RESULTS FROM THE APPLICATION OF UNCERTAINTY METHODS IN THE UMS AND IN BEMUSE

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1 RESULTS FROM THE APPLICATION OF UNCERTAINTY METHODS IN THE UMS AND IN BEMUSE A. Petruzzi (UNIPI) Presenteb by M. Adorni (UNIPI) Kick off meeting on Uncertainty Analyses for Criticality Safety Assessment IRSN, Fontenay-aux-Roses (France) 5-6 December 2007

2 The UMS Summary of the Uncertainty Methods in UMS AEAT, UMAE, GRS & IPSN, ENUSA Comparison between Uncertainty Methods UMS Applications The BEMUSE Programme Phase II Phase III CONTENTS Conclusions 2/61

3 THE UMS The Uncertainty Methods Study (UMS) Group, following a mandate from CSNI, has compared five methods (AEAW, GRS, UMAE, IPSN, ENUSA) for calculating the uncertainty in the predictions of advanced best estimate thermalhydraulic codes OBJECTIVES 1. To gain insights into differences between features of the methods by: - comparing the different methods, step by step, when applied to the same problem; - comparing the uncertainties predicted for specified output quantities of interest; - comparing the uncertainties predicted with measured values; - drowning conclusions about the suitability of method. 2. To inform those who will take decisions on conducting uncertainty analyses, for example in the licensing requirements. 3/61

4 THE UMS A Small Break LOCA (SBLOCA) experiment performed in the Japanese facility LSTF was selected as objective of the analysis of the international UMS Group 4/61

5 Five Methods compared: THE UMS Pisa Method (UMAE): extrapolation from integral experiments; GRS, IPSN, ENUSA methods: identify and combine input uncertainties, using subjective Probability Distribution Function (pdf); AEAT method: performs a bounding analysis 5/61

6 SUMMARY OF UNCERTAINTY METHODS IN UMS AEAT METHOD The uncertainty statements must be in the form of reasonable uncertainty ranges. This is defined as the smallest range of values that includes all values for which there is reasonable certainty that they are consistent with the all available evidence. Emphasis is given to the use of experimental data independent from those used by code developers to derive suitable uncertainty values. 6/61

7 SUMMARY OF UNCERTAINTY METHODS IN UMS UMAE METHOD The basic idea is to use the accuracy gathered from the comparison between measured and calculated time trends. These must be related to qualified ITF. No need to select input uncertainties or ranges. Emphasis is given to the calculation qualification process (quality of experimental data, of dalization, of code results checked). Qualitative and quantitative criteria have been proposed to accept suitable calculation results. Fulfilments of various conditions are needed to use the method. 7/61

8 SUMMARY OF UNCERTAINTY METHODS IN UMS UMAE METHOD General Qualification Process b Code a i j Plant dalization Plant calculation GI Generic experimental data Stop of the process NO h Nodalization and user qualification FG FG g NO ITF Nodalizations Specific experimental data ITF Calculation c e d k Demonstration of Similarity ( ) (Phemena Analysis) (Scaling Laws) YES Accuracy Quantification ( ) Accuracy Extrapolation ( ) f l m ASM Calculation LN ( ) ( ) Special methodology developed Uncertainty n 8/61

9 SUMMARY OF UNCERTAINTY METHODS IN UMS GRS & IPSN METHODS The amount and the type of selected uncertain input parameters distinguishes the two methods. The methods have the capability to consider the effects of code models, BIC, solution algorithms, etc., upon calculation results (all input parameters potentially affecting uncertainties). Well established concepts from probability calculus and statistics are used. The selection of an ITF experiment makes it possible to take decisions on dominant phemena. A random value for each uncertain parameter is selected according to the specified subjective probability distribution. Use of the Wilks formula for the minimum number of code calculations. Sensitivity measures are derived. 9/61

10 SUMMARY OF UNCERTAINTY METHODS IN UMS This is based upon CSAU. ENUSA METHOD The PIRT (Phemena Identification and Ranking Table) process is used to select a reasonable number of input uncertain parameters: same objective as for the AEAT method. The ranges of variations are fixed adopting a similar approach as the AEAT method. In order to minimize the number of calculation runs, the process of combination of input uncertainties is basically the same as adopted by GRS and IPSN. This makes the difference between ENUSA and CSAU. 10/61

