ML22053A190
| ML22053A190 | |
| Person / Time | |
|---|---|
| Issue date: | 02/28/2022 |
| From: | Sunny Chen, Chiang C, Ferng Y, Shih C, Kirk Tien, Jamie Wang, Yu T Office of Nuclear Regulatory Research, National Tsing Hua Univ, Institute of Nuclear Science, Taiwan, Taiwan Power Co |
| To: | |
| Malone Tina | |
| References | |
| NUREG/IA-0528 | |
| Download: ML22053A190 (54) | |
Text
NUREG/IA- 0528
Uncertainty Analysis of Main Stea m Line Break Accident f or Maanshan PWR with RELAP5/DAKOTA
Prepared by:
Chunkuan Shih, Jong-Rong Wang, Chih-Chia Chiang, Yuh-Ming Ferng, Shao-Wen Chen, and Tzu-Yao Yu*
National Tsing Hua University and Nuclear and New Energy Education and Research Foundation 101 Section 2, Kuang Fu Rd.,
HsinChu, Taiwan
- Department of Nuclear Safety, Taiwan Power Company 242, Section 3, Roosevelt Rd., Zhongzheng District, Taipei, Taiwan
K. Tien, NRC Project Manager
Division of Systems Analysis Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, DC 20555-0001
Manuscript Completed: September 2021 Date Published: February 2022
Prepared as part of The Agreement on Research Participation and Technical Exchange Under the Thermal-Hydraulic Code Applications and Maintenance Program (CAMP)
Published by U.S. Nuclear Regulatory Commission AVAILABILITY OF REFERENCE MATERIALS IN NRC PUBLICATIONS
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NUREG/IA- 0528
International Agreement Report
Uncertainty Analysis of Main Steam Line Break Accident for Maanshan PWR with RELAP5/DAKOTA
Prepared by:
Chunkuan Shih, Jong-Rong Wang, Chih-Chia Chiang, Yuh-Ming Ferng, Shao-Wen Chen, and Tzu-Yao Yu*
National Tsing Hua University and Nuclear and New Energy Education and Research Foundation 101 Section 2, Kuang Fu Rd.,
HsinChu, Taiwan
- Department of Nuclear Safety, Taiwan Power Company 242, Section 3, Roosevelt Rd., Zhongzheng District, Taipei, Taiwan
K. Tien, NRC Project Manager
Division of Systems Analysis Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, DC 20555-0001
Manuscript Completed: September 2021 Date Published: February 2022
Prepared as part of The Agreement on Research Participation and Technical Exchange Under the Thermal-Hydraulic Code Applications and Maintenance Program (CAMP)
Published by U.S. Nuclear Regulatory Commission
ABSTRACT
In our previous study, the RELAP5/SNAP model of Maanshan PWR nuclear power plant is established. This model was used to perform the analysis of Main Steam Line break (MSLB) inside-containment transient. The analysis results of RELAP5/SNAP are consistent with the FSAR data. In this study, the main purpose is to perform an uncertainty analysis for Maanshan MSLB by using RELAP5/SNAP model and DAKOTA code. Total 21 parameters which include initial power, accumulator volume, injection water temperature, injection flow, rod material thermal conductivity, discharge coefficient for break, slug flow drag, etc. are evaluated in this analysis. According to the uncertainty analysis results, discharge coefficient for break, slug flow drag, and annular -mist flow drag have larger effect in the calculation of break flow, and slug flow drag and annular-mist flow drag have larger effect in the calculation of void fraction.
iii
FOREWORD
RELAP5 is a thermal hydraulic analysis code and has been designed to perform best-estimate analysis of LOCA, operational transients, and other accident scenarios for nuclear power plants.
Traditionally, RELAP5 models were developed by ASCII files, which was not intelligible for the beginners of computer analysis. A graphic input interface code-SNAP is developed by Applied Programming Technology Inc. and can process the establishment of the RELAP5 models more conveniently.
