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Proceedings Papers

Analysis of Heat Transfer at Supercritical Conditions With Explainable Machine Learning Model

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Meiqi Song, Haozhe Li, Xiaojing Liu
Proc. ASME. ICONE31, Volume 6: Thermal-Hydraulics and Safety Analysis, V006T07A005, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-130237
https://doi.org/10.1115/ICONE31-130237
View Paper titled, Analysis of Heat Transfer at Supercritical Conditions With Explainable Machine Learning Model
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Topics: Algorithms, Heat transfer, Machine learning
Proceedings Papers

Research on Computation Method of Bubble Volume Based on Machine Learning

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Yongwang Ding, Xinxing Liu, Zhaoming Meng, Han Zhang, Fu Li
Proc. ASME. ICONE31, Volume 6: Thermal-Hydraulics and Safety Analysis, V006T07A065, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-135162
https://doi.org/10.1115/ICONE31-135162
View Paper titled, Research on Computation Method of Bubble Volume Based on Machine Learning
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Topics: Bubbles, Computation, Condensation, Convolutional neural networks, Image processing, Machine learning, Oscillations, Algorithms, Collapse, Errors
Proceedings Papers

An Online State Estimation Method Based on Quantum Genetic Algorithm for Space Nuclear Reactors

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Enping Zhu, Xiang Chai
Proc. ASME. ICONE31, Volume 7: Computational Fluid Dynamics (CFD) and Applications, V007T08A021, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-135080
https://doi.org/10.1115/ICONE31-135080
View Paper titled, An Online State Estimation Method Based on Quantum Genetic Algorithm for Space Nuclear Reactors
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Topics: Genetic algorithms, Machine learning, Nuclear reactors, State estimation
Proceedings Papers

Anomaly Detection of Thermal System Using CAE-DDQN Model

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Tong Li, Jiahao Cheng, Bo Wang, Sichao Tan, Ruifeng Tian
Proc. ASME. ICONE31, Volume 11: Student Paper Competition, V011T15A040, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-134870
https://doi.org/10.1115/ICONE31-134870
View Paper titled, Anomaly Detection of Thermal System Using CAE-DDQN Model
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Topics: Computer-aided engineering, Deep reinforcement learning, Thermal systems, Time series, Safety, Thermal engineering, Machine learning, Neural network models, Nuclear power, Accidents
Proceedings Papers

Surrogate Modeling Advancements in Nuclear Fuel Engineering: Bridging the Gap Between Accuracy and Efficiency

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Salvatore Angelo Cancemi, Michela Angelucci, Rosa Lo Frano, Sandro Paci
Proc. ASME. ICONE31, Volume 11: Student Paper Competition, V011T15A070, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-135798
https://doi.org/10.1115/ICONE31-135798
View Paper titled, Surrogate Modeling Advancements in Nuclear Fuel Engineering: Bridging the Gap Between Accuracy and Efficiency
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Topics: Metamodeling, Nuclear fuels, Artificial neural networks, Cladding systems (Building), Simulation, Temperature, Algorithms, Safety, Computer simulation, Design
Proceedings Papers

Machine Learning Approach to Analyzing Data in Japanese BWR Chemistry Database

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Gaku Yamazaki
Proc. ASME. ICONE31, Volume 1: Nuclear Plant Operation and Maintenance, Engineering and Modification, Operation Life Extension (OLE), and Life Cycle, V001T01A007, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-134463
https://doi.org/10.1115/ICONE31-134463
View Paper titled, Machine Learning Approach to Analyzing Data in Japanese BWR Chemistry Database
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Topics: Boiling water reactors, Chemistry, Databases, Machine learning, Radiation (Physics)
Proceedings Papers

Research on Interpretability Techniques in Two Widely Used Neural Network for Nuclear Power Plant Fault Diagnosis

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Jie Liu, Rafael Macián-Juan
Proc. ASME. ICONE31, Volume 1: Nuclear Plant Operation and Maintenance, Engineering and Modification, Operation Life Extension (OLE), and Life Cycle, V001T01A017, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-134882
https://doi.org/10.1115/ICONE31-134882
View Paper titled, Research on Interpretability Techniques in Two Widely Used Neural Network for Nuclear Power Plant Fault Diagnosis
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Topics: Artificial neural networks, Fault diagnosis, Machine learning, Nuclear power stations
Proceedings Papers

Strategies and Applications of Big Data and AI Technologies in Nuclear Power Public Opinion Prevention and Control System