11 COMPARISON BETWEEN UNCERTAINTY METHODS SIMILARITY AMONG THE METHODS 1) All methods have the capability to calculate the error ranges as a function of time (continuous uncertainty bands). 2) Each method consists of a limited number of main steps and a larger number of sub-steps that appear from the method use. 3) Each method requires resources of man-years to be used by a competent technician on the first time (status 1998). 4) Some features of each method may be connected with the features of the adopted code. 5) Each method requires the selection of a code and of a transient scenario. 6) Each method makes use of experimental data, to a different extent and at different levels. 7) Each method needs a qualified code. 8) Each method aims at providing information useful to a decisionmaker. 11/61

12 COMPARISON BETWEEN UNCERTAINTY METHODS MAIN CHARACTERISTICS OF CONSIDERED UNCERTAINTY METHODS GENERAL CHARACTERISTICS AEAT CSAU GRS UMAE 1 2 Restriction on the number of input uncertain parameters Deriving input uncertainty ranges n.a. 3 4 Assigning subjective probability distributions Use of statistics (a) 5 6 Use of response surface technique Necessity of specific data for scaling (b) 7 Quantification of code calculation accuracy 8 Use of expert groups 9 Use of biases on output (a) : To a limited extent. (b) : At a qualitative level, during code validation. 12/61

13 COMPARISON BETWEEN UNCERTAINTY METHODS COMPARISON AMONG RELEVANT FEATURES FEATURE Determination of uncertain parameters and of input uncertainty ranges Selection of uncertain parameter values within the determined range for code calculations Support of identification and ranking of main parameter and modelling uncertainties Account for state of kwledge of uncertain parameters (distribution of input uncertainties) Probabilistic uncertainty statement Statistical rigour Kwledge of code specifics may reduce resources necessary to the analysis Number of code runs independent from number of input and output parameters Quantitative information about influence of a limited number of code runs Continuous-valued output parameters Sensitivity measures of input parameters on output parameters AEAT experts experts n.a. CSAU experts experts GRS experts random selection UMAE (1) t necessary (1) Differences between experimental and used input data. 13/61

14 COMPARISON BETWEEN UNCERTAINTY METHODS 14/61

15 COMPARISON BETWEEN UNCERTAINTY METHODS 15/61

16 COMPARISON BETWEEN UNCERTAINTY METHODS 16/61

17 COMPARISON BETWEEN UNCERTAINTY METHODS 17/61

18 COMPARISON BETWEEN UNCERTAINTY METHODS 18/61

19 COMPARISON BETWEEN UNCERTAINTY METHODS 19/61

20 COMPARISON BETWEEN UNCERTAINTY METHODS 20/61

21 UMS APPLICATION UNCERTAINTY IN UP PRESSURE PREDICTED BY THE VARIOUS METHODS 21/61

22 UMS APPLICATION UNCERTAINTY IN MASS INVENTORY PREDICTED BY THE VARIOUS METHODS 22/61

23 UMS APPLICATION UNCERTAINTY IN ROD SURFACE TEMPERATURE PREDICTED BY THE VARIOUS METHODS 23/61

24 UMS APPLICATION AMPLITUDE OF UNCERTAINTY BANDS FOR PRESSURE 24/61

25 UMS APPLICATION AMPLITUDE OF UNCERTAINTY BANDS FOR ROD SURFACE TEMPERATURE 25/61

26 OECD BEMUSE BEMUSE PROGRAMME Objectives Description of the Work LOFT Facility and Test L2-5 PARTICIPANTS RESULTS (PHASE II) Nodalization Qualification Qualitative Accuracy Evaluation Quantitative Accuracy Evaluation Sensitivity Study PARTICIPANTS RESULTS (PHASE III) 26/61

27 BEMUSE: Objectives The BEMUSE Programme has been promoted by the Working Group on Accident Management and Analysis (GAMA) and endorsed by the Committee on the Safety of Nuclear Installations (CSNI) The Objectives of the activity are: To Evaluate the Practicability, the Quality and the Reliability of Best-Estimate (BE) Methods Including Uncertainty Evaluation in Applications Relevant to Nuclear Reactor Safety To Develop Common Understanding To Promote/Facilitate their use by the Regulatory Bodies and the Industry 27/61

28 BEMUSE: Description of the Work STEP 1: (NEA/SEN/SIN/AMA(2003)8) Phase I: (March 2003 March 2004) Presentation in advance of the uncertainty evaluation methodology to be used by participants Phase II: (September 2003 December 2004) Re-analysis of the ISP-13 exercise, post-test analysis of the LOFT L2-5 test calculation Phase III: (December 2004 April 2006) Uncertainty evaluation of the L2-5 test calculations, and deduced first conclusions on the methods and suggestions for improvement 28/61

