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Predictions of wave height and pressure induced by liquid sloshing based on neural network
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Xin JIN1, Yu-sheng WANG1, Fu-gui ZHANG1, Jian CHEN2, Deng-song LI3, Chang-yuan FAN1, Ming-ming LIU4
Journal of Ship Mechanics | 2025, 29(3) : 388 - 399
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Journal of Ship Mechanics | 2025, 29(3): 388-399
• Hydrodynamics •
Predictions of wave height and pressure induced by liquid sloshing based on neural network
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Xin JIN1, Yu-sheng WANG1, Fu-gui ZHANG1, Jian CHEN2, Deng-song LI3, Chang-yuan FAN1, Ming-ming LIU4
Affiliations
  • 1.College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
  • 2.PowerChina Hebei Electric Power Engineering Co., Ltd., Shijiazhuang 050031, China
  • 3.School of Automation, Chengdu University of Information Technology, Chengdu 610225, China
  • 4.School of Architecture and Engineering, Liaocheng University, Liaocheng 252000, China
Published: 2025-03-20 doi: 10.3969/j.issn.1007-7294.2025.03.005
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Numerical modelling based on Navier-Stokes equations and model experiment for studying liquid sloshing have the limits of low computational efficiency and high economic cost. Therefore, to predict the hydrodynamic pressure and wave height, the time-histories to numerical and experimental results were reconstructed in this paper through the neural network model. The total numerical and experimental pressures and free surface elevations were taken as training samples, and CNN, RNN and LSTM with strong repretational ability were used to reproduce the sloshing responses. The internal structural parameters of the neural network were systematically adjusted, besides, the errors and correlations between the predicted and actual values were analyzed. The results show that the error is lower than 4% and the correlations of both RNN and LSTM reach 0.88, which is in general superior to CNN, and that LSTM is optimal in predicting the long sequence data. Overall, three surrogate models can well predict the sloshing wave height and pressure, and are promising in the study of liquid sloshing.

liquid sloshing  /  neural network  /  numerical simulation  /  prediction
Xin JIN, Yu-sheng WANG, Fu-gui ZHANG, Jian CHEN, Deng-song LI, Chang-yuan FAN, Ming-ming LIU. Predictions of wave height and pressure induced by liquid sloshing based on neural network[J]. Journal of Ship Mechanics, 2025 , 29 (3) : 388 -399 . DOI: 10.3969/j.issn.1007-7294.2025.03.005
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Year 2025 volume 29 Issue 3
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doi: 10.3969/j.issn.1007-7294.2025.03.005
  • Receive Date：2024-09-25
  • Online Date：2026-03-24
  • Published：2025-03-20
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  • Received：2024-09-25
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Affiliations
    1.College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
    2.PowerChina Hebei Electric Power Engineering Co., Ltd., Shijiazhuang 050031, China
    3.School of Automation, Chengdu University of Information Technology, Chengdu 610225, China
    4.School of Architecture and Engineering, Liaocheng University, Liaocheng 252000, China
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https://castjournals.cast.org.cn/joweb/cblx/EN/10.3969/j.issn.1007-7294.2025.03.005
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