjoint neutron fluxes

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Abstract Perturbation methods are part of the reactor physics foundation devoted to the study of fundamental quantities used in design and safety analysis of nuclear reactors. In deterministic codes, such… Click to show full abstract

Abstract Perturbation methods are part of the reactor physics foundation devoted to the study of fundamental quantities used in design and safety analysis of nuclear reactors. In deterministic codes, such as ERANOS, standard perturbation theory (SPT) and generalized perturbation theory (GPT) methods have been historically developed and used. Monte Carlo codes, such as MCNP 6.1, can also perform, via adjoint weighted tally, SPT calculations of reactivity worths. In this work a method, referred to as MC-GPT, is envisaged to enable Monte Carlo codes to be used also for GPT analysis. A preliminary comparison between calculations with MCNP and ERANOS relevant to perturbations affecting a given reactivity worth functional is presented and commented.

Keywords: methodology; carlo gpt; adjoint; gpt methodology; analysis; monte carlo

Journal Title: Annals of Nuclear Energy
Year Published: 2017

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