Publication

Extension of GeN-Foam to departure from nucleate boiling prediction and validation against the OECD/NRC PSBT benchmark

Carlo Fiorina, Yuhang Niu, Hao Qin
2023
Journal paper
Abstract

The prediction of departure from nucleate boiling (DNB) has always been a crucial aspect of thermal-hydraulic codes for the analysis of Light Water Reactors. In this paper, GeN-Foam, a multi-physics code developed based on OpenFOAM, has been enhanced to incorporate DNB prediction using a CHF look-up table as well as post-CHF flow and heat transfer models. To assess GeN-Foam's accuracy in modeling DNB conditions in typical pressurized water reactors (PWRs), a preliminary validation was conducted utilizing Phase II of the PSBT benchmark, including the steady-state fluid temperature (Test Series 1), steady-state DNB (Test Series 4), and transient DNB (Test Series 11T) benchmarks. This paper presents the closure correlations implemented in GeN-Foam, provides a description of the PSBT benchmarks, and includes a comparison between GeN-Foam's predictions and experimental data, as well as code-to-code verification with other participants. The results demonstrate that GeN-Foam exhibits good performance in simulating two-phase flow boiling conditions. Furthermore, GeN-Foam accurately predicts the DNB power and time of occurrence within a +/- 10 % error range compared to measured values, preliminarily indicating its effectiveness in predicting DNB occurrence and two-phase flow boiling phenomena.

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