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Yun Liang, Shaolin Zhang, Shangyuan Liu
Proc. ASME. ICONE29, Volume 14: Computer Code Verification and Validation; Nuclear Education and Public Acceptance, V014T15A013, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-93779
https://doi.org/10.1115/ICONE29-93779
View Paper titled, Strategies and Applications of Big Data and AI Technologies in Nuclear Power Public Opinion Prevention and Control System
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Topics: Control systems, Nuclear power, Carbon, Carbon neutrality, Simulation, China, Climate change, Construction, Emissions, Feedback
Proceedings Papers

Prediction of the Operating Control Rod Position of the HTTR With Supervised Machine Learning

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Hai Quan Ho, Satoru Nagasumi, Yosuke Shimazaki, Toshiaki Ishii, Kazuhiko Iigaki, Minoru Goto, Irwan Liapto Simanullang, Nozomu Fujimoto, Etsuo Ishitsuka
Proc. ASME. ICONE29, Volume 2: Nuclear Fuel and Material, Reactor Physics and Transport Theory, and Fuel Cycle Technology, V002T02A025, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-90826
https://doi.org/10.1115/ICONE29-90826
View Paper titled, Prediction of the Operating Control Rod Position of the HTTR With Supervised Machine Learning
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Topics: Machine learning, Safety
Proceedings Papers

Multiplication Factor Prediction Feasibility Study for the BEAVRS Core Based on the LSTM Algorithm

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Ren Chang-an, Lei Ji-chong, Yang Xiao-hua
Proc. ASME. ICONE29, Volume 1: Nuclear Plant Operation and Maintenance, Engineering and Modification, Operation Life Extension (OLE), and Life Cycle, V001T01A011, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-90164
https://doi.org/10.1115/ICONE29-90164
View Paper titled, Multiplication Factor Prediction Feasibility Study for the BEAVRS Core Based on the LSTM Algorithm
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Topics: Algorithms, Cycles, Engineering simulation, Errors, Machine learning, Simulation
Proceedings Papers

Research on Intelligent Classification Method of Primary Loop Transient in Nuclear Power Plant

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Run Ze Zhang, Zhi Lin Chen, Yong Qiang Huang, Xin Chen
Proc. ASME. ICONE29, Volume 1: Nuclear Plant Operation and Maintenance, Engineering and Modification, Operation Life Extension (OLE), and Life Cycle, V001T01A058, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-92874
https://doi.org/10.1115/ICONE29-92874
View Paper titled, Research on Intelligent Classification Method of Primary Loop Transient in Nuclear Power Plant
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Topics: Machine learning, Nuclear power stations, Transients (Dynamics)
Proceedings Papers

Anomalies Detection in Structures, System and Components for Supporting Nuclear Long Term Operation Program

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Salvatore Angelo Cancemi, Rosa Lo Frano
Proc. ASME. ICONE29, Volume 15: Student Paper Competition, V015T16A110, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-93193
https://doi.org/10.1115/ICONE29-93193
View Paper titled, Anomalies Detection in Structures, System and Components for Supporting Nuclear Long Term Operation Program
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Topics: Algorithms, Digital twin, Failure, Finite element analysis, Machine learning, Maintenance, Nuclear power stations, Nuclear reactors, Pipes, Pressure
Proceedings Papers

Applying Machine Learning to Improve BOA Analysis of CIPS/CILC

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Jun Liao, Alexander Mace, Guoqiang Wang, Jesse S. Fisher
Proc. ASME. ICONE29, Volume 2: Nuclear Fuel and Material, Reactor Physics and Transport Theory, and Fuel Cycle Technology, V002T02A095, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-94480
https://doi.org/10.1115/ICONE29-94480
View Paper titled, Applying Machine Learning to Improve BOA Analysis of CIPS/CILC
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Topics: Machine learning, Boron, Corrosion, Fuels, Nuclear power stations, Algorithms, Calibration, Chemistry, Cladding systems (Building), Computers
Proceedings Papers

Comparative Machine Learning Study for Estimating Peak Cladding Temperature in AP1000 Under LOFW

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Merouane Najar, He Wang
Proc. ASME. ICONE29, Volume 5: Nuclear Safety, Security, and Cyber Security, V005T05A022, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-91516
https://doi.org/10.1115/ICONE29-91516
View Paper titled, Comparative Machine Learning Study for Estimating Peak Cladding Temperature in AP1000 Under LOFW
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Topics: Cladding systems (Building), Machine learning, Temperature, Algorithms, Uncertainty quantification, Accidents, Safety, Uncertainty, Databases, Errors
Proceedings Papers

