• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2311-2320
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• 2022

The main outcomes of the experiments H2P6 performed in the thermal-hydraulics large-scale PANDA facility at PSI in the frame of the OECD/NEA HYMERES-2 project are presented in this article. The experiments of the H2P6 series consists of two PANDA tests characterized by the activation of three (H2P6_1) or one (H2P6_2) cooler(s) in an initially stratified and pressurized containment atmosphere. The initial stratification is defined by a helium-rich region located in the upper part of the vessel and a steam/air atmosphere in the lower part. The activation of the cooler(s) results i) in the condensation of the steam in the vicinity of the cooler(s), ii) the corresponding activation of large scale natural circulation currents in the vessel atmosphere, with the result of iii) the re-distribution and mixing of the Helium stratification initially located in the upper half of the vessel and iv) the continuous pressure decay. The initial helium layer represents hydrogen generated in a postulated severe accident. The main question to be answered by the experiments is whether or not the interaction of the different, localized cooler units would be important for the application of numerical methods. The paper describes the initial and boundary conditions and the experimental results of the H2P6 series with the suggestion of simple scaling laws for both experiments in terms of i) the temperature difference(s) across the cooler(s), ii) the transient steam and helium content and iii) the pressure decay in the vessel. The outcomes of this scaling indicate that the interaction between separate, closely localized units does not play a prominent role for the present experiments. It is therefore reasonable to model several units as one large component with equivalent heat transfer area and total water flow rate.

• 시스템엔지니어링학술지
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• 제18권2호
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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.

• Nuclear Engineering and Technology
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• 제55권9호
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.452-459
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• 2023

The core power control is an important issue for the study of dynamic characteristics in China initiative accelerator driven subcritical system (CiADS), which has direct impact on the control strategy and safety analysis process. The CiADS is an experimental facility that is only controlled by the proton beam intensity without considering the control rods in the current engineering design stage. In order to get the optimized operation scheme with the stable and reliable features, the variation of beam intensity using the continuous and periodic control approaches has been adopted, and the change of collimator and the adjusting of duty ratio have been proposed in the power control process. Considering the neutronics and the thermal-hydraulics characteristics in CiADS, the physical model for the core power control has been established by means of the point reactor kinetics method and the lumped parameter method. Moreover, the multi-inputs single-output (MISO) logical structure for the power control process has been constructed using proportional integral derivative (PID) controller, and the meta-heuristic algorithm has been employed to obtain the global optimized parameters for the stable running mode without producing large perturbations. Finally, the verification and validation of the control method have been tested based on the reference scenarios in considering the disturbances of spallation neutron source and inlet temperature respectively, where all the numerical results reveal that the optimization method has satisfactory performance in the CiADS core power control scenarios.

• Nuclear Engineering and Technology
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• 제18권3호
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• pp.200-208
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• 1986

원자로 냉각 계통의 배관 파열에 근거한 냉각재 상실 사고를 방출계수 0.4에 대하여 분석하였다. 분석은 원자로 냉각계통의 배관 파열에 의하여 발생된 감압부터 노심 복구까지의 전 과도 상태를 포함한다. 계통 열수력과 핵연료 성능 평가를 위하여 BLOWDOWN 단계에서는 RELAP4/MOD6-EM 코드와 RELAP4/MOD6-HOT CHANNEL 코드를 사용하였으며 REFLOOD 단계에서는 RELAP4/ MOD6-FLOOD 코드와 TOODEE2 코드를 각각 사용하였다. LOWER PLENUM 충전을 고려하기 위하여 DOWNCOMER에서 증기-물역방향 유동과 과열벽효과를 근사하여 간단한 해석적 모델이 개발되었다. EOB 발생시의 정보를 근거로 하여 재충전지속 시간과 초기 복구 온도가 계산되었으며 RELAP4/MOD6에 의한 분석결과와 비교하여 상당한 일치를 보였다. 또한, 조기 EOB 발생에 영향을 미치는 계통변수의 연구가 수행되어졌다. DOWNCOMER와 UPPER HEAD사이의 마찰손실이 조기 EOB 발생에 지대한 영향을 미쳤으며 적당한 마찰손실계수의 선택을 통하여 조기 EOB 발생을 방지할 수 있었다. 노심 nodalization이 여섯 개인 경우와 세 개인 경우의 분석 결과가 계통열수력학적 면에서 유사한 결과를 나타내지만, 좋은 결과를 얻기 위하여 전자의 경우가 요구된다.

• 에너지공학
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• 제21권4호
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• pp.419-426
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• 2012

본 연구에서는 기기 스케일 2상 유동(Two-phase flow) 해석 코드 CUPID를 사용하여 CANDU 원자로의 칼란드리아 용기 내부 감속재의 열수력 거동을 분석하기 위한 사전연구를 수행하였다. 먼저, Stern 연구소에서 수행한 단상유동 실험 3종류를 이용하여 CUPID 코드를 검증하였다. 칼란드리아 관다발 영역 격자생성의 복잡성을 피하기 위하여 다공성 매질 모델을 해당 영역에 적용하였고, 다공성 매질 영역의 유동 저항은 실험에서 얻은 관계식을 이용하여 계산하도록 하였다. 계산결과, CUPID 코드는 칼란드리아 용기 내부의 강제 및 자연 대류의 혼합 유동 양식을 성공적으로 예측하였다. 다음으로 2상 유동이 발생하는 경우를 해석하였다. 이들 계산을 통해 CUPID 코드의 CANDU 원자로 감속재 해석 능력을 보였다. 또한, 국부 과냉각 여유도를 예측하는데 사용할 수 있는 유입유량 대비 칼란드리아 용기의 국부 최대 감속재 온도 그래프를 제시하였다.

• Nuclear Engineering and Technology
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• 제45권4호
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• pp.513-522
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• 2013

The ODSCC detected in the TSP position of Ulchin 3&4 SGs are typical ODSCC of Alloy 600MA tubes. The causative chemical environment is formed by concentration of impurities inside the occluded region formed by the tube surface, egg crate strips, and sludge deposit there. Most cracks are detected at or near the line contacts between the tube surface and the egg crate strips. The region of dense crack population, as defined as between $4^{th}$ and $9^{th}$ TSPs, and near the center of hot leg hemisphere plane, coincided well with the region of preferential sludge deposition as defined by thermal hydraulics calculation using SGAP computer code. The cracks developed homogeneously in a wide range of SGs, so that the number of cracks detected each outage increased very rapidly since the first detection in the $8^{th}$ refueling outage. The root cause assessment focused on investigation of the difference in microstructure and manufacturing residual stress in order to reveal the cause of different susceptibilities to ODSCC among identical six units. The manufacturing residual stress as measured by XRD on OD surface and by split tube method indicated that the high residual stress of Alloy 600MA tube played a critical role in developing ODSCC. The level of residual stress showed substantial variations among the six units depending on details of straightening and OD grinding processes. Youngwang 3&4 tubes are less susceptible to ODSCC than U3 and U4 tubes because semi-continuous coarse chromium carbides are formed along the grain boundary of Y3&4 tubes, while there are finer less continuous chromium carbides in U3 and U4. The different carbide morphology is caused by the difference in cooling rate after mill anneal. There is a possibility that high chromium content in the Y3&4 tubes, still within the allowable range of Alloy 600, has made some contribution to the improved resistance to ODSCC. It is anticipated that ODSCC in Y5&6 SGs will be retarded more considerably than U3 SGs since the manufacturing residual stress in Y5&6 tubes is substantially lower than in U3 tubes, while the microstructure is similar with each other.