• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.201-202
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.238-238
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• 2001

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.163.1-163
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• 1998

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.1231-1232
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• 2005

• Nuclear Engineering and Technology
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• v.38 no.1
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• pp.11-32
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• 2006

System thermal-hydraulic codes have been used in the past decades in the areas of design, operation, licensing and safety of Nuclear Power Plants (NPPs). The development and validation of these codes have reached a high degree of maturity, through the consideration of huge experiments and advanced numerical models. Nowadays, the analyses are based upon realistic approaches rather than the conservative evaluation models. However the applications of these computational tools require preliminary qualification issues. Although huge amounts of financial and human resources have been invested for the development and improvement of codes, the calculation results are still affected by errors. In the sophisticated nuclear technology, design and safety of NPP, these errors must be quantified. An overview of the state of the art of the current thermal-hydraulic system code is developed and the need of uncertainty analysis in code calculations is emphasized. Several sources of uncertainty have been classified and commented, and typical applications of such methods are shown.

• Journal of Energy Engineering
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• v.24 no.4
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• pp.175-182
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• 2015

A methodology to determine the most conservative initial condition based on random sampling of operation parameters is established, in which a best-estimate computer code is adopted to minimize the conservatism in code models. To validate the applicability of the suggested method, safety evaluation for a transient of loss of condenser vacuum in a pressurized water reactor is performed. One-hundred different initial conditions are generated by MOSAIQUE program automatically and the peak pressure for the most conservative case is determined from transient analyses. The safety margin obtained with the new approach is almost equivalent to the values determined with the existing methodologies. It is found that the time and human resources required for the safety evaluation could be reduced with the suggested approach.

• Nuclear Engineering and Technology
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• v.44 no.6
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• pp.611-622
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• 2012

"Scaling" plays an important role for safety analyses in the licensing of water cooled nuclear power reactors. Accident analyses, a sub set of safety analyses, is mostly based on nuclear reactor system thermal hydraulics, and therefore based on an adequate experimental data base, and in recent licensing applications, on best estimate computer code calculations. In the field of nuclear reactor technology, only a small set of the needed experiments can be executed at a nuclear power plant; the major part of experiments, either because of economics or because of safety concerns, has to be executed at reduced scale facilities. How to address the scaling issue has been the subject of numerous investigations in the past few decades (a lot of work has been performed in the 80thies and 90thies of the last century), and is still the focus of many scientific studies. The present paper proposes a "roadmap" to scaling. Key elements are the "scaling-pyramid", related "scaling bridges" and a logical path across scaling achievements (which constitute the "scaling puzzle"). The objective is addressing the scaling issue when demonstrating the applicability of the system codes, the "key-to-scaling", in the licensing process of a nuclear power plant. The proposed "road map to scaling" aims at solving the "scaling puzzle", by introducing a unified approach to the problem.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1698-1711
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• 2022

A combined safety approach, which uses a best-estimate computer code and adopts conservative assumptions for safety systems availability, is developed and applied to the safety margin evaluation for the Loss of Condenser Vacuum (LOCV) of the 1000 MWe Korean Nuclear Power Plant. The Multi-dimensional Analysis of Reactor Safety-KINS standard (MARS-KS) code is selected as a best-estimate code and the PAPIRUS program is used to obtain different initial operational conditions through random sampling of control variables. During an LOCV event, fuel integrity is not threatened by the increase in Departure from Nuclear Boiling Ratio (DNBR). However, the high pressure in the primary coolant system and the secondary system might affect the system integrity. Thus, the peak pressure becomes a major safety concern. Transient analyses are performed for 124 cases of different initial conditions and the most conservative case, which results in the highest system pressure is selected. It is found the suggested methodology gives similar peak pressures when compared to those predicted from existing methodologies. The proposed approach is expected to minimize the time and efforts required to identify the conservative plant conditions in the existing conservative safety methodologies.

• Nuclear Engineering and Technology
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• v.26 no.3
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• pp.355-366
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• 1994

The USNRC issued a revised ECCS rule that allows the use of best estimate computer codes for safety analysis. The rule also requires an estimation of uncertainty in calculated system response when applying the best estimate computer codes. A practical realistic evaluation methodology to evaluate the ECCS performance that satisfies the requirements of the ECCS rule has been developed and this paper describes the application of new realistic evaluation methodology to large break LOCA for, the demonstration of the new methodology. The computer code RELAP5/MOD3/KAERI, which was improved from RELAP5/MOD3.1, was used as the best estimate code in the application. The uncertainty of the code was evaluated by assessing several separate and integral effect tests, and for the application to actual plant Kori 3 & 4 was selected as the reference plant. Response surfaces for blowdown and reflood PCTs were generated from the results of the sensitivity analyses and probability distribution functions were established by random sampling or Monte-Carlo method for each response surface. Final uncertainties were quantified at 95% probability level and safety margins for large break LOCA were discussed.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.