Exploration and Application of Ensemble Learning Method on Predicting Two-Phase Flow Key Parameters of Rectangular Channel

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Qingyu Huang, Yang Yu, Hui Zeng, Hui Yang, Siyuan Zhang, Kunlin Yang, Yuanfeng Lin
Proc. ASME. ICONE29, Volume 7A: Thermal-Hydraulics and Safety Analysis, V07AT07A074, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-92231
https://doi.org/10.1115/ICONE29-92231
View Paper titled, Exploration and Application of Ensemble Learning Method on Predicting Two-Phase Flow Key Parameters of Rectangular Channel
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Topics: Machine learning, Two-phase flow
Proceedings Papers

Data Driven Methods for Break Size and Location Estimation in LOCA Based on Deep Learning

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Peng Yuan, Jian Deng, Zhifang Qiu, Qinglan Xu, Dahuan Zhu, Tao Huang, Zhongchun Li, Peng Du
Proc. ASME. ICONE29, Volume 7B: Thermal-Hydraulics and Safety Analysis, V07BT07A006, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-92380
https://doi.org/10.1115/ICONE29-92380
View Paper titled, Data Driven Methods for Break Size and Location Estimation in LOCA Based on Deep Learning
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Topics: Accidents, Algorithms, Artificial neural networks, China, Coolants, Design, Flow (Dynamics), Machine learning, Nuclear power stations, Nuclear reactors
Proceedings Papers

Machine Learning Modelling of Decay Heat Removal in High Temperature Gas-Cooled Reactor

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Hao Wu, Liangzhi Yu, Fenglei Niu, Jiyuan Tu, Shengyao Jiang
Proc. ASME. ICONE29, Volume 7B: Thermal-Hydraulics and Safety Analysis, V07BT07A019, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-92695
https://doi.org/10.1115/ICONE29-92695
View Paper titled, Machine Learning Modelling of Decay Heat Removal in High Temperature Gas-Cooled Reactor
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Topics: Heat, Machine learning, Modeling, Very high temperature reactors
Proceedings Papers

Study on the Applicability of a Machine-Learning Framework to Improve Modeling for the Stratification Phenomenon

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Takuo Oda, Shimpei Okayasu, Nobuhide Hara, Koichi Tanimoto, Ali Haghiri, Xiaowei Xu, Richard Sandberg
Proc. ASME. ICONE29, Volume 8: Computational Fluid Dynamics (CFD) and Applications, V008T08A026, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-91829
https://doi.org/10.1115/ICONE29-91829
View Paper titled, Study on the Applicability of a Machine-Learning Framework to Improve Modeling for the Stratification Phenomenon
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Topics: Computer programming, Machine learning, Modeling, Thermal stratification, Turbulence
Proceedings Papers

The Crown Predictive Model of Cold-Rolled Zirconium Alloy Strip Sheet Based on Machine Learning Algorithm

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Yuan Cao, Jianguo Cao, Yingqi Gao, Ben Wang, Pengfei Zhang, Fang Li, Bo Gao
Proc. ASME. ICONE29, Volume 10: Advanced Methods of Manufacturing for Nuclear Reactors and Components, V010T10A026, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-92252
https://doi.org/10.1115/ICONE29-92252
View Paper titled, The Crown Predictive Model of Cold-Rolled Zirconium Alloy Strip Sheet Based on Machine Learning Algorithm
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Topics: Algorithms, Cold rolling, Machine learning, Strips, Zirconium alloys
Proceedings Papers

Machine Learned Metamodeling of a Computationally Intensive Accident Simulation Code

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Landon Conner, Clarence L. Worrell, James P. Spring, Jun Liao
Proc. ASME. ICONE28, Volume 1: Operating Plant Challenges, Successes, and Lessons Learned; Nuclear Plant Engineering; Advanced Reactors and Fusion; Small Modular and Micro-Reactors Technologies and Applications, V001T02A035, August 4–6, 2021
Publisher: American Society of Mechanical Engineers
Paper No: ICONE28-66619
https://doi.org/10.1115/ICONE28-66619
View Paper titled, Machine Learned Metamodeling of a Computationally Intensive Accident Simulation Code
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Topics: Accidents, Machinery, Metamodeling, Simulation, Artificial neural networks, Machine learning, Manufacturing, Nuclear industry, Optimization, Safety