Taiwan and the United States have signed an agreement on CAMP to obtain the authorization of these codes. NTHU is the organization in Taiwan responsible for the application RELAP5 and SNAP in safety analysis of nuclear power plants. Hence, the RELAP5/SNAP model of Maanshan PWR nuclear power plant has been developed. T o expand the applicability of the RELAP5/SNAP model, a thermal hydraulic analysis methodology of the postulated MSLB is established in our previous study. By comparing the RELAP5 results and FSAR data, it indicates that the RELAP5/SNAP model has a respectable accuracy. Hence, this model was used to perform an uncertainty analysis of MSLB to understand the parameters effects in this study.
v
TABLE OF CONTENTS
ABSTRACT................................................................................................................... iii
FOREWORD................................................................................................................... v
TABLE OF CONTENTS................................................................................................ vii
LIST OF FIGURES......................................................................................................... ix
LIST OF TABLES.......................................................................................................... xi
EXECUTIVE
SUMMARY
............................................................................................. xiii
ABBREVIATIONS AND ACRONYMS.......................................................................... xv
1 INTRODUCTION........................................................................................................ 1
2 MODEL AND METHODOLOGY DESCRIPTION....................................................... 5 2.1 RELAP5/SNAP Model Description..................................................................................5 2.2 Analysis Methodology Description..................................................................................5
3 UNCERTAINTY ANALYSIS RESULTS................................................................... 15
4 CONCLUSION.......................................................................................................... 29
5 REFERENCES......................................................................................................... 31
vii
LIST OF FIGURES
Figure 1-1 Thermal Hydraulic Analysis Schematic Diagram [5]................................................ 2 Figure 1-2 Uncertainty Analysis Schematic Diagram [5]........................................................... 3 Figure 2-1 The RELAP5/SNAP Model of Maanshan NPP........................................................ 7 Figure 2-2 The Flow Chart of Analysis Methodology................................................................ 8 Figure 2-3 Uncertainty Configuration Interface......................................................................... 9 Figure 3-1 The Uncertainty Analysis Results of PCT.............................................................. 16 Figure 3-2 The Uncertainty Analysis Results of HHSI Mass Flow Rate.................................. 17 Figure 3-3 The Uncertainty Analysis Results of Core Collapsed Water Level........................ 18 Figure 3-4 The Uncertainty Analysis Results of Primary Side Pressure................................. 19 Figure 3-5 The Uncertainty Analysis Results of Secondary Side Pressure............................ 20 Figure 3-6 The Uncertainty Analysis Results of SG Heat Transfer Coefficient....................... 21 Figure 3-7 The Uncertainty Analysis Results of SG Void Fraction.......................................... 22 Figure 3-8 The Uncertainty Analysis Results of SG WRWL................................................... 23 Figure 3-9 The Uncertainty Analysis Results of SG NRWL.................................................... 24 Figure 3 -10 The Uncertainty Analysis Results of Break Mass Flow Rate................................. 25 Figure 3-11 The Parameters Correlation Size in Break Mass Flow Rate................................. 26 Figure 3-12 The Parameters Correlation Size in Void Fraction................................................ 27
ix
LIST OF TABLES
Table 2-1 Initial Conditions of Maanshan NPP........................................................................ 10 Table 2-2 Sequence of Events in MSLB.................................................................................. 11 Table 2-3 The Key Parameters of Uncertainty Analysis [6-8 ].................................................. 12 Table 2-4 Minimum Number of Code Runs for One-Side and Two-Side Tolerance Limits
[9-10]........................................................................................................................ 13
xi
EXECUTIVE
SUMMARY
RELAP5 which is MOD3.3 Patch05 code was developed by Idaho National Engineering Laboratory for light water reactor transient analysis. RELAP5 can simulate the operation of NPPs under normal operations and transients, provide an accurate and rapid analysis patterns for NPP systems, and provide transients analysis results to NPPs and regulatory commission.
RELAP5/MOD3.3 code is featured with nonhomogeneous and non-equilibrium model for the two-phase system and is a one-dimensional thermal hydraulic analysis c ode which uses Semi-Implicit method numerical scheme. RELAP5/MOD3.3 code also includes some models to deal with some particular phenomenon, such as critical flow model, reflooding model, metal -water reaction model etc.
