Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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.
Luis Guillermo Villanueva Torrijo, Tom Larsen, Ahmad Reza Motezakker