NUCLEAR TECHNIQUES, Volume. 48, Issue 1, 010601(2025)
Prediction of heat transfer parameters of nuclear reactor based on physical information machine learning algorithm
Fig. 5. HTC experimental data distribution of mass flux (a), pressure (b) and equilibrium quality (c)
Fig. 6. Relationship between the number of MLP hidden layer neurons and the error in the HTC model
Fig. 7. Relationship between the number of BPNN hidden layer neurons and the error in the HTC model
Fig. 8. Relationship between the number of RF decision trees and the error in the HTC model
Fig. 9. Prediction results of experimental data by six HTC models, MLP_Thom (a), MLP_JL (b), BPNN_Thom (c), BPNN_JL (d), RF_Thom (e) and RF_JL (f)
Fig. 10. Cumulative data fraction of MAPE in models associated with Thom (a) and Jens-Lottes (b)
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Dexiang KONG, Yichao MA, Jing ZHANG, Mingjun WANG, Yingwei WU, Yanan HE, Kailun GUO, Wenxi TIAN, Guanghui SU. Prediction of heat transfer parameters of nuclear reactor based on physical information machine learning algorithm[J]. NUCLEAR TECHNIQUES, 2025, 48(1): 010601
Category: NUCLEAR ENERGY SCIENCE AND ENGINEERING
Received: Jul. 12, 2024
Accepted: --
Published Online: Feb. 26, 2025
The Author Email: ZHANG Jing (章静)