Approaches, Relevant Topics, and Internal Method for Uncertainty Evaluation in Predictions of Thermal-Hydraulic System Codes

Petruzzi, A.; D'Auria, Francesco Saverio

doi:10.1155/2008/325071

Cited by 15 publications

(9 citation statements)

References 8 publications

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“…The common feature is that each option highly depends upon the extensive experimental database, from which uncertainties can be derived. and data adjustment/assimilation [87] A.1.1.1.…”

Section: A11 Best Estimate Plus Uncertainty Methodsmentioning

confidence: 99%

“…The input uncertainty is propagated through code calculations and then the obtained output uncertainty is updated with relevant experimental data applying a Bayesian statistical method for output distribution correction based on error distribution [15]. It is based on adjoint sensitivity-analysis procedure (ASAP), global adjoint sensitivity-analysis procedure (GASAP) [81,82], and data adjustment and assimilation (DAA) methodology [79] by which experimental and calculated data, including the computation of sensitivities (derived from ASAP), are mathematically combined for the prediction of the uncertainty scenarios [87]. The common feature is that each option highly depends upon the extensive experimental database, from which uncertainties can be derived.…”

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confidence: 99%

“…[ 87] . 56 uncertain input parameters (rank correlation coefficient) for the reference reactor large break [ 50], [ 97] Safety is an essential part for the peaceful use of nuclear power generation.…”

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confidence: 99%

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Framework and Strategies for the Introduction of Best Estimate Models Into the Licensing Process

Sollima

Petrangeli

D'Auria

et al. 2009

Volume 4: Codes, Standards, Licensing and Regulatory Issues; Student Paper Competition

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SOMMARIO. SBO and SBLOCA .................................. 48 4.2.4.1.3. Results of the analysis ......................................................... 49 4.2.4.1.4. Decay heat power ................................................................ 49 4.2.4.1.5. Hot rod temperature............................................................. 55 4.2.4.1.6. Analysis of the results .......................................................... 57 4.2.4.1.7. Conclusion ........................................................................... distribution..................... 59 4.2.4.2.3. Model and calculation cases................................................ 60 4.2.4.2.4. Evaluation of the cell probability .......................................... 61 4.2.4.2.5 LIST OF SYMBOLS U (1979) with 1973 ...................................................................................................... 70 Fig. 55 -LARGE reactor sin, 100 s, produced and absorbed power versus height fine model....................................................................................................... 70 Fig. 56 -CHF comparison, 7 MPa (RELAP5/Mod 2)............................................. 73 Fig. 57 -CHF Comparison 3 MPa (RELAP5/Mod2) .............................................. 73 Fig. 58 -LOFT: core cross flow model................................................................... 76 Fig. 59 -LOFT: core temperature .......................................................................... 76 Fig. 60 -LOFT: core mass flow ............................................................................. 77 Fig. 61 -PWR-1000: core cross flow model .......................................................... 78 Fig. 62 -PWR-1000: core temperature comparison.............................................. 79 Fig. 63 -PWR-1000 ...................................... 136 Fig. A.11 -Schematic processes in the Swedish reactor licensing program....... 137 Fig. A.12 -Schematic of steps in the Swedish reactor licensing program .......... 138 Fig. A.13 -VVER 1000, Steady State: Up and SGs (1 to 4) pressure ................ 143 Fig. A.14 -VVER 1000, Steady State: Core inlet mass flowrate......................... 144 Fig. A.15 -VVER 1000, Steady State: Core and SG exchanged power ............. 144 Fig. A.16 -VVER 1000 1 (up to 11000s)........ 160 Fig. A.44 -Pressure in the upper plenum in the transient 2 (up to 8000s).......... 160 Fig. A.45 -Pressure in the upper plenum in the transient 1 (up to 1200s).......... 161 Fig. A.46 -Pressure in the upper plenum in the transient 2 (up to 1200s).......... 161 Fig. A.47 -Model of the LOFT and PWR core..................................................... 163 XVIII LIST OF TABLES INTRODUCTIONSafety is an essential part for the peaceful use of nuclear power generation. The safety of nuclear power plants is based on the concept of defence in depth [1], Fig. 1, which indicates successive physical barriers (fuel matrix, cladding, primary system pressure boundary and ...

