bluuebunny/crossref_metadata_2025_split huggingface dataset:
CFD Simulation of Water Hammer Induced by Condensation Using an Improved Phase Change Model
Authors: Peng Li , Tu Ruiyang , Lin Daping , Xiong Feng , Zhao Jiaming , Long Xiaoxin , Chen Zhengyu , Zhang Zihao , Guo Wentao , Wang Shengfei 
Published: November 2024

Abstract
A computational fluid dynamics (CFD) based approach using FLUENT is applied to investigate the phenomenon of condensation-induced water hammer (CIWH) caused by direct contact condensation. In these simulations, the two-phase interface is explicitly tracked using the volume of fluid (VOF) method, and a hybrid heat transfer coefficient (HTC) model based on surface renewal theory is employed for interface heat transfer. The HTC model is implemented through user-defined functions (UDFs). The simulation results are compared with experimental data obtained from the PMK-2 facility of the VVER-440/312-type nuclear power plant in Budapest, Hungary. The results demonstrate that the model aligns well with the measured temperature field, as well as the timing and magnitude of pressure peaks. This CFD approach can be utilized for prediction and prevention of CIWH.
Few-Shot Learning for Abnormal Event Detection in Nuclear Power Plants
Authors: Zhang Tianhao , Guo Chao , Jia Qianqian , Huang Xiaojin 
Published: November 2024

Abstract
Recent research on abnormal event detection in nuclear power plants (NPPs) increasingly adopts the data-driven method, aiming to identify anomalies by harnessing vast operational data without needing prior knowledge of plant system dynamics. However, the limited availability of abnormal samples within NPPs affects the detection accuracy of data-driven methods. This paper introduces a few-shot learning approach based on neural networks to develop an efficient anomalous event detector using sparse samples within NPPs. To achieve this, a neural network structure is employed for operational feature extraction to facilitate the transformation of input data into lower-dimensional vectors with embedded space. Then, a prototypical network is introduced to derive a prototype for each abnormal event class based on a few embedded vector training samples. In this way, the anomaly type in a new instance can be identified by comparing the similarity of its embedded vector to each prototype. Experimental results illustrate that the proposed approach achieves high abnormal event detection accuracy.
Underlying Deep Learning Networks Diagnosis Evaluation and Generative Adversarial Network Data Augmentation Based on a Benchmark Accident Dataset
Authors: Qi Ben , Wang Yu , Xiao Xingyu , Liang Jingang 
Published: November 2024

Abstract
Nuclear energy plays an important role in the global energy supply, particularly as a key source of low-carbon electricity, while ensuring the safe operation of nuclear power plants (NPPs) is crucial. Given the significant impact of human-caused errors on three serious nuclear accidents in history, artificial intelligence (AI) has been increasingly interested assisting operators in NPP accident diagnosis. However, the field has lacked a benchmarking effort for underlying deep learning networks based on public datasets for accident diagnosis, as well as research on time-series data augmentation efforts for accident data. Based on the first open-source NPP accident dataset NPPAD, which covers all kinds of accident data of pressurized water reactors and has been validated with Fukushima nuclear accident data for reliability, this study explored accident diagnostic techniques based on Multilayer Perceptions (MLPs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Transformers, and data augmentation techniques based on conditional Generative Adversarial Networks (cGANs) and Time-series Generative Adversarial Networks (TimeGANs). Experimental results show Transformers have the best classification ability for accident types. In addition, the standardization of data has a large impact on the classification effect, and standardization in data preprocessing will make all models substantially more effective. For data augmentation, TimeGANs exhibit higher performance compared to cGANs in generating fake datasets and can better capture the dynamic features of time-series data. This paper provides a reference for the application of deep learning through the study of three parts: a comprehensive comparison of underlying deep learning networks, data standardization processing, and data augmentation.
Impact of Synoptic Weather Patterns Along the Pacific Coastline of Japan on Tornado Wind Hazard Curves
Authors: Fujiwara Kota , Nohara Daisuke , Eguchi Yuzuru , Hattori Yasuo , Hirakuchi Hiromaru 
Published: November 2024