SNAP which is developed by Applied Programming Technology, Inc. is a graphic interface code and different from the traditional input deck in ASCII files. SNAP can help users to easily build the RELAP5 models in a graphic interface. Furthermore, SNAP has the animation function to present RELAP5 analysis results. Hence, RELAP5/MOD3.3 and SNAP codes were used in this study.
DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) is developed by Sandia National Laboratory. DAKOTA supplies a sim ple setting interface for researchers to perform different iteration method with the analysis code (ex: RELAP5). Therefore, uncertainty analysis can be determined by some simulations with different input parameter s sets in RELAP5 and DAKOTA.
Maanshan NPP which is a PWR is located on the southern coast of Taiwan. The reactor coolant system of Maanshan NPP has three loops, each of which includes a reactor coolant pump and a steam generator. In addition, a pressurizer connects to the hot-leg piping in loop 2. In our previous study, to analyze the MSLB transient, the RELAP5/SNAP model of Maanshan NPP was established. The analysis results of RELAP5 were compared with the FSAR data.
According to the compared RELAP5 results and FSAR data, it indicates that the RELAP5/ SNAP model has the ability to predict the MSLB transient.
However, to understand the effects of parameters for MSLB transient, the uncertainty analysis by using the RELAP5/SNAP model and DAKOTA code was performed in this study. Total 21 parameters which include 13 parameters of NPP and 8 parameters of RELAP5 model are evaluated in this analysis. These parameters of NPP are initial power, accumulator volume, accumulator temperature, accumulator pressure, accumulator boron concentration, injection water temperature, high pressure injection flow, low pressure injection flow, rod material thermal conductivity, rod material heat capacity, RCP initial speed, RCP inertia, and pressurizer initial pressure. In addition, the parameters of RELAP5 model are discharge coefficient for break, two-phase friction, junction form loss, bubbly flow drag, s lug flow drag, annular-mist flow drag, dispersed flow drag, and reflood drag. The number of samples was determined by Wilks formula to generate the 95/95 confidence level and probability. Additionally, Pearson product-moment correlation coefficients were calculated to confirm the parameters correlation size in the MSLB. The uncertainty analysis results indicate that the discharge coefficient for break, slug flow drag, and annular -mist flow drag have larger correlation size in the break flow, and slug flow drag and annular-mist flow drag have larger correlation size in the void fraction.
xiii
ABBREVIATIONS AND ACRONYMS
ACC Accumulator CAMP Code Applications and Maintenance Program DAKOTA Design Analysis Kit for Optimization and Terascale Applications ECCS Emergency Core Cooling System FSAR Final Safety Analysis Report HHSI High Head Safety Injection kg kilogram(s)
LHSI Low Head Safety Injection LOCA Loss of Coolant Accident MPa Megapascal(s)
MSIV Main Steam Isolation Valves MSLB Main Steam Line Break MUR Measurement Uncertainty Recapture NPP Nuclear Power Plant NRC Nuclear Regulatory Commission NRWL Narrow Range Water Level NSSS Nuclear Steam Supply System NTHU National Tsing Hua University PWR Pressurized Light Water Reactor RCS Reactor Coolant System RCP Reactor Coolant Pump RPV Reactor Pressure Vessel SG Steam Generator SI Safety Injection SNAP Symbolic Nuclear Analysis Program WRWL Wide Range Water Level
xv
1 INTRODUCTION
Maanshan NPP which located on the southern coast of Taiwan is the third NPP in Taiwan and the only one PWR. The NSSS of Maanshan NPP is built by Westinghouse and has three loops, which can be divided into primary side and secondary side. The original power of Maanshan NPP is 277 5 MWt. After MUR finished, the power of Maanshan NPP is 2822 MWt. There is a RCP and a SG in each loop of the primary side. Pressurizer connects to the hot leg of the second loop, which can adjust the pressure of the RCS. In addition, each loop equipped with an ACC injection system, a HHSI and a LHSI.
