• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2001년도 추계학술발표회요약집
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• pp.227.1-227
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• 2001

• 시스템엔지니어링학술지
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• 제19권2호
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• pp.46-58
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• 2023

Deterministic safety analysis is a crucial part of safety assessment, particularly when it comes to demonstrating the safety of nuclear power plant designs. The traditional approach to deterministic safety analysis models is to model the nuclear core using point kinetics. However, this simplified approach does not fully reflect the real core behavior with proper moderator and fuel reactivity feedbacks during the transient. The use of Multi-Physics approach allows more precise simulation reflecting the inherent three-dimensionality (3D) of the problem by representing the detailed 3D core, with instantaneous updates of feedback mechanisms due to changes of important reactivity parameters like fuel temperature coefficient (FTC) and moderator temperature coefficient (MTC). This paper addresses a CEA ejection accident at hot full power (HFP), in which the underlying strong and un-symmetric feedback between thermal-hydraulics and reactor kinetics exist. For this purpose, a multi-physics analysis tool has been selected with the nodal kinetics code, 3DKIN, implicitly coupled to the thermal-hydraulic code, RELAP5, for real-time communication and data exchange. This coupled approach enables high fidelity three-dimensional simulation and is therefore especially relevant to reactivity initiated accident (RIA) scenarios and power distribution anomalies with strong feedback mechanisms and/or un-symmetrical characteristics as in the CEA ejection accident. The Systems Engineering approach is employed to provide guidance in developing the work in a systematic and efficient fashion.

• Nuclear Engineering and Technology
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• 제55권10호
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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.

• 시스템엔지니어링학술지
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• 제18권2호
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• pp.58-74
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• 2022

Deterministic accident analysis plays a central role in the nuclear power plant (NPP) safety evaluation and licensing process. Traditionally the conservative approach opted for the point kinetics model, expressing the reactor core parameters in the form of reactivity and power tables. However, with the current advances in computational power, high fidelity multi-physics simulations using real-time code coupling, can provide more detailed core behavior and hence more realistic plant's response. This is particularly relevant for transients where the core is undergoing reactivity anomalies and uneven power distributions with strong feedback mechanisms, such as reactivity initiated accidents (RIAs). This work addresses a RIA, specifically a control element assembly (CEA) withdrawal at power, using the multi-physics analysis tool RELAP5/MOD 3.4/3DKIN. The thermal-hydraulics (TH) code, RELAP5, is internally coupled with the nodal kinetics (NK) code, 3DKIN, and both codes exchange relevant data to model the nuclear power plant (NPP) response as the CEA is withdrawn from the core. The coupled model is more representative of the complex interactions between the thermal-hydraulics and neutronics; therefore the results obtained using a multi-physics simulation provide a larger safety margin and hence more operational flexibility compared to those of the point kinetics model reported in the safety analysis report for APR1400. The systems engineering approach is used to guide the development of the work ensuring a systematic and more efficient execution.

• Nuclear Engineering and Technology
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• 제50권2호
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• pp.268-279
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• 2018

The ALCYONE multidimensional fuel performance code codeveloped by the CEA, EDF, and AREVA NP within the PLEIADES software environment models the behavior of fuel rods during irradiation in commercial pressurized water reactors (PWRs), power ramps in experimental reactors, or accidental conditions such as loss of coolant accidents or reactivity-initiated accidents (RIAs). As regards the latter case of transient in particular, ALCYONE is intended to predictively simulate the response of a fuel rod by taking account of mechanisms in a way that models the physics as closely as possible, encompassing all possible stages of the transient as well as various fuel/cladding material types and irradiation conditions of interest. On the way to complying with these objectives, ALCYONE development and validation shall include tests on $PWR-UO_2$ fuel rods with advanced claddings such as M5(R) under "low pressure-low temperature" or "high pressure-high temperature" water coolant conditions. This article first presents ALCYONE V1.4 RIA-related features and modeling. It especially focuses on recent developments dedicated on the one hand to nonsteady water heat and mass transport and on the other hand to the modeling of grain boundary cracking-induced fission gas release and swelling. This article then compares some simulations of RIA transients performed on $UO_2$-M5(R) fuel rods in flowing sodium or stagnant water coolant conditions to the relevant experimental results gained from tests performed in either the French CABRI or the Japanese NSRR nuclear transient reactor facilities. It shows in particular to what extent ALCYONE-starting from base irradiation conditions it itself computes-is currently able to handle both the first stage of the transient, namely the pellet-cladding mechanical interaction phase, and the second stage of the transient, should a boiling crisis occur. Areas of improvement are finally discussed with a view to simulating and analyzing further tests to be performed under prototypical PWR conditions within the CABRI International Program. M5(R) is a trademark or a registered trademark of AREVA NP in the USA or other countries.

• Nuclear Engineering and Technology
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• 제39권5호
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• pp.591-602
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• 2007

The results of Reactivity-Initiated Accidents (RIA) experiments have been analysed and the main variables affecting the fuel failure propensity identified. Fuel burn-up aggravates the mechanical loading of the cladding, while corrosion, or better the hydrogen absorbed in the cladding as a consequence of corrosion, may under some conditions make the cladding brittle and more susceptible to failure. Experiments point out that corrosion impairs the fuel resistance for RIA transient occurring at cold conditions, whereas there is no evidence of important embrittlement effects at hot conditions, unless the cladding was degraded by oxide spalling. A fuel failure threshold correlation has been derived and compared with experimental data relevant for BWR and PWR fuel. The correlation can be applied to both cold and hot RIA transients, account taken for the lower ductility at cold conditions and for the different initial enthalpy. It can also be used for non-zero power transients, provided that a term accounting for the start-up power is incorporated. The proposed threshold is easy to use and reproduces the results obtained in the CABRI and NSRR tests in a rather satisfactory manner. The behaviour of advanced PWR alloys and of MOX fuel is discussed in light of the correlation predictions. Finally, a probabilistic approach has been developed in order to account for the small scatter of the failure predictions. This approach completes the RIA failure assessment in that after determining a best estimate failure threshold, a failure probability is inferred based on the spreading of data around the calculated best estimate value.