Abstract
The present study focuses on the wind hazard assessment along the Pacific coastline of Japan by categorizing tornado data based on synoptic weather patterns. The region faces unique challenges, including tornadoes occurring over the sea and a restricted area of interest along the coastline, leading to potential sampling issues. To address these challenges, the TOrnado Wind speed hazard for Limited Area (TOWLA) model was employed. Tornado data were classified into seven synoptic weather patterns. The hazard analysis conducted for each of these synoptic weather patterns along in the Pacific coastline region revealed that extra-tropical cyclones, typhoons, and monsoon (summer) were significant contributors to high-risk events. Monsoon (winter) had the highest tornado counts but lacked severity. Typhoons, exhibiting a distinct formation mechanism, presented a unique hazard factor along the Pacific coastline, which require verification through comparisons with other areas.
Experimental Study in Cooling Rate by Containment Spay
Authors: Wang Ning , Yang Yapeng , Liu Zhe 
Published: November 2024

Abstract
In case of loss of coolant accident, temperature and pressure in the containment would rise due to evaporation of coolant. Besides, radioactive aerosol and gas could possibly release to the containment in case of severe accident. Containment spray system is designed to cool it down, reduce its pressure and remove airborne radioactive material. According to NUREG 1465, 95% of released fission product exists in form of aerosol. Therefore, one experimental apparatus for typical China three loop PWR was built to investigate the above phenomenon. It consists of 4 parts: 1) spray vessel, which simulates reactor containment; 2) Spray system; 3) measurement system including temperature, pressure and flow rate; 4) Water tank, which stores and provides spray water. The spray vessel is 2.0m high with an internal diameter of 1.0m. There are 9 temperature sensors inside the spray vessel. The maximal design pressure of the vessel is 0.8MPa and maximal design temperature is 180°C. The spray tank is 1.0m high with an internal diameter of 1.0m. Temperature is the key factor that influence the behavior of aerosol, so the cooling rate experiment was conducted before the aerosol removal coefficient experiment. In this paper, experiments were conducted to obtain cooling rate by containment spay, which was the basis for aerosol removal coefficient experiment. Temperature distribution of spray vessel during the spray was obtained and cooling down rate was measured. Results show that spray flow rate and spray water temperature are the main parameters that determines cooling down rate. In future, aerosol spray removal coefficient will be obtained.
Research on the Localization Method of Loose Components in Nuclear Power Plants Based on Hilbert-Huang Signal Processing
Authors: Jiang Jiming , Liu Yu , Lu Daogang 
Published: November 2024

Abstract
During the service cycle of the nuclear power plant, due to factors such as construction renovation, irradiation, and other factors, loose parts may transfer along the flow of coolant in the primary circuit, which may lead to the failure of the RCP system and even cause the failure of the primary circuit containment state. The Loose Part Monitoring System (LPMS) is used to detect, locate, and estimate possible loose parts in the reactor primary circuit. To accurately locate the position of loose components, identify and track their trajectory within the system, and facilitate subsequent maintenance and troubleshooting, this paper applies the Hilbert Huang transform to extract the main frequency of the impact signal to achieve accurate measurement of the signal arrival time. Due to the unique advantages of its nonlinear and adaptive signal decomposition method, it can separate the amorphous vibration waveforms in the signal with the highest confidence. By determining the peak time of the first envelope curve after Hilbert transformation, the accurate measurement of signal arrival time can be realized conveniently. Based on the triangulation method, the time difference of the sensors obtained can accurately locate the impact location. To verify the effectiveness of the method, the algorithm validation is carried out on a small model, and the results show that the proposed localization method based on Hilbert’s yellow transform achieves significant results in the localization of impact signals, and can achieve fast localization. Finally, a digital twin system is proposed based on simulation to assist the LPMS system for fast localization by iteratively obtaining a collision moment lookup table.
Investigation on Development of New Mechanistic Model for Post Dryout Heat Transfer
Authors: Xia Zihan , Cheng Xu 
Published: November 2024