RELAP5, DAKOTA and SNAP codes are used in this study. RELAP5 is a thermal hydraulic analysis code and can simulate and analyze NPP transients [1]. We use the MOD3.3 Patch05 version in our studies. DAKOTA can couple with RELAP5 to perform uncertainty analysis [2].
SNAP can process the input and output of RELAP5 and DAKOTA in thermal hydraulic analysis and uncertainty analysis [3].
In our previous study [4], the RELAP5/SNAP model of Maanshan PWR NPP for MSLB transient is established. The analysis results of RELAP5 were compared with the FSAR data. It indicates that the RELAP5/ SNAP model has the ability to predict the MSLB transient. In this thermal hydraulic analysis, the values of parameters are constant which causes the only one result for RELAP5 calculation as Figure 1-1 [5]. However, the values of parameters have the variation in uncertainty analysis. This causes the different result for RELAP5 calculation as Figure 1-2 [5 ].
Therefore, to understand the variation effects of parameters in the RELAP5 calculation for MSLB transient, the uncertainty analysis by using the RELAP5/SNAP model and DAKOTA code was performed in this study. Total 21 parameters which include 13 parameters of NPP and 8 parameters of RELAP5 model are evaluated in this uncertainty analysis. The 13 parameters of NPP parameters are initial power, accumulator volume, accumulator temperature, accumulator pressure, accumulator boron concentration, injection water temperature, high pressure injection flow, low pressure injection flow, rod material thermal conductivity, rod material heat capacity, RCP initial speed, RCP inertia, and pressurizer initial pressure. The 8 parameters of RELAP5 model are discharge coefficient for break, two-phase friction, junction form loss, bubbly flow drag, s lug flow drag, annular-mist flow drag, dispersed flow drag, and reflood drag. The distributions and ranges of the parameters are from the references [6-8 ]. In addition, the number of samples was determined by Wilks formula [9-10] to generate the 95/95 confidence level and probability. Finally, to confirm the parameters correlation size in the MSLB transient, Pearson product-moment correlation coefficients [11 ] were calculated.
1 Figure 1-1 Thermal Hydraulic Analysis Schematic Diagram [5]
2 Figure 1-2 Uncertainty Analysis Schematic Diagram [5]
3
2 MODEL AND METHODOLOGY DESCRIPTION
2.1 RELAP5/SNAP Model Description
Figure 2-1 shows the RELAP5/SNAP model of Maanshan NPP. This model was established in our previous study [4]. This model can be divided into p rimary side loop, secondary side loop, and ECCS and established by using Pipe, Valve, Branch, Pump and Single Volume, and Time Dependent Junction components. There are three loops in this model. Every loop has a RCP and SG. A pressurizer which can adjust the pressure of RCS with the spray valves connects to the hot leg in the second loop. Some Branch components and heat structure components were used to simulate the reactor vessel and fuels channels. Table 2-1 presents the ini tial conditions of the model for MSLB transient. In addition, the sequence of MSLB transient is shown in Table 2-2.
2.2 Analysis Methodology Description
Figure 2-2 shows the analysis methodology of Maanshan NPP MSLB transient. The thermal hydraulic analysis was performed in our previous study [4] and the flow chart of analysis process is shown in Figure 2-2 green region. The main steps are as follows:
The model is established.
To perform the steady-state analysis and to confirm the analysis results of steady-state.
After the steady-state analysis results is consistent with the FSAR data, the transient analysis is performed.
To compare the transient analysis results with the FSAR data.
The compared results indicate that the RELAP5/SNAP model has a respectable accuracy [4].
Hence, this RELAP5/SNAP model is used to perform an uncertainty analysis in this study and the flow chart of analysis process is shown in Figure 2-2 red region. The main steps are as follows:
To identify the parameters which are evaluated.
To identify the distributions and ranges of parameters.
To generate the sample number of code runs by using Wilks formula.
To input the above data in the DAKOTA code and the screen of uncertainty configuration is shown in Figure 2-3.
