Advanced Power Reactor Research Articles

Development of advanced power reactor nuclear power plants containment pressure and temperature analysis methodology using CAP computer code

Development of advanced power reactor nuclear power plants containment pressure and temperature analysis methodology using CAP computer code

An Experimental Evaluation of the APR1000 Core Flow Distribution Using a 1/5 Scale Model

The experimental data of core flow distribution are indispensable for obtaining licensing and facilitating the design of fluid systems of nuclear reactors. In this study, an Advanced power reactor Core flow and Pressure (ACOP) test facility was established to experimentally simulate the internal flow of the Advanced Power Reactor 1000 (APR1000) on a reduced length scale of 1/5. The core region was simulated by using 177 core simulators representing the fuel assemblies of the APR1000. The APR1000 flow distributions were synthetically identified by accurately measured parameters: the core inlet flow rate and outlet pressure under the four-pump balanced and unbalanced flow conditions. The overall inlet flow rates ranged from 87.7% to 112.0% relative to the averaged flow rate. Here, we scrutinize the flow distributions considering the flow conditions and internal structures and briefly describe the applied scaling method and design concept of the test facility.

Analysis of control rod driving mechanism nozzle rupture with loss of safety injection at the ATLAS experimental facility using MARS-KS and TRACE

Korea Atomic Energy Research Institute (KAERI) has operated an integral effect test facility, the Advanced Thermal-Hydraulic Test Loop for Accident Simulation (ATLAS), with reference to the APR1400 (Advanced Power Reactor 1400) for tests for transient and design basis accidents simulation. A test for a loss of coolant accident (LOCA) at the top of the reactor pressure vessel (RPV) had been conducted at ATLAS to address the impact of the loss of safety injections (LSI) and to evaluate accident management (AM) actions during the postulated accident. The experimental data has been utilized to validate system analysis codes within a framework of the domestic standard problem program organized by KAERI in collaboration with Korea Institute of Nuclear Safety. In this study, the test has been analyzed by using thermal-hydraulic system analysis codes, MARS-KS 1.5 and TRACE 5.0 Patch 6, and a comparative analysis with experimental and calculation results has been performed. The main objective of this study is the investigation of the thermal-hydraulic phenomena during a small break LOCA at the RPV upper head with the LSI as well as the predictability of the system analysis codes after the AM actions during the test. The results from both codes reveal that overall physical behaviors during the accident are predicted by the codes, appropriately, including the excursion of the peak cladding temperature because of the LSI. It is also confirmed that the core integrity is maintained with the proposed AM action. Considering the break location, a sensitivity analysis for the nodalization of the upper head has been conducted. The sensitivity analysis indicates that the nodalization gave a significant impact on the analysis result. The result emphasizes the importance of the nodalization which should be performed with a consideration of the physical phenomena occurs during the transient.

Event diagnosis method for a nuclear power plant using meta-learning

Artificial intelligence (AI) techniques are now being considered in the nuclear field, but application faces with the lack of actual plant data. For this reason, most previous studies on AI applications in nuclear power plants (NPPs) have relied on simulators or thermal-hydraulic codes to mimic the plants. However, it remains uncertain whether an AI model trained using a simulator can properly work in an actual NPP. To address this issue, this study suggests the use of metadata, which can give information about parameter trends. Referred to here as robust AI, this concept started with the idea that although the absolute value of a plant parameter differs between a simulator and actual NPP, the parameter trend is identical under the same scenario. Based on the proposed robust AI, this study designs an event diagnosis algorithm to classify abnormal and emergency scenarios in NPPs using prototypical learning. The algorithm was trained using a simulator referencing a Westinghouse 990 MWe reactor and then tested in different environments in Advanced Power Reactor 1400 MWe simulators. The algorithm demonstrated robustness with 100 % diagnostic accuracy (117 out of 117 scenarios). This indicates the potential of the robust AI–based algorithm to be used in actual plants.

