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Keywords: neural network
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Proceedings Papers

Proc. ASME. ICONE31, Volume 1: Nuclear Plant Operation and Maintenance, Engineering and Modification, Operation Life Extension (OLE), and Life Cycle, V001T01A039, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-135988
...Proceedings of the 2024 31st International Conference on Nuclear Engineering ICONE31 August 4-8, 2024, Prague, Czech Republic ICONE31-135988 A CONTROL-ORIENTED HYBRID MODEL FOR NUCLEAR REACTORS BASED ON NEURAL NETWORK Ze Zhu Xi'an Jiaotong University Shaanxi, Xi an, China Pengfei Wang Xi'an...
Proceedings Papers

Proc. ASME. ICONE31, Volume 3: I&C, Digital Control, and Influence of Human Factors, V003T03A010, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-134913
... process, the fault diagnosis is usually carried out by operators by observing the parameters during operation and combining their own knowledge. The advantage of using neural networks for fault diagnosis lies in their direct and effective statistical analysis and information extraction of massive, multi...
Proceedings Papers

Proc. ASME. ICONE31, Volume 5: Nuclear Safety, Security, and Cyber Security; Nuclear Codes, Standards, Licensing, and Regulatory Issues, V005T05A018, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-134965
... 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...
Proceedings Papers

Proc. ASME. ICONE31, Volume 8: Decontamination and Decommissioning, Radiation Protection, and Waste Management, V008T09A018, August 4–8, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ICONE31-135796
... million cases are generated using the neural network-based surrogate model, drastically reducing computational time (~1.9 seconds) compared to traditional methods (~78.4 days). The model evaluates the deterioration mechanisms of various materials like iron, aluminum, zinc, and brass, in cementitious waste...
Proceedings Papers

Proc. ASME. ICONE29, Volume 3: I&C, Digital Control, and Influence of Human Factors, V003T03A005, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-89440
... software error severity, and so on. The rapidly developed neural network technology provides a new kind of research tool to analyze these recorded data. This paper uses software error data to train a Recurrent Neural Network (RNN), the trained RNN can give more correct software reliability growth...
Proceedings Papers

Proc. ASME. ICONE29, Volume 4: SMRs, Advanced Reactors, and Fusion, V004T04A005, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-90511
...Proceedings of the 2022 29th International Conference on Nuclear Engineering ICONE29 August 8-12, 2022, Virtual, Online ICONE29-90511 OPTIMIZATION OF CORE PARAMETERS BASED ON ARTIFICIAL NEURAL NETWORK SURROGATE MODEL Shu Chen1, Peng Ding1, Shuowen Hu1, Wenqing Xia1, Min Liu1, Fengwan Yu1, Wenhuai...
Proceedings Papers

Proc. ASME. ICONE29, Volume 15: Student Paper Competition, V015T16A063, August 8–12, 2022
Publisher: American Society of Mechanical Engineers
Paper No: ICONE29-91880
.... In actual operation, it is difficult for classical PID control to ensure a satisfactory control performance. In this paper, the neural network methods are used to optimize the parameters of the PID controller, and a neural network controller is designed. The controller of the system consists of two...
Proceedings Papers

Proc. ASME. ICONE2020, Volume 1: Beyond Design Basis; Codes and Standards; Computational Fluid Dynamics (CFD); Decontamination and Decommissioning; Nuclear Fuel and Engineering; Nuclear Plant Engineering, V001T06A005, August 4–5, 2020
Publisher: American Society of Mechanical Engineers
Paper No: ICONE2020-16138
... diagnosis based on BP-NN is higher than RBF-NN; fuzzy-NN for fault diagnosis is faster than NN. nuclear safety reactor coolant system fault diagnosis neural network fuzzy system RESEARCH ON FAULT DIAGNOSIS OF REACTOR COOLANT ACCIDENT IN NUCLEAR POWER PLANT BASED ON RADIAL BASIS FUNCTION...
Proceedings Papers

Proc. ASME. ICONE2020, Volume 3: Student Paper Competition; Thermal-Hydraulics; Verification and Validation, V003T12A050, August 4–5, 2020
Publisher: American Society of Mechanical Engineers
Paper No: ICONE2020-16900
.... The structure of the network packets is analyzed in detail with examples. Then, Features are extracted from network packets. An unsupervised neural network called autoencoder is applied for anomaly detection. Training and testing database are captured from a physical PLC system which simulates a water level...
Proceedings Papers

Proc. ASME. ICONE10, 10th International Conference on Nuclear Engineering, Volume 3, 71-78, April 14–18, 2002
Publisher: American Society of Mechanical Engineers
Paper No: ICONE10-22088
... for an adiabatic vertical co- rent downward air-water two-phase flow in the 25.4 mm ID the 50.8 mm ID round tubes was performed by employing impedance void meter coupled with the neural network ssification approach. This approach minimizes the jective judgment in determining the flow regimes. The nals obtained...