• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1448-1459
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• 2023

A key element of the safety analysis is Loss of Coolant Analysis (LOCA) which must be performed using system thermal-hydraulic codes. These codes are extensively validated against separate effect and integral experiments. RELAP/SCDAPSIM is one such code that may be used to predict LBLOCA response in a CANDU reactor. The RD-14M experiment selected for the Best Estimate Plus Uncertainty study is a 44 mm (22.7%) inlet header break test with no Emergency Coolant Injection. This work has two objectives first is to simulate pipe break with RELAP and compare these results to those available from experiment and from comparable TRACE calculations. The second objective is to quantify uncertainty in the fuel element sheath (FES) temperature arising from model coefficient as well as input parameter uncertainties using Integrated Uncertainty Analysis package. RELAP calculated results are found to be in good agreement with those of TRACE and with those of experiments. The base case maximum FES temperature is 335.5 ℃ while that of 95% confidence 95^th percentile is 407.41 ℃ for the first order Wilk's formula. The experimental measurements fall within the predicted band and the trends and sensitivities are similar to those reported for the TRACE code.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.419-433
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• 2016

One of the important severe accident management measures in the Light Water Reactors is water injection to the reactor core. The related phenomena are investigated by performing experiments and computer simulations. One of the most widely known is the QUENCH test-program. A number of analyses on QUENCH tests have also been performed by different computer codes for code validation and improvements. Unfortunately, any deterministic computer simulation is not free from the uncertainties. To receive the realistic calculation results, the best estimate computer codes should be used for the calculation with combination of uncertainty and sensitivity analysis of calculation results. In this article, the QUENCH-03 and QUENCH-06 experiments are modelled using ASTEC and RELAP/SCDAPSIM codes. For the uncertainty and sensitivity analysis, SUSA3.5 and SUNSET tools were used. The article demonstrates that applying the best estimate approach, it is possible to develop basic QUENCH input deck and to develop the two sets of input parameters, covering maximal and minimal ranges of uncertainties. These allow simulating different (but with the same nature) tests, receiving calculation results with the evaluated range of uncertainties.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2670-2677
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• 2023

In the nuclear safety studies, a new trend refers to the evaluation of uncertainties as a mandatory component of best-estimate safety analysis which is a modern and technically consistent approach being known as BEPU (Best Estimate Plus Uncertainty). The major objectives of this study consist in performing a study of uncertainties/sensitivities of the major analysis results for a generic CANDU 6 Nuclear Power Plant during Station Blackout (SBO) progression to understand and characterize the sources of uncertainties and their effects on the key figure-of-merits (FOMs) predictions in severe accidents (SA). The FOMs of interest are hydrogen mass generation and event timings such as the first fuel channel failure time, beginning of the core disassembly time, core collapse time and calandria vessel failure time. The outcomes of the study, will allow an improvement of capabilities and expertise to perform uncertainty and sensitivity analysis with severe accident codes for CANDU 6 Nuclear Power Plant.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3787-3800
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• 2023

Reactivity Initiated Accident (RIA) scenarios require special attention using advanced simulation techniques due to their complexity and importance for nuclear power plant (NPP) safety. While the conservative approach has traditionally been used for safety analysis, it may lead to unrealistic results which calls for the use of best estimate plus uncertainty (BEPU) approach, especially with the current advances in computational power which makes the BEPU analysis feasible. In this work an Uncontrolled Control Element Assembly (CEA) Withdrawal at Full Power accident scenario is analyzed using the BEPU approach by loosely coupling the thermal hydraulics best-estimate system code (RELAP5/SCDAPSIM/MOD3.4) to the statistical analysis software (DAKOTA) using a Python interface. Results from the BEPU analysis indicate that a realistic treatment of the accident scenario yields a larger safety margin and is therefore encouraged for accident analysis as it may enable more economic and flexible operation.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.1-15
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• 2020

Nuclear power plants in South Korea are operated to cover the baseload demand. Hence they are operated at 100% rated power and do not deploy power tracking control except for startup, shutdown, or during transients. However, as the contribution of renewable energy in the energy mix increases, load follow operation may be needed to cover the imbalance between consumption and production due to the intermittent nature of electricity produced from the conversion of wind or solar energy. Load follow operation may be quite challenging since the operators need to control the axial power distribution and core reactivity while simultaneously conducting the power maneuvering. In this paper, a systems engineering approach for multi-physics load follow simulation of APR1400 is performed. RELAP5/SCDAPSIM/MOD3.4/3DKIN multi-physics package is selected to simulate the Korean Advanced Power Reactor, APR1400, under load follow operation to reflect the impact of feedback signals on the system safety parameters. Furthermore, the systems engineering approach is adopted to identify the requirements, functions, and physical architecture to provide a set of verification and validation activities that guide this project development by linking each requirement to a validation or verification test with predefined success criteria.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.27-37
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• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.