Estimating Allowable Operator Action Time for Mitigating Multiple‐Failure Accidents in Korean Advanced Power Reactor

In the case of multiple‐failure accidents in light water reactors, it is imperative to demonstrate that a significant fuel damage can be prevented via prearranged mitigation measures performed by operators. However, the time elapsed from the initiation of the event to the implementation of mitigation actions significantly influences the progress and consequences of the accident. Therefore, assuming a specific time for operator mitigation actions does not provide sufficient insights for safety assessments, thereby calling for further investigations into the effect of the time delay from the prescribed value. In this study, the allowable operator action time for multiple‐failure accidents of the Advanced Power Reactor 1400 was estimated by means of the sensitivity analysis using multi‐dimensional analysis for reactor safety‐KINS standard (MARS‐KS), a best‐estimate thermal–hydraulic analysis code used by the Korean nuclear regulatory authority. Three multiple‐failure accidents were investigated, including small‐break loss‐of‐coolant accident with the loss of safety injection (SI), intermediate‐break loss‐of‐coolant accident with the loss of SI, and total loss of feedwater accident. The upper limit of the mitigation action time, which prevents core damage, was estimated based on the requirement for peak cladding temperature. This was in turn used to derive the tolerable delay from the assumed action time in the Korean accident management program for each multiple‐failure accident.

Discussing the possibility of using thorium-based fuels as an alternative fuel to uranium dioxide fuel for APR-1400 reactor

This work investigates the possibility of using thorium-based fuels as an alternative fuel for advanced power reactor APR-1400. MCNPX code version 2.7 with cross-section library ENDF.VII has been used to design an APR-1400 fuel assembly. This code has been used to study the neutronic performance of the proposed thorium-based Fuel types (0.944Th, U)O2, (0.955Th, 233U)O2, (0.934Th, rgPu)O2. The fuel burn-up parameters such as infinity multiplication factor (kinf), initial heavy metals concentrations, Minor actinides concentration and fission products concentration have been analyzed during 1500 effective full power days (FPDSs) for thorium-based Fuel types and compared with the common fuel. The analysis of the horizontal thermal power and neutron flux distribution provides valuable insights into the behavior and performance of the suggested Fuel types in the APR-1400 assembly. The analysis of the neutronic results ensures the viability of using the proposed thorium-based fuel types as an alternative fuel to UO2 because they achieved acceptable safety parameter values and provided a good power distribution through the fuel assembly compared to UO2.

Improvement of CFD code for two-phase flow with boiling and natural convection for evaluation of core-catcher cooling performance in OpenFOAM

The PECS (Passive Ex-vessel corium retaining and Cooling System) is installed inside the EU (European Union)-APR (Advanced Power Reactor) 1400 to prevent CCI (corium-concrete interaction) and to cool down the corium under an ex-vessel severe accident. The main phenomenon in the PECS is the natural convection of the cooling water generated by the heat from the corium. A verification experiment on the cooling capability of the PECS has been conducted in the CE (Cooling Experiment)-PECS. A benchmark CFD analysis of the CE-PECS (Cooling Experiment-PECS) was performed using the modified OpenFOAM solver. In this study, the physical properties such as specific heat, dynamic viscosity, and density of water were modified to provide inputs as a function of temperature. Since the modified solver was developed to analyze PECS, the mesh was made as simple as and the number of cells is also optimized to reduce the computational load. As a result of a simulation using the improved solver, the prediction of both the mass flow rate and the temperature change of the cooling water showed good accuracy compared to the case of inputting the existing constant properties.

