Uncertainty Analysis of Scaling Calculations From LSTF Small Break LOCA Tests With Steam Generator Intentional Depressurization Applying to a Four-Loop PWR

2018 ◽  
Author(s):  
Ikuo Kinoshita
Keyword(s):  
Steam Generator ◽  
Uncertainty Propagation ◽  
Correlation Coefficients ◽  
Injection System ◽  
Plant Model ◽  
Input Uncertainty ◽  
Loss Of Coolant Accident ◽  
Output Uncertainty ◽  
Management Procedure ◽  
Uncertainty Parameters

The Best Estimate Plus Uncertainty (BEPU) method is applied to analysis of the “intentional depressurization of steam generator secondary side” which is an accident management procedure in a small break loss-of-coolant accident with high pressure injection system failure. In the present study, scaling calculations from the LSTF small break LOCA tests were carried out for a conventional Westinghouse type four-loop PWR. The two test cases were selected with different break size and different depressurization conditions to ensure the reliability for the analyses for the accident scenario. The uncertainty propagation analyses were performed for the PWR. The dominating input uncertainty parameters, i.e. those few with the highest influence on the output uncertainty were identified. The analysis results were compared with those for the LSTF to address the scaling up capability and the similarity evaluation between the LSTF model and the PWR plant model. It was found that the PWR plant model results had overall agreements with the LSTF model, and the uncertainty of the predicted PCT included the measured PCT. Furthermore, the correlation coefficients between the input uncertainty parameters and the PCT for the PWR plant model had similarities with those for the LSTF model.

RELAP5 Code Uncertainty Analysis of LSTF Small Break LOCA Tests With Steam Generator Intentional Depressurization as an Accident Management Procedure

2016 ◽  
Author(s):  
Ikuo Kinoshita ◽  
Toshihide Torige
Keyword(s):  
Steam Generator ◽  
Injection System ◽  
Test Facility ◽  
Test Cases ◽  
Input Uncertainty ◽  
Accident Scenario ◽  
Management Procedure ◽  
Accident Management ◽  
Uncertainty Parameters ◽  
Secondary Side

The Best Estimate Plus Uncertainty (BEPU) method is applied to analysis of the “intentional depressurization of steam generator secondary side” which is an accident management procedure in a small break loss-of-coolant accident with high pressure injection system failure. In the present study, experimental analyses using the RELAP5/MOD3.2 code were carried out for the ROSA/Large Scale Test Facility (LSTF) secondary-side depressurization tests. The two test cases were selected with different break sizes and different depressurization conditions to ensure the reliability for the accident scenario analyses. The input parameter uncertainty propagation analyses were performed to get 95%/95% tolerance limit values of the output parameters. It was confirmed that the code predicted well the major event progressions of the accident for both test cases and the 95%/95% uncertainty bounds of the peak cladding temperatures included the measured values. On the other hand, the same ranges of some input uncertainty parameters could lead to different influences on the output uncertainties between the test cases. The dominating input uncertainty parameters could be different depending on the break sizes and depressurization conditions of the accident scenario.

Sobol′ Sensitivity Analysis Using a Neural Network Model of a LB-LOCA in the ZION Nuclear Power Plant With CATHARE-2 V2.5 Code

2013 ◽  
Author(s):  
Fabrice Fouet ◽  
Pierre Probst
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Nuclear Power ◽  
Uncertainty Propagation ◽  
Correlation Coefficients ◽  
Computer Code ◽  
Numerical Application ◽  
Loss Of Coolant Accident ◽  
Input Parameters ◽  
Artificial Neural Network Ann

In nuclear safety, the Best-Estimate (BE) codes may be used in safety demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. The uncertainty of output parameters, which comes mainly from the lack of knowledge of the input parameters, is evaluated by estimating the 95% percentile with a high degree of confidence. IRSN, technical support of the French Safety Authority, developed a method of uncertainty propagation. This method has been tested with the BE code used is CATHARE-2 V2.5 in order to evaluate the Peak Cladding Temperature (PCT) of the fuel during a Large Break Loss Of Coolant Accident (LB-LOCA) event, starting from a large number of input parameters. A sensitivity analysis is needed in order to limit the number of input parameters and to quantify the influence of each one on the response variability of the numerical model. Generally, the Global Sensitivity Analysis (GSA) is done with linear correlation coefficients. This paper presents a new approach to perform a more accurate GSA to determine and to classify the main uncertain parameters: the Sobol′ methodology. The GSA requires simulating many sets of parameters to propagate uncertainties correctly, which makes of it a time-consuming approach. Therefore, it is natural to replace the complex computer code by an approximate mathematical model, called response surface or surrogate model. We have tested Artificial Neural Network (ANN) methodology for its construction and the Sobol′ methodology for the GSA. The paper presents a numerical application of the previously described methodology on the ZION reactor, a Westinghouse 4-loop PWR, which has been retained for the BEMUSE international problem [8]. The output is the first maximum PCT of the fuel which depends on 54 input parameters. This application outlined that the methodology could be applied to high-dimensional complex problems.

