本研究中使用MAAP5量化先進型沸水式反應器在電廠全黑嚴重事故下壓力槽失效模式與時間之不準確度。MAAP 5 程式使用簡化模組與經驗公式模擬爐心熔毀事件過程以及現象，可以預見MAAP 5程式的模擬結果必然存在不準確度。
本研究選定MAAP5程式反應器壓力槽失效模擬模組的20個輸入參數，設定其機率密度函數，以蒙地卡羅隨機取樣方法決定輸入參數的組合，使用MAAP 5程式進行多次計算，輸出參數的分佈即為程式輸出參數的不準確度，再利用皮爾森相關系數找出對輸出參數不準確度影響最大的輸入參數。本研究將以台灣電力公司龍門電廠為例，模擬時假設電廠於事故發生瞬間喪失所有電源，且運轉人員未進行系統洩壓高壓事故序列。
MAAP5程式同時進行5種會造成壓力槽失效機制的模擬，事故演變過程中，最先達到失效條件的機制，即為壓力槽失效的模式。MAAP5模擬壓力槽失效現象時須設定兩個模式選擇之輸入參數 (model option)，INTERFOX和IQDPB，共有4 種組合。INTERFOX選擇爐芯殘渣所構成液態氧化物層與凝固之爐芯殘渣所形成之硬殼 (crust) 間的介面溫度使用是固體熔化溫度 (solidus temperature)抑或是液體凝固溫度 (liquidus temperature)；IQDPB則是選擇爐心殘渣與壓力槽底部積水間之熱傳經驗公式。
本研究的不準確度分析共有4組案例，每個案例進行500組計算。討論的輸出參數包括熔融爐芯掉落至壓力槽底部區間的時間、壓力槽底部區間積水蒸乾時間、壓力槽失效時間、壓力槽失效模式、壓力槽底部積水蒸乾至壓力槽失效所需時間、以及爐芯掉落於壓力槽底部至壓力槽失效所需時間、壓力槽失效後熔融爐芯於圍阻體內之分佈、壓力槽失效時爐穴與乾井之溫度等參數。
不準確度分析的結果顯示，如INTERFOX與IQDPB 均採用MAAP5使用手冊的建議值，壓力槽失效時間介於4.58 (5th) 與7.06 (95th)小時間，中位值為 6.05小時、平均時間為6小時、最可能時間為6.3小時；76.4% 的機會壓力槽的失效模式為熔融爐芯池金屬曾造成壓力槽槽體受熱喪失強度失效(OVLH)、32.4% 的機會為壓力槽底部控制棒穿越管焊道受熱失效(EJCRD)。若所有的輸入參數均採使用手冊的建議值，預測之壓力槽失效時間為4.81小時，失效模式為 OVLH。
量化結果顯示INTERFOX模式選擇參數幾乎對所有本研究討論的輸出參數都有較大的影響。20個輸入參數中，僅ECREPF與XDJETO兩個參數的皮爾森係數超過篩選值，顯示其與輸出參數有明顯之關係。

MAAP5 is an integral severe accident analysis code, which employs modularized phenomenological models to mimic the phenomena involved in the progression of core melt accident of nuclear power reactors. These modules were validated against the results of separate effects experiments. It can be expected that the predicted results of MAAP5 have large uncertainties and these uncertainties would definitely play a role in delineating the mitigating measures during a severe accident of nuclear power plant.
In the present study, the uncertainty in the predicted vessel lower head failure time and failure mode of an Advanced Boiling Water Reactor (ABWR) in an accident initiated by station blackout is explored. The important model parameters that affect the target output parameters are selected based on the suggestion by the code developer, Fauske & Associated Inc. The uncertainties of input parameters are propagated through code calculations and the input combinations of 20 input parameters are generated using the technique of Latin Hypercube Sampling.
The vessel failure mechanisms considered in MAAP5 code including the attack of vessel wall by layered molten core pool and overlying metal layer in vessel lower plenum, the ejection of vessel penetration tubes due to failure of weld, the heat up of penetration tubes. The results of the uncertainty quantification show that, when default model options are used in the quantification, the vessel failure time lies between 4.58 (5th) and 7.06 hours (95th), the median time is 6.05 hour, the average time is 6 hour, the most probable time is 6.3 hour. The point estimate time is 4.81 hour.
The results show that the probability of vessel fails due to the ejection of control rod drive tube is 32.4% and due to attacking of metal layer is 76.4%. The probability of vessel failure due to heat up of drain line is very small. When Pearson’s correlation coefficient is used to identify the relation between output parameter and input parameters, among 20 input parameters studied, only ECREPF is related to the vessel failure time.

