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Guangying Chen
Researcher at Hunan University
Publications - 15
Citations - 524
Guangying Chen is an academic researcher from Hunan University. The author has contributed to research in topics: Chemistry & Mass transfer. The author has an hindex of 9, co-authored 12 publications receiving 365 citations.
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Journal ArticleDOI
The genetic algorithm based back propagation neural network for MMP prediction in CO2-EOR process
Guangying Chen,Kaiyun Fu,Zhiwu Liang,Teerawat Sema,Chen Li,Paitoon Tontiwachwuthikul,Paitoon Tontiwachwuthikul,Raphael Idem,Raphael Idem +8 more
TL;DR: In this paper, a genetic algorithm based back propagation artificial neural network model was developed and used to predict the minimum miscibility pressure, ie MMP, for both pure and impure CO2 injection cases.
Journal ArticleDOI
Experimental study on mass transfer and prediction using artificial neural network for CO2 absorption into aqueous DETA
Kaiyun Fu,Guangying Chen,Teerawat Sema,Xu Zhang,Zhiwu Liang,Raphael Idem,Raphael Idem,Paitoon Tontiwachwuthikul,Paitoon Tontiwachwuthikul +8 more
TL;DR: In this article, the volumetric overall mass transfer coefficient (KGav) for carbon dioxide (CO2) absorption into aqueous diethylenetriamine (DETA) was experimentally determined in an absorption column packed with Sulzer DX-type structured packing over a temperature range of 30-50°C and at atmosphere pressure.
Journal ArticleDOI
Artificial neural network models for the prediction of CO2 solubility in aqueous amine solutions
Guangying Chen,Xiao Luo,Haiyan Zhang,Kaiyun Fu,Zhiwu Liang,Wichitpan Rongwong,Paitoon Tontiwachwuthikul,Raphael Idem +7 more
TL;DR: In this article, back-propagation neural networks (BPNN) and radial basis function neural network (RBFNN) were proposed to predict the CO 2 solubility in 12 known amine solutions.
Journal ArticleDOI
Analysis of Mass Transfer Performance of Monoethanolamine-Based CO2 Absorption in a Packed Column Using Artificial Neural Networks
Kaiyun Fu,Guangying Chen,Zhiwu Liang,Teerawat Sema,Raphael Idem,Raphael Idem,Paitoon Tontiwachwuthikul,Paitoon Tontiwachwuthikul +7 more
TL;DR: In this paper, two types of artificial neural networks (ANNs) were applied to predict the mass-transfer performance of CO2 absorption into aqueous monoethanolamine (MEA) in packed columns (containing Berl saddles, Pall rings, IMTP random packing, and 4A Gempack, Sulzer DX structured packing, respectively) from input variables.
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Understanding the potential benefits of blended ternary amine systems for CO2 capture processes through 13C NMR speciation study and energy cost analysis
TL;DR: Aqueous blends of the three amines 2-aminoethanol (MEA), N-methyldiethanolamine (MDEA), and 2amino-2-methyl-1-propanol (AMP) were tested as sorbents for CO2 capture processes as discussed by the authors .