Comparative analysis of associated cost of nuclear hydrogen production using IAEA hydrogen cost estimation program

The interest in non-electric applications of nuclear energy is rising ranging from hydrogen production, district heating, seawater desalination, and various industrial applications to provide long-term answers for a variety of energy issues that both present and future generations will confront. Hydrogen is a dynamic fuel that can be used across all industrial sectors to lower carbon intensity. This study, therefore, aims at estimating the cost of nuclear hydrogen production from some light water reactors using International Atomic Energy Agency (IAEA) Hydrogen Calculator (HydCalc) program and comparing the result with similar existing studies conducted by other scholars using the Hydrogen Economic Evaluation Program (HEEP) program. The study employs six existing Light Water Reactors (LWRs) comprised of Korea Advanced Power Reactor 1400 MW electricity (APR1400), Russian VVER-1200, Davis-Besse Nuclear Power Plant in Ohio, Prairie Island NPP in Minnesota, Nine Mile Point NPP in New York, and Arizona Public Service's Palo Verde NPP to evaluate the Levelized cost of nuclear hydrogen production. Estimation of hydrogen demand was performed without carbon dioxide (CO2) tax since nuclear power has zero CO2 emission. The Levelized costs obtained using IAEA HydCalc and HEEP Programme were compared as follows; APR1400 cost are 2.6$/kg and 3.18$/kg, VVER1200 cost are 3.8$/kg and 3.44$/kg; Exelon cost are 1.7$/kg and 4.85$/kg; Davis Besse cost are 3.9$/kg and 3.09$/kg; Parlo Verde cost are 3.5$/kg and 4.77$/kg; Xcel Energy cost are 3.63$/kg and 0.69$/kg. The cost of hydrogen production using HEEP for Xcel Energy's Prairie Island NPP is 0.69 $/kg. This is because the reactor utilizes High Temperature Steam Electrolysis, method of hydrogen production, while the other methods employs Low Temperature Electrolysis. The results shows that the final price of the hydrogen for each reactor technology depends not only on the production method but also on the cost of the nuclear power plant and the production rate of the hydrogen plant.

Analysis of nuclear accident scenarios and emergency planning zones for a proposed Advanced Power Reactor 1400 (APR1400)

Radiological scenario analysis considering potential accidents and the corresponding emergency planning arrangements are based on the estimations of radioactive releases following such accidents. This involves investigating the possible effects on the surrounding population and environment. The current paper hypothesized three accident scenarios in a pressurized water reactor (PWR) proposed to be located in Khor Duweihin on the Western Coast of the Arabian Gulf. HotSpot tool was used to estimate the total effective dose equivalent (TEDE) due to certain released radionuclides of different chemical groups. Initial emergency planning arrangements were defined based on the estimated doses triggered by the hypothetical scenarios considered: loss of coolant accident (LOCA), station blackout (SBO) and steam generator tube rupture (SGTR) in an Advanced Power Reactor 1400 (APR1400). This study established a baseline for an emergency plan that assures the mitigation of radiological consequences due to probable nuclear accidents, involving preparedness based on forecasting the atmospheric dispersion of radionuclides released during potential scenarios in different meteorological conditions.

Analysis of 4-inch cold leg top-slot break LOCA in ATLAS experimental facility using MARS-KS

Abstract Korea Atomic Energy Research Institute (KAERI) has operated an integral effect test facility, the Advanced Thermal-Hydraulic Test Loop for Accident Simulation (ATLAS) with reference to the Advanced Power Reactor 1400 MW (APR1400) for transient and design basis accidents (DBAs) simulation. An experiment for a 4-inch cold leg top-slot break was performed at ATLAS to resolve a safety issue that the loop seal reformation (LSR) of APR1400 could lead to the increase of peak cladding temperature. In addition, the experimental data has been utilized to validate system codes within a framework of domestic standard problem (DSP) program organized by KAERI in collaboration with Korea Institute of Nuclear Safety (KINS). In this study, the experiment has been analyzed by thermal-hydraulic system analysis code, MARS-KS 1.5 and a comparison with experimental and calculation results has been performed. Since the top-slot break is not a typical break geometry for safety analyses, this study aims at examining the applicability of MARS-KS to the top-slot break accident where the LSR occurs repeatedly. The results revealed that overall physical behavior during the accident was predicted by the code, appropriately. MARS-KS showed the excursion of the peak cladding temperature because of the LSR as in experiment. It has been confirmed that the core integrity was maintained because the temperature excursion by the LSR was not large enough to alter the acceptance criteria. In addition, it is presented the results of the sensitivity analysis of parameter that affect the figure of merits.

