Application of adjoint based node optimization method to nuclear thermal-hydraulic system analysis code

Abstract Nuclear thermal-hydraulic system analysis codes with the Best Estimate plus Uncertainty approach are unavoidably uncertain and naturally, an uncertainty analysis has been an important issue. In general, the system is discretized depending on the user while satisfying some criteria. Previously, uncertainties related to spatial discretization in nodalization have been less considered due to their difficulty in quantification. However, there are some results that they are comparable to other uncertainties. Previous studies have been conducted by evaluating and optimizing the uncertainty related to user effect by performing iterative calculations. Since these methods consume a large amount of resources for computation, this study suggests a method of consuming less resources. For this purpose, the adjoint method is applied to the code for node optimization in this study. The proposed methodology is applied to two cases and confirmed its applicability for the node optimization and its utility in the node uncertainty quantification.

[1]  F. D’Auria,et al.  Standardized Consolidated Calculated and Reference Experimental Database (SCCRED): A Supporting Tool for V&V and Uncertainty Evaluation of Best-Estimate System Codes for Licensing Applications , 2016 .

[2]  Jeong Ik Lee,et al.  Preliminary study of applying adjoint-based mesh optimization method to nuclear power plant safety analysis , 2017 .

[3]  Francesco Saverio D'Auria,et al.  Development of a qualified nodalization for small-break LOCA transient analysis in PSB-VVER integral test facility by RELAP5 system code , 2010 .

[4]  Francesco Saverio D'Auria,et al.  Review of quantitative accuracy assessments with fast Fourier transform based method (FFTBM) , 2002 .

[5]  R. Errico What is an adjoint model , 1997 .

[6]  F. D'Auria,et al.  User effects on the thermal-hydraulic transient system code calculations , 1993 .

[7]  Dan G. Cacuci,et al.  Adjoint Sensitivity Analysis of the RELAP5/MOD3.2 Two-Fluid Thermal-Hydraulic Code System—I: Theory , 2000 .

[8]  Francesco Saverio D'Auria,et al.  Thermal-Hydraulic System Codes in Nulcear Reactor Safety and Qualification Procedures , 2008 .

[9]  Pavel Kudinov,et al.  Automation of RELAP5 input calibration and code validation using genetic algorithm , 2016 .

[10]  T. Kozlowski,et al.  Confirmation of Wilks’ method applied to TRACE model of boiling water reactor spray cooling experiment , 2018, Annals of Nuclear Energy.

[11]  Jong-Rong Wang,et al.  Using genetic algorithms to calibrate the user-defined parameters of IIST model for SBLOCA analysis , 2014 .

[12]  Ki-Yong Choi,et al.  ATLAS program for advanced thermal-hydraulic safety research , 2015 .

[13]  S. S. Wilks Determination of Sample Sizes for Setting Tolerance Limits , 1941 .

[14]  Francesc Reventos,et al.  Uncertainty and sensitivity analysis of a LBLOCA in a PWR Nuclear Power Plant: Results of the Phase V of the BEMUSE programme , 2011 .

[15]  Suk Ku Sim,et al.  Assessment of the COBRA/RELAP5 code using the LOFT L2–3 large-break loss-of-coolant experiment , 1997 .

[16]  Dong-Jin Euh,et al.  Characteristics of the local bubble parameters of a subcooled boiling flow in an annulus , 2010 .

[17]  Sung Won Bae,et al.  ANALYSIS OF UNCERTAINTY QUANTIFICATION METHOD BY COMPARING MONTE-CARLO METHOD AND WILKS’ FORMULA , 2014 .

[18]  Kyung Doo Kim,et al.  PAPIRUS, a parallel computing framework for sensitivity analysis, uncertainty propagation, and estimation of parameter distribution , 2015 .