Experimental and modeling of CO2 capture by dry sodium hydroxide carbonation

被引:34
|
作者
Kianpour, Mohsen [1 ]
Sobati, Mohammad Amin [1 ]
Shahhosseini, Shahrokh [1 ]
机构
[1] IUST, Sch Chem Engn, Tehran, Iran
来源
关键词
CO2; capture; Sodium hydroxide; Neural network; Adsorption; ARTIFICIAL NEURAL-NETWORKS; DIOXIDE CAPTURE; PRODUCT LAYER; FLUE-GAS; SEPARATION; ADSORPTION; RECOVERY; SORBENTS; KINETICS; PROGRESS;
D O I
10.1016/j.cherd.2012.04.005
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In this work, CO2 capture from the air using dry NaOH sorbents has been studied. The influences of the main operating parameters such as temperature, air humidity, and NaOH loading on the CO2 removal rate have been experimentally investigated using Taguchi method. The results revealed that the appropriate value of the temperature to maximize the rate was in the range of 35-45 degrees C. A multilayer artificial neural network (ANN) was also used to model the process in order to find the optimal conditions. A procedure reported in the literature was modified and applied to design the ANN model. The model predictions were validated by conducting some more experiments. The experimental results proved the accuracy of the model to predict the optimal conditions. The effects of NaOH particle size and multiple carbonation cycles have also been investigated. (C) 2012 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:2041 / 2050
页数:10
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