The APR1400 SOARCA study: Insights into the evolution of severe accidents and fission product source term analysis results

The Korean utility, KHNP (Korea Hydro and Nuclear Power Co.), carried out a three-year research study in July 2016 (named the Korean SOARCA: K-SOARCA), which is similar with the United State (US) SOARCA (State-of-the-Art Reactor Consequence Analysis) study. One of the two reference reactors designated for the study was Advanced Power Reactor of 1400 MWe (APR1400). To consider the integral response of the reactor, steam generators, and containment to severe accidents initiated by the representative accident sequences selected from the plant-specific Probabilistic Safety Assessment (PSA) results, dedicated modeling was performed for a broad spectrum of plant safety/mitigation systems and relevant phenomena influencing the evolution of the accident. The influence of dedicated accident mitigation strategies on the evolution of accident progression and fission product source terms was also investigated to assess their effectiveness in coping with relevant severe accident sequences. Especially, relating to the APR1400 SOARCA, the latest versions of two severe accident analysis codes, MELCOR 2.2 and MAAP5.04, were used to compare the analysis results of interest. This paper presents best-practice analysis results for the evolution of key accidents and plant response including the environmental release of radiological fission product Cs (cesium), as implemented through the APR1400 SOARCA study, and relevant insights.

Integral-Effect Test for Loss of Residual Heat Removal System During Mid-Loop Operation in ATLAS Facility

A test called B4.2 in the OECD-ATLAS2 project was performed to simulate loss of the residual heat removal system (RHRS) during mid-loop operation (MLO) using a thermal-hydraulic (T-H) integral-effect test facility: the Advanced Thermal-Hydraulic Test Loop for Accident Simulation (ATLAS). The main purpose of this test was to investigate a T-H transient in the reactor coolant system (RCS) during loss of the RHRS and to evaluate the effectiveness of reflux condensation and the capability of a safety injection tank (SIT) on shutdown coolability. The initial and boundary conditions for the B4.2 test were appropriately determined according to a state of MLO corresponding to 65 h after reactor trip in the Advanced Power Reactor 1400 MW(electric) (APR1400). During the loss of RHRS accident transient simulation, major T-H parameters such as system pressures, temperatures, and collapsed water levels in the RCS were measured, and unique T-H phenomena such as reflux/cocurrent condensations, off-take, countercurrent flow, and countercurrent flow limitation were investigated. In this paper, the overall T-H behavior in the RCS during a simulated loss of the RHRS with SITs is highlighted to provide a better understanding of T-H phenomena regarding coolability with reflux condensation.

Analysis of LBLOCA of APR1400 with 3D RPV model using TRACE

It is very difficult to capture the multi-dimensional phenomena such as asymmetric flow and temperature distributions with the one-dimensional (1D) model, obviously, due to its inherent limitation. In order to overcome such a limitation of the 1D representation, many state-of-the-art system codes have equipped a three-dimensional (3D) component for multi-dimensional analysis capability. In this study, a standard multi-dimensional analysis model of APR1400 (Advanced Power Reactor 1400) has been developed using TRACE (TRAC/RELAP Advanced Computational Engine). The entire reactor pressure vessel (RPV) of APR1400 has been modeled using a single 3D component. The fuels in the reactor core have been described with detailed and coarse representations, respectively, to figure out the impact of the fuel description. Using both 3D RPV models, a comparative analysis has been performed postulating a double-ended guillotine break at a cold leg. Based on the results of comparative analysis, it is revealed that both models show no significant difference in general plant behavior and the model with coarse fuel model could be used for faster transient analysis without reactor kinetics coupling. The analysis indicates that the asymmetric temperature and flow distributions are captured during the transient, and such nonuniform distributions contribute to asymmetric quenching behaviors during blowdown and reflood phases. Such asymmetries are directly connected to the figure of merits in the LBLOCA analysis. Therefore, it is recommended to employ a multi-dimensional RPV model with a detailed fuel description for a realistic safety analysis with the consideration of the spatial configuration of the reactor core.

