| 基于人工神经网络的滴流床脉冲流频率的预测 |
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| 引用本文： | 刘国柱, ,米镇涛. 基于人工神经网络的滴流床脉冲流频率的预测[J]. 中国化学工程学报, 2004, 12(4): 582-585 |
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| 作者姓名： | 刘国柱 米镇涛 |
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| 作者单位： | SchoolofChemicalEngineeringandTechnology,TianjinUniversity,Tianjin300072,China |
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| 基金项目： | 国家重点基础研究发展计划(973计划)，the SINOPEC |
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| 摘 要： | An extensive database (946 measurements) for the frequency of pulsing flow in trickle beds was established by collecting the experimental results published over past 30 years. A new correlation based on artificial neural network (ANN) to predict the pulsation frequency was developed. Seven dimensionless numbers (groups) employed in the proposed correlation were liquid and gas Reynolds, liquid Weber, liquid Eǒtvǒs, gas Froude, and gas Stokes numbers and a bed correction factor. The comparisons of performance reported in the of literature and present correlations show that ANN correlation is a significant improvement in predicting pulsation frequency with an average absolute relative error (AARE) of 10% and a standard deviation less than 18%.
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| 关 键 词： | 震动频率 脉冲调制流程 滴流床 神经网络系统 反应器 |
| 修稿时间： | |
Prediction of Pulsation Frequency of Pulsing Flow in Trickle Beds Based on Artificial Neural Network |
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| LIU Guozhu,MI Zhentao. Prediction of Pulsation Frequency of Pulsing Flow in Trickle Beds Based on Artificial Neural Network[J]. Chinese Journal of Chemical Engineering, 2004, 12(4): 582-585 |
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| Authors: | LIU Guozhu MI Zhentao |
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| Affiliation: | School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China |
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| Abstract: | An extensive database (946 measurements) for the frequency of pulsing flow in trickle beds was established by collecting the experimental results published over past 30 years. A new correlation based on artificial neural network (ANN) to predict the pulsation frequency was developed. Seven dimensionless numbers (groups)employed in the proposed correlation were liquid and gas Reynolds, liquid Weber, liquid Eotvos, gas Froude, and gas Stokes numbers and a bed correction factor. The comparisons of performance reported in the of literature and present correlations show that ANN correlation is a significant improvement in predicting pulsation frequency with an average absolute relative error (AARE) of 10% and a standard deviation less than 18%. |
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| Keywords: | trickle bed pulsing flow pulsation frequency artificial neural network |
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