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      Effects of Tube Rupture Modeling and Parameters on Analysis of MSGTR Event Progression in PWR

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      https://www.riss.kr/link?id=E805089

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      A multiple steam generator tube rupture (MSGTR) event in APR1400 has been investigated using the best estimate thermal hydraulic system code, MARS1.4. The effects of parameters such as the number of ruptured tubes, rupture location, affected steam generator on analysis of the MSGTR event in APR1400 is examined. In particular, tube rupture modeling methods, single tube modeling (STM) and double tube modeling (DTM), are compared. When five tubes are ruptured, the STM predicts the operator response time of 2085 seconds before main steam safety valves (MSSVs) are lifted. The effects of rupture location on the MSSV lift time is not significant in case of STM, but the MSSV lift time for tube-top rupture is found to be 25.3% larger than that for rupture at hog-leg side tube sheet in case of DTM. The MSSV lift time for the cases that both steam generators are affected (4C5x, 4C23x) are found to be larger than that of the single steam generator cases (4A5x, 4B5x) due to a bifurcation of the primary leak flow. The discharge coefficient of Cd is found to affect the MSSV lift time only for smaller value of 0.5. It is found that the most dominant parameter governing the MSSV lift time is the leak flow rate. Whether any modeling method is used, it gives the similar MSSV lift time if the leak flow rate is close, except the case of both steam generators are affected. Therefore, the system performance and the MSSV lift time of the APR1400 are strongly dependent on the break flow model used in the best estimate system code.
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      A multiple steam generator tube rupture (MSGTR) event in APR1400 has been investigated using the best estimate thermal hydraulic system code, MARS1.4. The effects of parameters such as the number of ruptured tubes, rupture location, affected steam gen...

      A multiple steam generator tube rupture (MSGTR) event in APR1400 has been investigated using the best estimate thermal hydraulic system code, MARS1.4. The effects of parameters such as the number of ruptured tubes, rupture location, affected steam generator on analysis of the MSGTR event in APR1400 is examined. In particular, tube rupture modeling methods, single tube modeling (STM) and double tube modeling (DTM), are compared. When five tubes are ruptured, the STM predicts the operator response time of 2085 seconds before main steam safety valves (MSSVs) are lifted. The effects of rupture location on the MSSV lift time is not significant in case of STM, but the MSSV lift time for tube-top rupture is found to be 25.3% larger than that for rupture at hog-leg side tube sheet in case of DTM. The MSSV lift time for the cases that both steam generators are affected (4C5x, 4C23x) are found to be larger than that of the single steam generator cases (4A5x, 4B5x) due to a bifurcation of the primary leak flow. The discharge coefficient of Cd is found to affect the MSSV lift time only for smaller value of 0.5. It is found that the most dominant parameter governing the MSSV lift time is the leak flow rate. Whether any modeling method is used, it gives the similar MSSV lift time if the leak flow rate is close, except the case of both steam generators are affected. Therefore, the system performance and the MSSV lift time of the APR1400 are strongly dependent on the break flow model used in the best estimate system code.

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      목차 (Table of Contents)

      • Ⅰ. INTRODUCTION
      • Ⅱ. MARS MODELING FOR APR140
      • Ⅱ.A. Single Tube Modeling (STM)
      • Ⅱ.B. Double Tube Modeling (DTM)
      • Ⅱ.C. Calculation Procedure
      • Ⅰ. INTRODUCTION
      • Ⅱ. MARS MODELING FOR APR140
      • Ⅱ.A. Single Tube Modeling (STM)
      • Ⅱ.B. Double Tube Modeling (DTM)
      • Ⅱ.C. Calculation Procedure
      • Ⅲ. RESULTS AND DISSCUSSIONS
      • Ⅲ.A. Effects of Number of Ruptured Tubes
      • Ⅲ.B. Effects of Rupture Location
      • Ⅲ.C. Effects of Affected Steam Generator
      • Ⅲ.D. Effects of Discharge Coefficient
      • Ⅲ.E. Effects of Modeling Methods
      • Ⅳ. CONCLUSIONS AND RECOMMENDATIONS
      • ACKNOWLEDGMENTS
      • REFERENCES
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