Abstract
During some transient scenarios such as loss of coolant accident (LOCA) in nuclear power plants, dryout could occur in fuel assemblies. The heat transfer after dryout will determine the maximum cladding temperature when dryout occurs. Therefore, identifying the heat transfer mechanism and predicting heat transfer in Post-dryout (PDO) region will be particularly important for facility safety operation. In the post dryout region, the behaviour of droplets may significantly affect the heat transfer and subsequently, the wall temperature. When droplets move toward the wall due to turbulence dispersion effect, most of the droplets will be completely evaporated inside the vapor layer or bounced back to the mainstream. Therefore, in this paper, the flow area is divided into the central region and the near-wall region considering the large difference in vapor superheating between wall and tube center. The interfacial heat transfer is calculated separately in these two regions with a correlation of vapor temperature profile obtained from CFD results. There will be droplet mass exchange between the two regions due to the concentration difference caused by the fluctuation velocity profile. The calculation results were compared with Becker’s water PDO experimental results, and it was found that the predicted wall temperature were in good agreement with the experimental data. It shows that the new model can improve the prediction accuracy of heat transfer in the post dryout region.
Performance Analysis for Enhanced Cr-Coated Fuel Cladding System in APR-1400 Reactor
Authors: Alzarooni Asma , Alrwashdeh Mohammad , Alameri Saeed A. 
Published: November 2024

Abstract
The conventional Zircaloy-uranium fuel-cladding system in pressurized water reactors faces challenges such as reduced mechanical strength, stability, and susceptibility to oxidation and embrittlement at high temperatures. The Accident Tolerant Fuel concept, aiming to address these issues, involves replacing or coating cladding with materials exhibiting enhanced corrosion resistance. This study explores the efficacy of ATF using a chromium coating and selecting an adhesive layer material (Niobium or Molybdenum) between cladding and coating. Neutronics analyses, employing the Serpent Monte Carlo 2.31 simulation tool on the APR-1400 reactor, assess the impact on different neutronics parameters. A sensitivity analysis involves varying coating thickness (10 μm, 15 μm, 20 μm) and adhesive layer thickness (2.20 μm, 3.20 μm, 4.20 μm) for Zircaloy cladding. Results show that adjusting ATF design parameters can match the original fuel-cladding cycle length. The 10 μm coating with 2.2 μm Nb adhesive layer exhibits minimal neutronics impact, suggesting it as an alternative cladding material. In 2D reactor core analysis, Nb outperforms Mo due to a lower reactivity difference and smaller absorption cross-section, enhancing thermomechanical properties with minimal neutronics impact. Implementing Cr-coating with Nb adhesive layers holds promise for enhancing safety and reliability in nuclear power plants, particularly in mitigating risks during high-temperature conditions and loss-of-coolant accidents.
Adaptive Refinement Simulation Model of Condenser Based on the Mechanism-AI Coupling Modeling Paradigm
Authors: Jing Furu , Xue Ruojun , Tang Jiaming , Chong Haofang 
Published: November 2024

Abstract
Condenser is widely regarded as the key equipment of nuclear energy utilization device, and its performance has an important influence on the safety, economy and stability of the whole nuclear energy utilization device. In this paper, aiming at the problems that the simulation accuracy of the condenser real-time simulation model is lower than that of the numerical calculation simulation method and it is difficult to realize self-adjustment according to the actual changes, the NSGA-III ( a multi-objective optimization algorithm ) related to machine learning in AI technology is introduced into the mechanism modeling method,, that is, a mechanism-AI coupling modeling method is adopted. The specific model construction process is divided into three steps : constructing the basic model of the condenser according to the fluid network method, using the AI algorithm to determine the reason for the reduction of the model accuracy, and coupling the mechanism model with the AI algorithm to construct the condenser adaptive refinement simulation model. Finally, the simulation of a condenser is carried out to verify the model. The results show that the mechanism-AI coupling model can further improve the simulation accuracy of the condenser under the condition of meeting the real-time simulation requirements. When the condenser parameters change, the model can be adjusted independently to reduce the error caused by the change of the condenser parameters.
Simulation and Analysis for Hualong Reactor Advanced Integrated Test Facility Based on RELAP5
Authors: Geng Yiwa , Zhan Jingxiang , Zheng Yuntao , Liu Jiatai , Huang Shuliang , Ni Si , Yang Changjiang 
Published: November 2024

