Phase-field modeling with the TAF-ID of incipient melting and oxygen transport in nuclear fuel during power transients
Source abstract
Abstract
Abstract In this paper, a phase-field model is developed for a two phase compositional (multicomponent) system and combined with the thermodynamic description provided by a CALPHAD database. The model is applied to a uranium-oxygen binary system within a solid/liquid mixture to simulate incipient melting and oxygen transport (oxygen-uranium inter-diffusion and Soret effect) in the fuel with thermodynamic properties coming from the Thermodynamics for Advanced Fuels-International Database (TAF-ID). The interface with the TAF-ID required the coupling of the phase-field model with the OpenCalphad thermochemical solver. This coupling led to the development of a partitioned scheme that is solved at each time step with a fixed-point algorithm. To analyze the response of and to parameterize the phase-field model, two 1D demonstration problems from the open literature have been considered and solved using a finite-difference scheme. The first problem deals with oxygen transport in UO 2.005 fuel under an imposed parabolic temperature profile below liquidus. The second one describes the incipient melting and oxygen transport in oxidized fuel under an increasing temperature profile. Oxygen thermal diffusion is considered both in the solid and liquid phases. All the results presented in this paper are in good agreement with those already published but are here performed considering a direct coupling with the TAF-ID database. They demonstrate the thermodynamic consistency of the phase-field model as well as its capability to simulate incipient melting and oxygen transport in the fuel with advanced thermodynamics databases.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nuclear Materials and Properties · Nuclear reactor physics and engineering · Metallurgical Processes and Thermodynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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