摘 要 i
Abstract iii
致謝詞 v
目錄 vi
表目錄 viii
圖目錄 ix
符號及縮寫表 xi
第一章 緒論 1
1.1 前言 1
1.2 嚴重事故進程 1
1.3 龍門電廠介紹 3
第二章 程式介紹 4
2.1 MAAP 5.03 程式介紹 4
2.2 Dakota 程式 9
第三章MAAP 5.03程式 壓力槽失效機制與計算模式 10
3.1 壓力槽失效機制 10
3.2 壓力槽失效計算模式 15
第四章 不準確度量化方法論 18
4.1量化步驟 18
4.2 蒙地卡羅抽樣法 22
4.3 假設檢定(Hypothesis Testing) 23
4.4 卡方檢定 (Chi-square Test) 24
4.5 皮爾森相關係數 24
第五章 概述與討論 25
5.1龍門電廠全黑事故分析 25
5.2 案例分析組合 28
5.3 壓力槽失效模式 30
5.4 重要事件時間分析 32
5.4.1 熔融爐心掉落至壓力槽底部起始時間 32
5.4.2 壓力槽底部積水蒸乾時間 34
5.4.3 壓力槽失效時間 38
5.4.4 壓力槽底部積水蒸乾所需時間 51
5.4.5 壓力槽底部失效所需時間 53
5.4.6 壓力槽失效後圍阻體增加之質量 59
5.4.7 壓力槽失效時爐穴與乾井之平均溫度 65
第六章 結論 與 未來建議 70
6.1 結論 70
6.2 未來建議 71
參考文獻 71

 

1. “MELCOR Computer Code Manuals, Vol. 1: Primer and Users’ Guide, Version 2.2.9541,” SAND 2017-0455 O, Sandia National Laboratories, January 2017
2. R. E. HENRY, C. Y. PAIK, and C. E. HENRY, “MAAP5-Modular Accident Analysis Program for LWR Power Plants,” Fauske & Associates, Inc., Burr Ridge, Illinois (2008).
3. 國立清華大學工程與系統科學系 李敏 等，「核電廠安全度評估方法之理論與應用」，中華民國85年6月
4. IAEA Safty Guide No. NS-G-2.15,”Severe Accident Management Guidelines” ,July ,2009
5. N. C. Rasmussen, et al., “Reactor Safety Study: An Assessment of Accident Risks in U.S. Commercial Nuclear Power Plant,” NUREG-75/014(WASH-1400), U.S. NRC, October 1975.
6. 國立清華大學工程與系統科學系 陳建智 「利用MAAP 4.0.4程式評估龍門電廠嚴重事故下圍阻體物理現象及抑緩措施功能」中華民國90年
7. “Final Safety Analysis Report of Lungmen Nuclear Power Station,” Taiwan Power Company ,2007
8. 國立清華大學工程與系統科學系 王德全 「用MAAP 5程式量化嚴重事故下爐內氫氣產生量之不準度研究與爐外溶渣冷卻靈敏度分析」中華民國109年
9. “Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 User’s Manual”, May, 2020
10. Fauske & Associate ,“MAAP 5.03 User Manual” November, 2008
11. NUREG/CR-5582,”Lower head failure experiments and analysis”, Sandia National Laboratory
12. Ronald J, Lipinski “A Model for Boiling and Dryout in Particle Beds”,1980
13. Robert E. Henry”A Study Of One and Two Component Two Phases Critical Flows At Low Qualiyies” 1968
14. C. PAIK and Q. ZHOU, ‘‘MAAP5 Users’ Group Workshop,” Fauske & Associates, Inc. Taipei, Taiwan (2012)
15. Reliability Engineering and System safety, Vol. 89, pp.305-330, 2005 R. L. Iman, “Latin Hypercube Sampling (Program User’s Guide),” OSTI 5577631 ,1980
16. J.C.Helton and F.J.Davis “Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems”, Sandia National Laboratory,2002
17. Stuart A., Ord K., Arnold S., Kendall's Advanced Theory of Statistics: Volume 2A—Classical Inference & the Linear Model,1999
18. J.C.Helton, Jon Craig and F.J.Davis, “Sampling-Based Methods for Uncertainty and Sensitivity Analysis”, Sandia National Labs, 2000
19. Pearson, Karl “On the Criterion That a Given System of Deviations from the Probable in the Case of a Correlated System of Variables Is Such That It Can Be Reasonably Supposed to Have Arisen from Random Sampling” Philosophical Magazine Series 50(302):157-175.
20. M. D. McKay, R. J. Davis, and W. J. Conover, “A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code” Technometrics (American Statistical Association), Vol 21, May 1979
21. T. C. Wang and M. Lee, “Uncertainty Qualification Using MAAP Code of In vessel Hydrogen Generation In a Severe Accident at Advanced Boiling Water Reactor”, 2018