Issue |
EPJ Web Conf.
Volume 302, 2024
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC 2024)
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Article Number | 03002 | |
Number of page(s) | 10 | |
Section | Thermal-Hydraulics | |
DOI | https://doi.org/10.1051/epjconf/202430203002 | |
Published online | 15 October 2024 |
https://doi.org/10.1051/epjconf/202430203002
Bubble flow analysis using multi-phase field method
1 Center for Computational Science & e-Systems, Japan Atomic Energy Agency
2 Nuclear Science and Reactor Engineering Division, Nuclear Science and Engineering Center, Japan Atomic Energy Agency
* e-mail: sugihara.kenta@jaea.go.jp
* e-mail: onodera.naoyuki@jaea.go.jp
* e-mail: sitompul.yos@jaea.go.jp
* e-mail: idomura.yasuhiro@jaea.go.jp
† e-mail: yamashita.susumu@jaea.go.jp
Published online: 15 October 2024
In simulations of gas-liquid two-phase flows using conventional interface capture methods, we observed that when bubbles come close to each other, they tend to merge numerically, despite experimental evidence indicating that they would repel each other. Given the significant impact of sequential numerical coalescence on flow patterns, it is necessary to regulate the merging behavior of close bubbles. To address this issue, we introduced the Multi-Phase Field (MPF) method, which mitigates bubble coalescence by applying an independent fluid fraction function to each bubble. In this study, we employed the MPF based on the N-phase model [7] to minimize numerical errors associated with surface interactions at triple junction points. Additionally, we implemented the Ordered Active Parameter Tracking (OAPT) method [9] to efficiently store several hundreds of fluid fraction functions. To validate the MPF method, we conducted analysis of turbulent bubbly pipe flows and compared the results against experimental data from Colin et al [12]. The validation results showed reasonable agreements with respect to the bubble distribution and the flow velocity profiles.
© The Authors, published by EDP Sciences, 2024
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