Abstract
Hualong One and its subsequent rectors are the third-generation pressurized water reactor (PWR) and constructed by the China National Nuclear Corporation (CNNC) which possess completely independent intellectual property rights. China Nuclear Power Engineering Co., Ltd. (CNPE) designed and built an integrated test facility for the Hualong’s subsequent rectors emergency core cooling system (referred as Integrated Test Facility). The Integrated Test Facility is a large-scaled facility and designed based on the Hualong’s subsequent rectors’ safety systems, which adopts a passive safety design. The Integrated Test Facility includes main loop system, High-Pressure Makeup Tank (HPMT), Accumulator (ACC), Automatic Depressurization System (ADS), Outside Reactor Water Storage Tank (ORWST), Direct Vessel Injection (DVI) pipeline, Sump, Passive Residual Heat Removal System (PRS), Passive Containment Cooling System (PCS), etc. These systems and equipment work together to achieve passive emergency core cooling function. In this paper, a RELAP5 model is establish to analyze a small LOCA accident sequence. Simulations are conducted for five stages after the accident, including natural circulation, automatic depressurization, safety injection, and long-term sump recirculation. A 4MW core power (with operation pressure 15.5MPa, core inlet temperature 292.4 Celsius degrees, core outlet temperature 327.7 Celsius degrees) and medium pressure model was established. The emergency core cooling system operational characteristics were investigated under small break loss of coolant accident (SBLOCA). The simulation results demonstrated that the RELAP5 model can simulate the transient key system parameters accurately. This paper investigates the operational characteristics of the emergency core cooling system under different LOCA conditions, elucidates the interaction mechanisms of passive safety systems, and explores the physical mechanisms of thermal-hydraulic phenomena and processes in the integrated test facility. Based on numerical simulation analysis, the experimental data under accident conditions are obtained, thereby validating the rationality of the safety system design for the integrated test facility and the effectiveness of the accident analysis modeling method.
Research on Computation Method of Bubble Volume Based on Machine Learning
Authors: Ding Yongwang , Liu Xinxing , Meng Zhaoming , Zhang Han , Li Fu 
Published: November 2024

Abstract
In the case of low-speed jet flow and high undercooling degree, the condensation process in the reactor suppression system is often accompanied by low-frequency oscillations, namely the chugging phenomenon. The mechanism of oscillation is related to the formation, condensation, and collapse of bubbles. The accuracy of extracting bubble geometry parameters directly impacts the analysis of condensation oscillation mechanisms. The calculation of geometric parameters of bubbles using traditional image processing techniques often involves complex pre-processing, and the feature parameters need to be defined manually. There are some issues, such as significant user effects and long computation time. Therefore, based on traditional methods, this paper proposes a more efficient algorithm for extracting image feature parameters using convolutional neural networks (CNN). The results show that the performance of the newly proposed method under a single condition is satisfactory, and its generalization performance across different backgrounds is also good. The average additional error of extracted feature parameters is less than 2%, but the extraction cost can be significantly reduced.
Feasibility and Safety Analysis of Solid-State Reactor for Lunar Surface Exploration
Authors: Ma Yugao , Lu Jiahao , Liu Yue , Zhang Suyi , Zhang Muhao 
Published: November 2024