New Concept of a Micro Gas Turbine Based Co-Generation Package for Performance Improvement in Practical Use

2005 ◽  
Author(s):  
Kenichiro Mochizuki ◽  
Satoshi Shibata ◽  
Umeo Inoue ◽  
Toshiaki Tsuchiya ◽  
Hiroko Sotouchi ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Steam Generator ◽  
Thermal Efficiency ◽  
Heat Recovery ◽  
Steam Injection ◽  
Operating Conditions ◽  
Market Potential ◽  
Injection System ◽  
Heat Recovery Steam Generator ◽  
Micro Gas Turbine

As the energy consumption has been increasing rapidly in the commercial sector in Japan, the market potential for the micro gas turbine is significant and it will be realized substantially if the thermal efficiency is improved. One of measures is to introduce the steam injection system using the steam generated by the heat recovery steam generator. Steam injection tests have been carried out using a micro gas turbine (Capstone C60). Test results showed that key performance parameters such as power output, thermal efficiency and emissions were improved by the steam injection. The stable operation of micro gas turbine with steam injection was confirmed under various operating conditions. Consequently, a micro gas turbine based co-generation package with steam injection driven by a heat recovery steam generator (HRSG) with supplementary firing is proposed.

Uncertainty Propagation Through a Simulation of Industrial High Pressure Die Casting

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Jiahong Fu ◽  
John Coleman ◽  
Gregory Poole ◽  
Matthew John M. Krane ◽  
Amy Marconnet
Keyword(s):  
Heat Transfer ◽  
High Pressure ◽  
Boundary Conditions ◽  
Die Casting ◽  
Uncertainty Propagation ◽  
Model Parameters ◽  
High Pressure Die Casting ◽  
Output Uncertainty ◽  
Pressure Die Casting ◽  
The Impact

Abstract While numerical models are often used in industry to evaluate the transport phenomena in solidification processes, the uncertainty in the results propagated from uncertain input parameters is rarely considered. In this work, in order to investigate the effects of input uncertainty on the outputs of high pressure die casting (HPDC) simulations, the Center for Prediction of Reliability, Integrity, and Survivability of Microsystems (PRISM) uncertainty quantification (PUQ) framework was applied. Three uncertainty propagation trials investigate the impact of uncertainty in metal material properties, thermal boundary conditions, and a modeling parameter on outputs of interest, such as fraction liquid at different times in the process cycle and shrinkage porosity volume, in an industrial A380 aluminum alloy HPDC process. This quantification of the output uncertainty establishes the reliability of the simulation results and can inform process design choices, such as the determination of the part ejection time. The results are most sensitive to the uncertainty in the interfacial heat transfer (for both outputs of interest) and the feeding effectivity (FE) (a model parameter controlling porosity formation determination), while the other heat transfer boundary conditions, model parameters, and all the properties play a secondary role in output uncertainty.

Development of Steam Generator Model Using RELAP5 to Simulate Two-Phase Natural Circulation for Pressurized Water Reactor

2014 ◽  
Author(s):  
Shinya Miyata ◽  
Satoru Kamohara ◽  
Wataru Sakuma ◽  
Hiroaki Nishi
Keyword(s):  
Steam Generator ◽  
Natural Circulation ◽  
Injection System ◽  
Pressurized Water Reactor ◽  
Two Phase ◽  
Pressurized Water ◽  
Water Reactor ◽  
Loss Of Coolant ◽  
Mass Inventory ◽  
Core Cooling

In typical pressurized water reactor (PWR), to cope with beyond design basis events such as station black out (SBO) or small break loss of coolant accident with safety injection system failure, injection from accumulator sustains core cooling by compensating for loss of coolant. Core cooling is sustained by single- or two-phase natural circulation or reflux condensation depending on primary coolant mass inventory. Behavior of the natural circulation in PWR has been investigated in the facilities such as Large Scale Test Facility (LSTF) which is a full-height and full-pressure and thermal-hydraulic simulator of typical four-loop PWR. Two steady-state natural circulation tests were conducted in LSTF at both high and low pressure. These two tests were conducted changing the primary mass inventory as a test parameter, while keeping the other parameters such as core power, steam generator (SG) pressure, and steam generator water level as they are. Mitsubishi Heavy Industries (MHI) plans new natural circulation tests to cover wider range of core power and pressure as test-matrix (including the previous LSTF tests) to validate applicability of the model in wider range of core power and pressure conditions including the SBO conditions. In this paper, the previous LSTF natural circulation tests are reviewed and the new test plan will be described. Additionally, MHI also started a feasibility study to improve the steam generator tube and inlet/outlet plenum model using the M-RELAP5 code [4]. Newly developed model gives reasonable agreement with the previous LSTF tests and applies to the new test conditions. The feasibility findings will also be described in this paper.

