Bibliographic Details
| Title: |
Assessment of MARS-KS prediction capability for natural circulation flow in passive heat removal system |
| Authors: |
Jehee Lee, Youngjae Park, Seong-Su Jeon, Ju-Yeop Park, Hyoung Kyu Cho |
| Source: |
Nuclear Engineering and Technology, Vol 56, Iss 8, Pp 3435-3449 (2024) |
| Publisher Information: |
Elsevier, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Nuclear engineering. Atomic power |
| Subject Terms: |
Passive safety system, Passive heat removal system, Natural circulation flow, Pressure drop, Two-phase flow, MARS-KS, Nuclear engineering. Atomic power, TK9001-9401 |
| More Details: |
Considering that system analysis codes are used for the evaluation of the performance of Passive Safety Systems (PSSs), it is important to investigate the capability of the system analysis code to reliably predict the heat transfer and natural circulation flow, which are the main phenomena governing the performance of a PSS. Since MARS-KS has been widely validated for heat transfer models, this study focuses on evaluating its capability to predict the single and two-phase pressure drops and natural circulation flow. The straight pipe simulation results indicate that the pressure drop predictions are reliable within ±5 % error margin for the single-phase flow and the errors of pressure drop up to −30 % for the two-phase flow. Through single-phase natural circulation flow analysis, it is concluded that the use of the appropriate K-factor modeling based on the flow regimes is important since the natural circulation flow rate in MARS-KS is mainly affected by the form loss factor modeling. With two-phase natural circulation flow analysis, this study emphasizes the behavior of the system could change significantly depending on the two-phase wall friction and pressure loss modeling. With the analysis results, modeling considerations for the PSS performance evaluation with the system analysis codes are proposed. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1738-5733 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S1738573324002109; https://doaj.org/toc/1738-5733 |
| DOI: |
10.1016/j.net.2024.04.042 |
| Access URL: |
https://doaj.org/article/7fa2b32f71ca4f7a9aa24651c0f0b795 |
| Accession Number: |
edsdoj.7fa2b32f71ca4f7a9aa24651c0f0b795 |
| Database: |
Directory of Open Access Journals |