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“…The common feature is that each option highly depends upon the extensive experimental database, from which uncertainties can be derived. and data adjustment/assimilation [87] A.1.1.1.…”

Section: A11 Best Estimate Plus Uncertainty Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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Framework and Strategies for the Introduction of Best Estimate Models Into the Licensing Process

Sollima

Petrangeli

D'Auria

et al. 2009

Volume 4: Codes, Standards, Licensing and Regulatory Issues; Student Paper Competition

View full text Add to dashboard Cite

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“…As is known, conflicting and contradictory claims are often made about the relative models and parameter selections during the simulation processes of Nuclear Power Plants, which may cause some unpredictable influences on the code outputs. For example, when using RELAP5 code to simulate the AP1000 NPP systems, as is shown in Figure 1, the simulation results may be influenced by initial and boundary parameters such as temperature, pressure, and feedwater mass flow rate, as well as some other system conditions, for example, selected model and volume partition methods [16,17]. Consequently, in this paper, an overall sensitivity analysis is proposed and performed to study the importance of different parameters and models upon the predicted results in the AP1000 Nuclear Power Plant and validated against available data (AP1000 Design Control Document, 2010) [18], which could assist the engineers to evaluate the effects of relative factors and improve the code simulation accuracy [19].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Evaluation of AP1000 Nuclear Power Plant Best Estimation Model

Shi

Cai

Chen

2017

Science and Technology of Nuclear Installations

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The best estimation process of AP1000 Nuclear Power Plant (NPP) requires proper selections of parameters and models so as to obtain the most accurate results compared with the actual design parameters. Therefore, it is necessary to identify and evaluate the influences of these parameters and modeling approaches quantitatively and qualitatively. Based on the best estimate thermalhydraulic system code RELAP5/MOD3.2, sensitivity analysis has been performed on core partition methods, parameters, and model selections in AP1000 Nuclear Power Plant, like the core channel number, pressurizer node number, feedwater temperature, and so forth. The results show that core channel number, core channel node number, and the pressurizer node number have apparent influences on the coolant temperature variation and pressure drop through the reactor. The feedwater temperature is a sensitive factor to the Steam Generator (SG) outlet temperature and the Steam Generator outlet pressure. In addition, the cross-flow model nearly has no effects on the coolant temperature variation and pressure drop in the reactor, in both the steady state and the loss of power transient. Furthermore, some fittest parameters with which the most accurate results could be obtained have been put forward for the nuclear system simulation.

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“…Also uncertainties in modeling have not been addressed explicitly in the previous analytical works. Assessment of the uncertainties and their influence on behavior of the system is an essential element of the code validation [25]. One of the sources of uncertainties is code input parameters that are not measured directly in the experiment.…”

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confidence: 99%

Input Calibration and Validation of RELAP5 Against CIRCUS-IV Single Channel Tests on Natural Circulation Two-Phase Flow Instability

Phung

Kudinov

Grishchenko

et al. 2015

Science and Technology of Nuclear Installations

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RELAP5 is a system thermal-hydraulic code that is used to perform safety analysis on nuclear reactors. Since the code is based on steady state, two-phase flow regime maps, there is a concern that RELAP5 may provide significant errors for rapid transient conditions. In this work, the capability of RELAP5 code to predict the oscillatory behavior of a natural circulation driven, twophase flow at low pressure is investigated. The simulations are compared with a series of experiments that were performed in the CIRCUS-IV facility at the Delft University of Technology. For this purpose, we developed a procedure for calibration of the input and code validation. The procedure employs (i) multiple parameters measured in different regimes, (ii) independent consideration of the subsections of the loop, and (iii) assessment of importance of the uncertain input parameters. We found that predicted system parameters are less sensitive to variations of the uncertain input and boundary conditions in high frequency oscillations regime. It is shown that calculation results overlap experimental values, except for the high frequency oscillations regime where the maximum inlet flow rate was overestimated. This finding agrees with the idea that steady state, two-phase flow regime maps might be one of the possible reasons for the discrepancy in case of rapid transients in two-phase systems.

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Approaches, Relevant Topics, and Internal Method for Uncertainty Evaluation in Predictions of Thermal-Hydraulic System Codes

Cited by 15 publications

References 8 publications

Framework and Strategies for the Introduction of Best Estimate Models Into the Licensing Process

Framework and Strategies for the Introduction of Best Estimate Models Into the Licensing Process

Sensitivity Evaluation of AP1000 Nuclear Power Plant Best Estimation Model

Input Calibration and Validation of RELAP5 Against CIRCUS-IV Single Channel Tests on Natural Circulation Two-Phase Flow Instability

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