인공신경망을 이용한 불안정 전력망에 접속된 발전기 변압기 OLTC 제어

The safe and economic operation of the nuclear power plant (NPP) requires that the plant be connected to a stable and reliable electric grid where the voltage and frequency can be controlled within predefined limits. For a country introducing NPP for the first time, such stable and reliable grid may not exist and the grid may experience voltage and frequency fluctuations beyond the acceptable limits for extended periods. This paper therefore analyzes the necessity of installing an on-load tap changer (OLTC) on the main transformer (MT) of the NPP for automatic and fine voltage control in the event of severe voltage degradation on the Nigeria’s electric grid. IEEE Std. C57.116-2014 power transfer equation and load flow analysis using the electrical transient analyzer program (ETAP®) approach were used for this study. The paper also proposes implementation of artificial neural network (ANN) as a control mechanism for the effective and efficient operation of the MT OLTC tap settings. The research is based on the hypothetical generator output voltage of the proposed advanced power reactor (APR1400) unit connected to the Nigerian electric grid. Implementing the ANN model for MT OLTC automatic control enables stable operation even for the large synchronous generators connected to highly fluctuating voltage grids exceeding the +/-5% voltage range.

Numerical Analysis for Hydrogen Flame Acceleration during a Severe Accident Initiated by SBLOCA in the APR1400 Containment

We performed a hydrogen combustion analysis in the Advanced Power Reactor 1400 MWe (APR1400) containment during a severe accident initiated by a small break loss of coolant accident (SBLOCA) which occurred at a lower part of the cold leg using a multi-dimensional hydrogen analysis system (MHAS) to confirm the integrity of the APR1400 containment. The MHAS was developed by combining MAAP, GASFLOW, and COM3D to simulate hydrogen release, distribution and combustion in the containment of a nuclear power plant during the severe accidents in the containment of a nuclear power reactor. The calculated peak pressure due to the flame acceleration by the COM3D, using the GASFLOW results as an initial condition of the hydrogen distribution, was approximately 555 kPa, which is lower than the fracture pressure 1223 kPa of the APR1400 containment. To induce a higher peak pressure resulted from a strong flame acceleration in the containment, we intentionally assumed several things in developing an accident scenario of the SBLOCA. Therefore, we may judge that the integrity of the APR1400 containment can be maintained even though the hydrogen combustion occurs during the severe accident initiated by the SBLOCA.

PARTICLE SWARM OPTIMIZATION BASED PROBABILISTIC NEURAL NETWORK FOR CLASSIFICATION OF SEVERE ACCIDENT OF NUCLEAR REACTOR

Due to its danger and complexity, the identification and prediction of major severe accident scenarios from an initiating event of a nuclear power plant remains a challenging task. This paper aims to classify severe accident at the Advanced Power Reactor (APR) 1400, which includes the loss of coolant accidents (LOCA), total loss of feedwater (TLOFW), station blackout (SBO), and steam generator tube rupture (SGTR) using a standard probabilistic neural network (PNN) and Particle Swarm Optimization Based Probabilistic Neural Network (PSO PNN). The algorithm has been implemented in MATLAB. The experiment results showed that supervised PNN PSO could classify severe accident of nuclear power plant better than the standar PNN.