29 BEMUSE: Description of the Work STEP 2: (NEA/SEN/SIN/AMA(2003)8) Phase IV: (October 2005 October 2007) Phase V: Best-estimate analysis of the LBLOCA in NPP Sensitivity studies and uncertainty evaluation for the NPP-LB (with and without methodology improvements resulting from Phase III) Phase VI: Status report on the area, classification of the methods, conclusions and recommendations 29/61

30 BEMUSE: Participating Organizations 14 Participating Organizations; 7 TH System Codes; 8 Uncertainty Methodologies 30/61

31 BEMUSE: LOFT Facility 50-MWt PWR with instrumentation to measure and provide data on the TH and nuclear conditions Operation of the LOFT system is typical of large (~1000 MWe) commercial PWR operations. LOFT facility consists of: RPV (core with 1300 unpressurized nuclear FR m) Intact Loop (SG, PRZ and 2 primary CPs connected in parallel) Broken Loop with a simulated pump, simulated SG, 2 break plane orifices, 2 QOBV and 2 isolation valves; A blowdown suppression system consisting of a header, suppression tank and a spray system An ECC injection system consisting of two LPIS pumps, HPIS pumps and two accumulators 31/61

32 BEMUSE: LOFT Facility 32/61

33 BEMUSE: TEST L2-5 DOUBLED-ENDED 200 % COLD LEG BREAK 33/61

34 PARTICIPANTS RESULTS (PHASE II) A CONSISTENT CODE QUALIFICATION PROCESS BASED ON UMAE CRITERIA HAS BEEN APPLIED TO PHASE 2 OF BEMUSE NODALIZATION QUALIFICATION Nodalization Tables Pressures Vs Length Curve QUALITATIVE ACCURACY EVALUATION Resulting Time Sequence of Events Relevant Thermalhydraulic Aspects (RTA) Experimental Time Trends Comparisons Qualitative Judgments QUANTITATIVE ACCURACY EVALUATION Application of the FFTBM 34/61

35 PARTICIPANTS RESULTS (PHASE II) Code Resources 14 Participating Organizations; 7 TH System Codes 35/61

36 PARTICIPANTS RESULTS (PHASE II) NODALIZATION QUALIFICATION Part A Part B 36/61

37 PARTICIPANTS RESULTS (PHASE II) NODALIZATION QUALIFICATION Part A: Nodalization Development 37/61

38 PARTICIPANTS RESULTS (PHASE II) Part B: Steady State Level 38/61

39 PARTICIPANTS RESULTS (PHASE II) Results of the Nodalization Qualification QA and QB should be less than 1. 39/61

40 PARTICIPANTS RESULTS (PHASE II) Results of the Nodalization Qualification Qa Qb CEA [C25] IRSN [C25] NRI-2 [A20] GRS [A12] KFKI [A20] UPI [R5] NRI-1 [R5] UPC [R5] KINS [R5] TAEK [R5] PSI [TR4] EDO [T97] JNES [TM55] KAERI [M23] Global Acceptability Factors Organization's Name 40/61

41 PARTICIPANTS RESULTS (PHASE II) Pressures Length Curve CEA [C25] ( MPa) EDOGIDRO [T97] ( MPa) GRS [A12] ( MPa) IRSN [C25] ( MPa) JNES [TM55] ( MPa) KAERI [M23] ( MPa) KFKI [A20] ( MPa) KINS [R5] ( MPa) NRI-1 [R5] ( MPa) NRI-2 [A20] ( MPa) PSI [TR4] ( MPa) TAEK [R5] ( MPa) UPC [R5] ( MPa) UPI [R5] ( MPa) Experimental Normalized Pressure (-) HL IN HL OUT UT TOP SG OUT LOOP SEAL PUMP OUT CL IN CL OUT LP BAF TAF HL IN SG IN OUT SG NOZZLE PUMP IN Loop Length (m) 41/61

42 PARTICIPANTS RESULTS (PHASE II) QUALITATIVE ACCURACY EVALUATION Resulting Time sequence of Events Time After Experiment Initiation (s) Maximum cladding temperature reached Accumulator emptied LPIS injection terminated CEA [C25] EDOGIDRO [T97] GRS [A12] IRSN [C25] JNES [TM55] KAERI [M23] KFKI [A20] KINS [R5] NRI-1 [R5] NRI-2 [A20] PSI [TR4] TAEK [R5] UPC [R5] UPI [R5] Experimental Time (s) Core cladding fully quenched 42/61

