International Journal of Greenhouse Gas Control 49 (2016) 24–33 Contents lists available at ScienceDirect International Journal of Greenhouse Gas Control j ourna l ho me page: www.elsevier.com/locate/ijggc Modeling and optimization of CO 2 capture using 4-diethylamino-2-butanol (DEAB) solution Morteza Afkhamipour, Masoud Mofarahi ∗ Department of Chemical Engineering, Faculty of Oil, Gas and Petrochemical Engineering, Persian Gulf University, P.O. Box 75169-13798, Bushehr, Iran a r t i c l e i n f o Article history: Received 1 September 2015 Received in revised form 11 February 2016 Accepted 12 February 2016 Keywords: Packed column MLPNN model Taguchi method DEAB CO2 removal efficiency a b s t r a c t A multi-layer perceptron neural network (MLPNN) model with Levenberg–Marquardt learning algo- rithm were applied to model CO 2 capture by a novel amine solution called 4-diethylamino-2-butanol (DEAB). The MLPNN model predicted the CO 2 concentration and temperature profiles along the height of the packed column as the model output. Inlet feed conditions of the absorber column (flue gas and amine) were selected as the inputs of the MLPNN model. Experimental data about random and structured packed columns were extracted from the literature and used to train the MLPNN model. In addition, a systematic procedure, i.e. Taguchi method, was applied to obtain the significant sequence of process parameters affecting CO 2 removal efficiency and to optimize the variables in the absorber column. Five levels of five variables, including lean amine temperature, amine concentration, CO 2 loading of amine, gas temperature, and amine flow rate, were used for the optimization of the absorber column. The average absolute relative deviations (AARD) between the predicted results and the experimental data suggested that our MLPNN model could predict CO 2 concentration and temperature profiles along the packed column (AARD% = 5.47 and 3.61, respectively). The signal to noise ratio analysis of the Taguchi method yielded a significant sequence of factors affecting CO 2 removal efficiency in the packed column (CO 2 loading > amine flow rate > amine concentration > gas temperature > amine temperature). This study demonstrated the acceptable accuracy of the MLPNN and Taguchi method in, respectively, the modeling and optimization of CO 2 capture in amine solutions. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction 1.1. Background CO 2 separation technologies, including membrane separation, low temperature distillation, adsorption, physical absorption, and chemical absorption, play a crucial role in preventing both global warming and global climate change. While the CO 2 capture pro- cess using amine solutions is a promising technology in this field (Mofarahi et al., 2008), choosing the appropriate amine solvent is essential to ensure such benefits as fast reaction, high mass transfer rate and capacity, and low energy requirements for regen- eration, degradation rate, tendency to foam, and corrosiveness (Kohl and Nielsen, 1997; Sema et al., 2013a,b,c). Of all amines, alka- nolamines, e.g. monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA), have been widely used in the CO 2 capture process (Kohl and Nielsen, 1997). Although both MEA ∗ Corresponding author. E-mail address: mofarahi@pgu.ac.ir (M. Mofarahi). (primary amine) and DEA (secondary amine) have high reaction rates with CO 2 , their application in the CO 2 capture process is associated with a number of drawbacks including low absorp- tion capacity, high-energy requirements for regeneration, and high corrosion rate (Kohl and Nielsen, 1997; Mofarahi et al., 2008; Fu et al., 2012). MDEA, on the other hand, is a tertiary amine with high absorption capacity, low-energy requirements for regenera- tion, and low circulation rate for CO 2 absorption. However, its low reaction rate with CO 2 not only necessitates higher pressure, but also increases the height of the packed absorber column (Mofarahi et al., 2008; Fu et al., 2012). According to the report of International Test Center (ITC) for CO 2 Capture (Tontiwachwuthikul et al., 2008), replacing conventional amines with nine innovative amine solu- tions containing an amino alcohol group can improve CO 2 capture efficiency by increasing CO 2 absorption and cyclic capacity. Among these amines, 4-diethylamino-2-butanol (DEAB) and diethylenetri- amine (DETA) have been shown to have the potential to enhance the efficiency of the CO 2 capture process (Maneeintr et al., 2008; Sema et al., 2011, 2012, 2013a,b,c; Naami et al., 2012; Hartono and Svendsen, 2009; Fu et al., 2012, 2013). Previous studies have mainly focused on two different mathematical models, i.e. rate-based and http://dx.doi.org/10.1016/j.ijggc.2016.02.019 1750-5836/© 2016 Elsevier Ltd. All rights reserved.