Fire resistance of bi-directionally prestressed concrete under extreme fire loading

Infrastructures such as prestressed concrete containment vessels (PCCVs) and liquid gas storage tanks are constructed as bi-directional prestressed concrete (PSC) structures to ensure outstanding leak-tight storage and shielding performance. However, PSC structures exhibit severe vulnerability to high-temperature fire due to the high-strength concrete used and the application of prestressing (PS) stresses to increase the strength of the structures. The PCCV of a 1400 MW advanced power reactor was selected as the target for study. A scaled-down model of the PCCV outer wall was fabricated and tested to determine its resistance to a standard fire-loading scenario. Furthermore, different PS forces were applied to the specimens to evaluate the effect of concrete confinement on the fire resistance. Test data of temperature distribution, PS force loss and residual strength capacity were obtained. The experimental data were used for calibration of a commercial finite-element simulation program (Midas FEA) for structural fire analysis of real-scale concrete structure and infrastructure. The simulation and test results showed significant similarity and the result trends were accurate.

Machine Learning-Based Classification and Regression Approach for Sustainable Disaster Management: The Case Study of APR1400 in Korea

During nuclear accidents, decision-makers need to handle considerable data to take appropriate protective actions to protect people and the environment from radioactive material release. In such scenarios, machine learning can be an essential tool in facilitating the protection action decisions that will be made by decision-makers. By feeding machines software with big data to analyze and identify nuclear accident behavior, types, and the concentrations of released radioactive materials can be predicted, thus helping in early warning and protecting people and the environment. In this study, based on the ground deposition concentration of radioactive materials at different distances offsite in an emergency planning zone (EPZ), we proposed classification and regression models for three severe accidents. The objective of the classification model is to recognize the transient situation type for taking appropriate actions, while the objective of the regression model is to estimate the concentrations of the released radioactive materials. We used the Personal Computer Transient Analyser (PCTRAN) Advanced Power Reactor (APR) 1400 to simulate three severe accident scenarios and to generate a source term released to the environment. Additionally, the Radiological Consequence Analysis Program (RCAP) was used to assess the off-site consequences of nuclear power plant accidents and to estimate the ground deposition concentrations of radionuclides. Moreover, ground deposition concentrations at different distances were used as input data for the classification and regression tree (CART) models to obtain an accident pattern and to establish a prediction model. Results showed that the ground deposition concentration at a near distance from a nuclear power plant is a more informative parameter in predicting the concentration of radioactive material release, while the ground deposition concentration at a far distance is a very informative parameter in identifying accident types. In the regression model, the R-square of the training and test data was 0.995 and 0.994, respectively, showing a mean strong linear relationship between the predicted and actual concentration of radioactive material release. The mean absolute percentage error was found to be 26.9% and 28.1% for the training and test data, respectively. In the classification model, the model predicted a scenario (1) of 99.8% and 98.9%, scenario (2) of 98.4% and 91.6%, and scenario (3) of 98.6% and 94.7% for the training and test data, respectively.

Optimal earthquake intensity measures for probabilistic seismic demand models of ARP1400 reactor containment building

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R2), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

STPA-Based Hazard and Importance Analysis on NPP Safety I&C Systems Focusing on Human–System Interactions

To ensure system safety, conducting required control actions (CAs) in time at the right place is essential. Among the CAs, safety critical ones such as reactor trip signals in a nuclear power plant are preferentially and automatically generated by the instrumentation and control (I&C) system. If necessary, however, they can also be generated manually by human operators. Even for manual CAs, though, the I&C system is still needed to convey relevant feedback to the human operators. It is therefore indispensable to analyze the risk associated with the transmission of feedback to the human operators in terms of the condition of the I&C system. In this context, System-Theoretic Process Analysis (STPA) can provide a framework to link the conditions of the I&C system with the feedback transmission for manual CA generation. Based on STPA, this study proposes a method to analyze I&C system hazards and assess the relative importance of system components in terms of human–system interactions, or more specifically, feedback transmission for manual CA generation. As a feasibility study, the method is applied to an example case requiring reactor trip signal generation in the Advanced Power Reactor 1400 (APR-1400).