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Influence of Two-Phase Crossflow for Void Prediction in Bundles Using Thermal-Hydraulic System Codes

Author

Listed:
  • Yunseok Lee

    (Department of Safety Engineering, Incheon National University, Incheon 22012, Korea)

  • Taewan Kim

    (Department of Safety Engineering, Incheon National University, Incheon 22012, Korea)

Abstract

The previous study, where the void fraction predictability of three different thermal-hydraulic system codes was assessed against PSBT (PWR Subchannel and Bundle Test) benchmark data, indicated a general overprediction tendency of all system codes, especially in bundles. Because all codes have been utilized for best-estimate analyses, it is necessary to conduct further assessments in order to find the root cause of the overprediction. A further assessment has been performed using two thermal-hydraulic system codes, TRACE V5.0 patch 5 and MARS-KS 1.4, and the assessment has been carried out for both one- and multi-dimensional components. The results indicate that there is no significant difference in the predictability of the void fraction between one- and multi-dimensional components. In addition, it is found that the turbulent mixing model implemented for the multi-dimensional component of MARS-KS does not play an important role in the prediction of void distribution. Meanwhile, TRACE reveals a significant overprediction due to much less crossflow calculation compared to MARS-KS. By conducting an additional analysis with the modified one-dimensional models, it is clearly confirmed that crossflow significantly affects the void distribution. Therefore, it is concluded that the model for the thermal hydraulic mixing by crossflow in each system code should be improved in order to predict the void distribution in bundles appropriately.

Suggested Citation

  • Yunseok Lee & Taewan Kim, 2020. "Influence of Two-Phase Crossflow for Void Prediction in Bundles Using Thermal-Hydraulic System Codes," Energies, MDPI, vol. 13(14), pages 1-13, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3686-:d:386043
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    Cited by:

    1. Wei-Hsin Chen & Hwai Chyuan Ong & Shih-Hsin Ho & Pau Loke Show, 2021. "Green Energy Technology," Energies, MDPI, vol. 14(20), pages 1-4, October.

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