43 PARTICIPANTS RESULTS (PHASE II) Experimental Time Trends Comparisons Qualitative Judgments Pressure (MPa) CEA [C25] EDOGIDRO [T97] GRS [A12] IRSN [C25] JNES [TM55] KAERI [M23] KFKI [A20] KINS [R5] NRI-1 [R5] NRI-2 [A20] PSI [TR4] TAEK [R5] UPC [R5] UPI [R5] EXP: PE-PC-002 Time (s) 43/61

44 PARTICIPANTS RESULTS (PHASE II) Core Geometry and Position for the Hot Rod Cladding Temperatures ZONE 4 = HOT ROD (RODS N = 1) ZONE 3 = HOT CHANNEL (RODS N = 203) ZONE 2 = AVERAGE CHANNEL (RODS N = 876) ZONE 1 = PERIPHERAL CHANNEL (RODS N = 220) CONTROL RODS (RODS N = 137) TAF TOP 1.0 m 2/3 ZONE m 0.4 m BOTTOM BAF ZONE 4: HOT ROD (FUEL ASSEMBLY N 5) - HEIGHT: 2/ J N A B C D E F G H I J K L M N O PCT Min : 5H (0.94 m K) 8 9 PCT MAX = PCT Ref : 5H (0.61 m K) /61

45 PARTICIPANTS RESULTS (PHASE II) Experimental Time Trends Comparisons Qualitative Judgments Temperature (K) CEA [C25] GRS [A12] JNES [TM55] KFKI [A20] NRI-1 [R5] PSI [TR4] UPC [R5] PCTmax: TE-5H EDOGIDRO [T97] IRSN [C25] KAERI [M23] KINS [R5] NRI-2 [A20] TAEK [R5] UPI [R5] PCTmin: TE-5H Time (s) 45/61

46 PARTICIPANTS RESULTS (PHASE II) QUANTITATIVE ACCURACY EVALUATION (AA) tot (AA)p1 (AA)tot 0.35 AA P-1 & AA TOT (AA) p CEA [C25] IRSN [C25] NRI-2 [A20] GRS [A12] KFKI [A20] UPI [R5] NRI-1 [R5] UPC [R5] KINS [R5] Organization's Name TAEK [R5] PSI [TR4] EDO [T97] JNES [TM55] KAERI [M23] 46/61

47 PARTICIPANTS RESULTS (PHASE II) USER S EFFECT ON BEMUSE User effect (UE) is a source of uncertainty (it might result in the largest contribution to the uncertainty) User expertise, Quality and comprehensiveness of the code-user manual Database available for performing the analysis UE is originated by: A) Nodalization development QA; B) Interpreting the supplied (or the available) information, usually incomplete; C) Accepting the steady state performance of the dalization QB; D) Interpreting transient results ( AA, AATOT), planning and performing sensitivity studies, modifying the dalization and finally achieving a reference or an acceptable solution. 47/61

48 PARTICIPANTS RESULTS (PHASE II) USER S EFFECT ON BEMUSE Q a, Q b Qa Qb Global Acceptability Factors & AA TOT (AA) tot (AA)tot CEA [C25] IRSN [C25] NRI-2 [A20] GRS [A12] KFKI [A20] UPI [R5] NRI-1 [R5] UPC [R5] KINS [R5] Organization's Name TAEK [R5] PSI [TR4] EDO [T97] JNES [TM55] KAERI [M23] 48/61

49 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) PARTICIPANT S ORGANIZATIONS TO PHASE III PARTICIPANT CEA (France) GRS (Germany) IRSN (France) KAERI (South Korea) KINS (South Korea) NRI-1 (Czech Republic) UPC (Spain) UNIPI (Italy) CODE CATHARE V2.5: 3-D ATHLET 1.2C CATHARE V2.5: 1-D MARS 2.3 RELAP5 / MOD3.3 RELAP5 / MOD3.3 RELAP5 / MOD3.3 RELAP5 / MOD3.2 49/61

50 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) OUTPUT PARAMETERS Time trend TYPE DEFINITION Envelop value of all the rod surface temperatures: Max_TC Upper plenum pressure: P UP Single valued parameter 1 st PCT 2 nd PCT: after t inj Time of accumulator injection: t inj Time of complete quenching: t que OUTPUT UNCERTAIN PARAMETER LOWER UNCERTAINTY BOUND REFERENCE CALCULATION VALUE EXPERIMENTAL VALUE UPPER UNCERTAINTY BOUND 1 st PCT 1062 K 2 nd PCT 1077 K t inj 16.8 s t que 64.9 s 50/61

