DocumentCode :
3284892
Title :
Operation parameters optimization of butadiene extraction distillation based on neural network
Author :
Fengqin Chen ; Zheng, Fengqin Chen Jianguo
Author_Institution :
Glorious Sun Sch. of Bus. & Manage., Donghua Univ., Shanghai, China
fYear :
2011
fDate :
20-23 Feb. 2011
Firstpage :
1157
Lastpage :
1163
Abstract :
In this paper, based on the material balance, we used Aspen plus software to make sensitivity analysis of separation performance of the key component and the operational parameters. We quantitatively analyze the influence between the component parameters and the process. At last, we used the neural network to forecast the solvent ratio on diffident C4 feed and calculated the optimization solvent. At the end of the paper, we used the actual production data to test the validity of the model. On the view of reducing the energy consumption and ensuring the product quality, the research result told us that solvent ratio could be reduced nearly one percentage point.
Keywords :
energy consumption; neural nets; optimisation; production engineering computing; raw materials; rubber; separation; solvents (industrial); Aspen plus software; butadiene extraction distillation; energy consumption; material balance; neural network; operation parameter optimization; product quality; production data; sensitivity analysis; separation performance; solvent ratio; Distillation equipment; Feeds; Optimization; Poles and towers; Predictive models; Production; Solvents; Butadiene Extractive Distillation; Neural Network; Optimization; Reflux ratio; Solvent ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nano/Micro Engineered and Molecular Systems (NEMS), 2011 IEEE International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-61284-775-7
Type :
conf
DOI :
10.1109/NEMS.2011.6017562
Filename :
6017562
Link To Document :
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