Abstract
The Fission Surface Power System is a feasible solution for future lunar surface exploration energy supply, with the solid-state reactor being considered a primary candidate. This paper presents a modeling and analysis of a solid-state reactor based on publicly available information.
Using the reactor Monte Carlo program RMC and the commercial finite element analysis software ANSYS, the reactor is modeled and analyzed. The power distribution of the active zone and reactivity feedback coefficients of the entire core are obtained. The result indicates a negative reactivity feedback coefficient, confirming this reactor design’s inherent safety. Furthermore, a two-dimensional reactor model is constructed to obtain the temperature distribution during full-power operation, and non-passive residual heat removal analysis and radiative heat loss failure analysis are performed. At the failure condition of all heat pipes, the maximum core temperature is 742 K, which is below the reactor safety temperature limit, confirming the residual heat removal capability of the solid-state reactor in the loss of heat sink. Additionally, the self-developed transient reactor system analysis program is used for thermal safety analysis. The thermal parameters and heat transfer limits of high-temperature alkali metal heat pipes within the reactor are obtained, with the ratio of heat transfer limit to the heat load of 2.05 demonstrating sufficient safety margins of the heat pipe operation in the reactor. The results manifest that the core is satisfied with the existing criteria for anticipated operating occurrences of solid-state reactors, verifying the excellent safety performance of this reactor design.
Based on the analysis and calculations in this study, it is concluded that this reactor design exhibits superior safety performance, which is attributed to the neutron physics design concept of the intermediate neutron spectrum and the thermal-hydraulic design concept of non-passive residual heat removal. This study contributes to the field of advanced nuclear reactor engineering by providing a comprehensive analysis of the solid-state reactor design for the Fission Surface Power System. The findings highlight the superior safety performance and potential application of this solid-state reactor design for future lunar surface exploration, which has important implications for the development of lunar surface reactors.
Seismic Response of NPP Considering the Non-Linear Soil-Structure Interaction Effects Using DRM
Authors: Jang Youngsun , Lee Youngoh 
Published: November 2024

Abstract
For improvement of seismic capacity of NPP, the Non-linear SSI (NLSSI) analysis concepts are studied and applied to practical NPP (Nuclear Power Plant) Structural Analysis. Nonlinear SSI analysis requires a different approach from existing linear and frequency domain SSI analysis. In order to consider the non-linear behavior of the ground and structural materials, the analysis must be performed in the time domain, but this is difficult due to a large analysis model and many repetitive analyzes. Accordingly, many researches are being actively conducted to introduce a hybrid method that sets a certain region as the near field, adds boundary elements, and conducts analysis in the frequency domain or time domain. DRM (Domain Reduction Method) is a method proposed by Bielak et al. by developing several theories for calculating effective seismic force, and is the most widely used technique when analyzing NLSSI using the sub-structure method. This method is also provided in LS-DYNA. In this study, the Korean NPP Structures are analyzed with ABAQUS program in the time domain for the NLSSI analysis. The Linear SSI analysis of the NPP Structure is performed with ACS SASSI program in the frequency domain at same time, and LSSI analysis result is compared to NLSSI analysis result. The final produce of NLSSI analysis is the FRS (Floor Response Spectrum) at each story of building. After NLSSI analysis, FRS will be provided for re-calculation of the HCLPF (High Confidence of Low Probability of Failure) of some critical equipment that contribute significantly to the CDF (Core Damage Frequency).
Experimental Study on Startup and Heat Transfer Performance of High Temperature Sodium Heat Pipe
Authors: Jiang Shunli , Zhou Huihui , Zhang Youjia , Yuan Dewen , Huang Shanfang 
Published: November 2024

Abstract
The screen-wick sodium heat pipe is a highly effective passive device for heat transfer that can operate under complex operating conditions. In this work, the startup process, steady-state heat transfer, and heat transfer limits of sodium heat pipe were experimentally studied and the influence law and mechanism of the heating power, inclination angle, and cooling condition on the heat transfer of the heat pipe have been discussed. The experimental results show that high heating power will cause overheating, and even local dry out, leading to the failure of heat pipe. The increase of inclination angle will lead to irregular change of heat transfer. Geyser boiling will occur within a heating power range under the positive inclination angle, resulting in the significant temperature oscillation. The increase of cooling capacity will improve heat transfer power, and the critical startup power of the heat pipe is basically in a linear relationship with the length of the condenser. However, the excessive cooling may cause the heat pipe to fail to start and the operation of heat pipe at low temperatures is restricted by the sonic limit. This research may provide valid experimental data support and references for the design optimization and operation of high temperature heat pipes.