51 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) 1300 SINGLE VALUE OUTPUT PARAMETERS 1 st PCT: uncertainty bounds temperature (K) lower uncertainty bound reference computation upper uncertainty bound experiment 500 UPC GRS IRSN UNIPI NRI-1 CEA KAERI KINS organisation 51/61

52 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) 1300 SINGLE VALUE OUTPUT PARAMETERS 2 nd PCT: uncertainty bounds temperature (K) lower uncertainty bound reference computation upper uncertainty bound experiment 500 UPC IRSN GRS NRI-1 UNIPI CEA KINS KAERI organisation 52/61

53 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) SINGLE VALUE OUTPUT PARAMETERS time of accumulator injection: uncertainty bounds time (s) lower uncertainty bound reference computation upper uncertainty bound experiment 0 KINS IRSN CEA GRS KAERI UPC NRI-1 UNIPI organisation 53/61

54 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) 120 SINGLE VALUE OUTPUT PARAMETERS time of complete quench: uncertainty bounds time (s) lower uncertainty bound 20 reference computation upper uncertainty bound experiment 0 UPC NRI-1 CEA KAERI UNIPI GRS IRSN KINS organisation 54/61

55 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) temperature (K) CEA Lower uncertainty bound Reference calculation values Upper uncertainty bound Experimental value temperature (K) IRSN Lower uncertainty bound Reference calculation Upper uncertainty bound Experiment temperature (K) time (s) 1400 MAX_TC-59-Lower bound Max_TC-59-Upper bound 1200 NRI-1 Experiment Reference calculation temperature (K) time (s) UPC Lower uncertainty bound Reference calculation values Upper uncertainty bound Experimental value time (s) / time (s)

56 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) Lower uncertainty bound Reference calculation values Upper uncertainty bound Experimental value temperature (K) Lower uncertainty bound Reference calculation values Upper uncertainty bound Experimental value temperature (K) time (s) time (s) UPI Lower Uncertainty Band Reference Calculation Upper Uncertainty Band Experiment temperature (K) temperature (K) Lower uncertainty bound Reference calculation values Upper uncertainty bound Experimental value time (s) / time (s)

57 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) Maximum cladding temperature: width of the uncertainty band 1 st PCT 2 nd PCT complete core quench CEA GRS IRSN KAERI KINS NRI-1 UNIPI UPC temperature (K) time (s) 57/61

58 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) Upper plenum pressure: width of the uncertainty band 5 pressure MPa CEA GRS IRSN KAERI KINS NRI-1 UNIPI UPC time (s) 58/61

59 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) Study performed by KAERI AN INPORTANT OBSERVATION Direct Monte-Carlo: 3500 code runs performed and several sample of 59 or 93 realization From about 1000 the mean value and the 95 % empirical quantile are almost stabilized. The results for the 1 st PCT are: Mean: 1034 K 95% percentile: 1173 K (to be compared to the value 1219 K obtained for step 7 with 93 computations: -46 K) Comparison to Wilks' formula (α = β = 95%, at order 1 and 2): Each 59 computation, the max value is retained Each 93 computation, the 2 nd max value is retained 59/61

60 PARTICIPANTS RESULTS (PHASE III) Mostly taken from Presentation of A. de Crecy, P. Bazin (CEA): 3 rd BEMUSE Meeting Greble, October 2005 (FRANCE) AN INPORTANT OBSERVATION 1400 Reflood PCT (K) Number of Calculations Mean PCT 95% Reflood PCT Wilks 1st order Upper Wilks 2nd order Upper In accordance with Wilks' formula, the 2 nd order determination is less conservative than the 1 st order one Comparison to Wilks' formula (α = β = 95%, at order 1 and 2): 1 st order: among ~58 values [ ] K, -one is significantly lower than the 3500 code run 95 % quantile (5 % of 58 = 3 cases should be expected) 2 nd order: among ~37 values [ ] K, 1 case is found below 1173 K 60/61

61 CONCLUSIONS CONSISTENT AND ADOPTED APPROACHES TO QUANTIFY UNCERTAINTY HAVE BEEN IDENTIFIED: error does t motonically increase with time SUITABLE UNCERTAINTY METHODS EXIST THE BEMUSE PROGRAMME IS AN IMPORTANT STEP ON THE ROAD TO THE RELIABLE APPLICATION TO THE LICENSING PROCESS OF HIGH-QUALITY BEST-ESTIMATE AND UNCERTAINTY EVALUATION METHODS IT ENJOYS WIDE INTERNATIONAL PARTICIPATION AND THE USE OF DIFFERENT COMPUTATIONAL TOOLS (RELAP5, CATHARE, TRACE, ATHLET, MARS, TECH) 61/61

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