The trajectory importance measure of the shaping machine under stochastic excitation

2011 ◽  
Vol 226 (3) ◽  
pp. 808-815 ◽  
Author(s):  
L J Cui ◽  
Z Z Lu ◽  
C C Zhou
Keyword(s):  
Failure Probability ◽  
Computational Efficiency ◽  
Importance Measure ◽  
Stochastic Excitation ◽  
Input Uncertainty ◽  
Dynamic Reliability ◽  
Probability Density Evolution Method ◽  
Output Uncertainty ◽  
The Moment ◽  
Probability Density Evolution

Two trajectory importance measures, the trajectory importance measure based on variance and the moment-independent trajectory importance measure, are proposed to represent the time-variant effects of input uncertainty on the output uncertainty of the shaping machine under stochastic excitation in its work stroke, respectively. At the same time, the trajectory importance measure based on the failure probability is proposed to reflect the contribution of the input uncertainty on the dynamic reliability of the mechanism. These three trajectory importance measures provide different references to improve the performance and reliability of the mechanism from the time-variant perspective. As the probability density evolution method (PDEM) is employed to solve the proposed trajectory importance measures, it can improve the computational efficiency largely without losing precision. Results of the shaping mechanism illustrate the feasibility of the proposed trajectory importance measures and the veracity of the PDEM in solving the lathe mechanism.

scholarly journals ROSA/LSTF Tests and RELAP5 Posttest Analyses for PWR Safety System Using Steam Generator Secondary-Side Depressurization against Effects of Release of Nitrogen Gas Dissolved in Accumulator Water

2016 ◽  
Vol 2016 ◽  
pp. 1-15
Author(s):  
Takeshi Takeda ◽  
Akira Ohnuki ◽  
Daisuke Kanamori ◽  
Iwao Ohtsu
Keyword(s):  
Steam Generator ◽  
Safety System ◽  
Injection System ◽  
Test Facility ◽  
Gas Release ◽  
Dissolved Gas ◽  
Nitrogen Gas ◽  
Two Phase ◽  
Pressurized Water ◽  
Secondary Side

Two tests related to a new safety system for a pressurized water reactor were performed with the ROSA/LSTF (rig of safety assessment/large scale test facility). The tests simulated cold leg small-break loss-of-coolant accidents with 2-inch diameter break using an early steam generator (SG) secondary-side depressurization with or without release of nitrogen gas dissolved in accumulator (ACC) water. The SG depressurization was initiated by fully opening the depressurization valves in both SGs immediately after a safety injection signal. The pressure difference between the primary and SG secondary sides after the actuation of ACC system was larger in the test with the dissolved gas release than that in the test without the dissolved gas release. No core uncovery and heatup took place because of the ACC coolant injection and two-phase natural circulation. Long-term core cooling was ensured by the actuation of low-pressure injection system. The RELAP5 code predicted most of the overall trends of the major thermal-hydraulic responses after adjusting a break discharge coefficient for two-phase discharge flow under the assumption of releasing all the dissolved gas at the vessel upper plenum.

scholarly journals Optimized Sparse Polynomial Chaos Expansion With Entropy Regularization

2021 ◽  
Author(s):  
SiJie Zeng ◽  
XiaoJun Duan ◽  
JiangTao Chen ◽  
Liang Yan
Keyword(s):  
Polynomial Chaos ◽  
Uncertainty Propagation ◽  
Entropy Change ◽  
Optimization Method ◽  
Polynomial Chaos Expansion ◽  
Chaos Expansion ◽  
Sparse Polynomial ◽  
Output Uncertainty ◽  
Sparse Polynomial Chaos Expansion ◽  
Fitting In

Abstract Sparse Polynomial Chaos Expansion(PCE) is widely used in various engineering fields to quantitatively analyse the influence of uncertainty, while alleviate the problem of dimensionality curse. However, current sparse PCE techniques focus on choosing features with the largest coefficients, which may ignore uncertainties propagated with high order features. Hence, this paper proposes the idea of selecting polynomial chaos basis based on information entropy, which aims to retain the advantages of existing sparse techniques while considering entropy change as output uncertainty. A novel entropy-based optimization method is proposed to update the state-of-the-art sparse PCE models. This work further develops an entropy-based synthetic sparse model, which has higher computational efficiency. Two benchmark functions and a CFD experiment are used to compare the accuracy and efficiency between the proposed method and classical methods. The results show that entropy-based methods can better capture the features of uncertainty propagation, and the problem of over-fitting in existing sparse PCE methods can be avoided.

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