To perform the uncertainty analysis by using DAKOTA and RELAP5/SNAP model.
Table 2-3 lists the distributions and ranges of parameters. Total 21 parameters which include 13 parameters of NPP and 8 parameters of RELAP5/SNAP model are evaluated in the uncertainty analysis. Table 2-4 presents the required minimum number of RELAP5 runs which is dependent of the values of confidence level and probability. Wilks formula [9 -10] was employed to determinate the minimum number of runs and as follows:
5 1-n for one-side tolerance limit 1-n-n(1 -) n-1 for two-side tolerance limit
Where is probability, is the confidence level, and n denotes the number of code runs.
Hence, the required minimum number of RELAP5 runs for one-side tolerance limit is 59 to generate the 95/95 confidence level and probability in this study. Finally, to confirm the parameters correlation size in the MSLB transient, Pearson product-moment correlation coefficient [11] was calculated by using the analysis results and the equation is as follows:
Where r is the Pearson product-moment correlation coefficient, n is the number of samples, and x and y denote two quantities.
6 Figure 2-1 The RELAP5/SNAP Model of Maanshan NPP
7 Figure 2-2 The Flow Chart of Analysis Methodology
8 Figure 2-3 Uncertainty Configuration Interface
9 Table 2-1 Initial Conditions of Maanshan NPP
Parameters RELAP5 Power (MWt) 2900 RCS temperature (K) 582.97 Primary side pressure (MPa) 15.862 Secondary side pressure (MPa) 6.845 Scram setpoint (MPa) 12.8 SI signal setpoint (MPa) 11.8 ECCS electric delay time (s) 27 ACC pressure (MPa) 4.24 Auxiliary feedwater flow rate (kg/s) 7.965 Break size (m2) 0.436
10 Table 2-2 Sequence of Events in MSLB
Events Time (sec)
Steady-state 0 Pipe break 400 Reactor scram 418 SI signal 427 Auxiliary feedwater 446 HHSI 447 Accumulator injection 541 End of Accumulator injection 1219 Transient end 2000
11 Table 2-3 The Key Parameters of Uncertainty Analysis [6-8 ]
Parameters Distribution Range
Initial power Uniform -1.02% ~ 1.02%
Accumulator volume Uniform 985 ~ 1015 Accumulator Uniform 100 ~ 150 temperature Accumulator pressure Uniform 632 ~ 680 Accumulator boron Uniform 2300 ~ 2500 concentration Injection water Uniform 70 ~ 130 temperature High pressure injection Uniform -5% ~ 5%
The parameter s of NPP flow Low pressure injection Uniform -5% ~ 5%
flow Rod material thermal Normal -20% ~ 20%
conductivity Rod material heat Normal -10% ~ 10%
capacity RCP initial speed Uniform 1180 ~ 1190 RCP inertia Uniform -5% ~ 5%
Pressurizer Initial Uniform 2200 ~ 2300 pressure
Discharge coefficient for Uniform -20% ~ 20%
break Tw o-phase friction Uniform 0.5 ~ 1.5 The parameters of Junction form loss Lognormal = 0.1 (0.05=~=0.2) =
RELAP5/SNAP model By==dr = Uform = 0.5=~=1.5 =
Slug=fl=dr = Uform = 0.5=~=1.5 =
A -mis=dr = Uform = 0.5=~=1.5 =
Dispersed=fl=dr = Uform = 0.5=~=1.5 =
Refl = Uform = 0.5=~=1.5 =
=
12 Table 2-4 Minimum Number of Code Runs for One-Side and Two-Side Tolerance Limits
[9-10]
One-side tolerance limits Two-side tolerance limits 0.90 0.95 0.99 0.90 0.95 0.99 0.90 22 45 230 38 77 388 0.95 29 59 299 46 93 473 0.99 44 90 459 64 130 662
13
3 UNCERTAINTY ANALYSIS RESULTS
Figure 3-1~3-11 are the analysis results of uncertainty analysis in this study. In general, t he safety analysis of transients focus on the PCT criteria which is 2200 ºF in 10 CFR 50.46. Figure 3-1 shows the PCT results. It indicates that the PCT results ar e lower than the criteria of 2200
ºF. Additionally, the variation of PCT results are more obvious after 600 sec. That is because HHSI injects water to the core in this duration (see Figure 3-2). This causes the variation of core water level (see Figure 3-3) which affects the variation of PCT.
Figure 3-4 and 3-5 present the results of primary side and secondary side pressure. By compared the results of primary side and secondary side pressure, it indicates that the variation of secondary side pressure results are more obvious in 600~1000 sec. This may be caused by the SG heat transfer coefficient. Figure 3-6 shows that the SG heat transfer coefficient has more variation in 600~1000 sec. Figure 3-7 presents the void fraction results which have larger variation than other parameters. Because the void fraction is also related to the water level, it also can see the similar symptom in the WRWL and NRWL (see Figure 3 -8 and 3-9). In the analysis of MSLB transient, one of important parameters is the break mass flow rate. Figure 3-10 shows the results of break mass flow rate. It indicates that the variation of break mass flow rate results are more obvious in 600~1000 sec and after 3000 sec.
To confirm the correlation size of parameters in the void fraction and break mass flow rate, Pearson product-moment correlation coefficients were calculated. Figure 3-11 shows the results of Pearson product-moment correlation coefficient for break mass flow rate. It indicates that the maximum correlation size is the d ischarge coefficient. In addition, the s lug flow drag and annular-mist flow drag also have the larger correlation size in the calculation of break mass flow rate. Therefore, the d ischarge coefficient, slug flow drag, and annular -mist flow drag may dominate the break mass flow rate. Figure 3-12 presents the results of Pearson product-moment correlation coefficient for void fraction. It indicates that the maximum correlation size is the slug flow drag. The second correlation size is the annular-mist flow drag. This indicates that slug flow drag and annular-mist flow drag may dominate the calculation of void fraction. In addition, it also can find that the parameters of RELAP5/SNAP model have the larger effects than the parameters of NPP in the void fraction and break mass flow rate.
15 Figure 3-1 The Uncertainty Analysis Results of PCT
16 Figure 3-2 The Uncertainty Analysis Results of HHSI Mass Flow Rate
17 Figure 3-3 The Uncertainty Analysis Results of Core Collapsed Water Level
18 Figure 3-4 The Uncertainty Analysis Results of Primary Side Pressure
19 Figure 3-5 The Uncertainty Analysis Results of Secondary Side Pressure
20 Figure 3-6 The Uncertainty Analysis Results of SG Heat Transfer Coefficient
21 Figure 3-7 The Uncertainty Analysis Results of SG Void Fraction
22 Figure 3-8 The Uncertainty Analysis Results of SG WRWL
23 Figure 3-9 The Uncertainty Analysis Results of SG NRWL
24 Figure 3-10 The Uncertainty Analysis Results of Break Mass Flow Rate
25 Discharge coefficient
Slug flow drag
Annular-mist flow drag
Formloss
Power
Pressurizer pressure
Wall drag
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Figure 3-11 The Parameters Correlation Size in Break Mass Flow Rate
26 Slug flow drag
Annular-mist flow drag
Power
Wall drag
Pressurizer pressure
Low pressure injection flow
0 0.1 0.2 0.3 0.4 0.5 0.6
Figure 3-12 The Parameters Correlation Size in Void Fraction
27
4 CONCLUSION
The RELAP5/SNAP model of Maanshan PWR was used to perform a thermal hydraulic analysis for MSLB in our previous study [4]. The analysis results are similar to the FSAR data [6]. This indicates that the R ELAP5/SNAP model has a respectable accuracy. Therefore, to understand the parameters effects for MSLB, an uncertainty analysis of Maanshan PWR MSLB by using RELAP5/SNAP model and DAKOTA code is performed in this study. This uncertainty analysis evaluates total 21 parameters which include initial power, accumulator volume, injection water temperature, injection flow, rod material thermal conductivity, discharge coefficient for break, slug flow drag, etc. According to the results of uncertainty analysis, in the calculation of break flow, discharge coefficient for break, slug flow drag, and annular -mist flow drag have larger effect. However, in the calculation of void fraction, s lug flow drag and annular-mist flow drag have larger effect.
29
5 REFERENCES
[1] Information Systems Laboratories, Inc., RELAP5/MOD3.3 Code Manual Volume I: Code Structure, System Models, and Solution Methods, Information Systems Laboratories.
[2] Brian M. Adams et al, Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.0 User's Manual, Sandia National Laboratories, Albuquerque, 2014.
[3] Applied Programming Technology, Symbolic Nuclear Analysis Package (SNAP) User's Manual, Applied Programming Technology Inc., Bloomsburg, 2007.
[4] Chih-Chia Chiang, The Development and Application of Maanshan RELAP5/SNAP/DAKOTA Model in MSLB Analysis, 2020.
[5] H. Glaeser, GRS Method for Uncertainty and Sensitivity Evaluation of Code Results and Applications, Science and Technology of Nuclear Installations, 2008.
[6] Taiwan Power Company, Final Safety Analysis Report for Maanshan Nuclear Power Station Units 1&2 (FSAR), 1983.
[7] M. Kyncl, R. Pernica, Assessment of RELAP5/MOD3.3 and TRACE V5.0 Computer Codes against LOCA Test Data from PSB -VVER Test Facility, NUREG /IA-0435, 2013.
[8] Byung Gil, Huh, Best-Estimate Calculation for LBLOCA Analysis of APR1400 Using TRACE Code, Fall 2018 CAMP meeting, 2018.
[9] Wilks, S. S., Statistical Prediction with Special Reference to The Problem of Tolerance Limits, Annals of Mathematical Statistics, Vol. 13, 400, 1942.
[10] Guba A., M. Makai, and L. Pal, Statistical Aspects of Best Estimate Method-I, Reliability Engineering and System Safety, Vol. 80, 2003.
[11] R.F. Bartlett, Linear Modeling of Pearsons Product Moment Correlation Coefficient: An Application of Fishers z-Transformation, Journal of the Royal Statistical Society Series D (The Statistician), Vol. 42, No. 1, 1993.
31
NUREG/IA- 0528
Uncertainty Analysis of Main Steam Line Break Accident for Maanshan February 2022 PWR with RELAP5/DAKOTA
Chunkuan Shih, Jong-Rong Wang, Chih-Chia Chiang, Yuh-Ming Ferng, Shao-Technical Wen Chen, and Tzu-Yao Yu*
National Tsing Hua University and Nuclear and New Energy Education and Research Foundation, 101 Section 2, Kuang Fu Rd., HsinChu, Taiwan
- Department of Nuclear Safety, Taiwan Power Company 242, Section 3, Roosevelt Rd., Zhongzheng District, Taipei, Taiwan
Division of Systems Analysis Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, D.C. 20555-0001
K. Tien, NRC Project Manager
In our previous study, the RELAP5/SNAP model of Maanshan PWR nuclear power plant is established. This model was used to perform the analysis of Main Steam Line break (MSLB) inside-containment transient. The analysis results of RELAP5/SNAP are consistent with the FSAR data. In this study, the main purpose is to perform an uncertainty analysis for Maanshan MSLB by using RELAP5/SNAP model and DAKOTA code.
Total 21 parameters which include initial power, accumulator volume, injection water temperature, injection flow, rod material thermal conductivity, discharge coefficient for break, slug flow drag, etc. are evaluated in this analysis. According to the uncertainty analysis results, discharge coefficient for break, slug flow drag, and annular-mist flow drag have larger effect in the calculation of break flow, and slug flow drag and annular-mist flow drag have larger effect in the calculation of void fraction.
MSLB, PWR, RELAP5, DAKOTA, Maanshan
NUREG/IA-0528 Uncertainty Analysis of Main Steam Line Break Accident for Maanshan February 2022 PWR with RELAP5/DAKOTA