Research Article Carbon Dioxide Absorption Modeling for Off-Gas Treatment in the Nuclear Fuel Cycle Jorge Gabitto 1 and Costas Tsouris 2 1 Department of Chemical Engineering, Prairie View A&M University, Prairie View, TX 77446, USA 2 Oak Ridge National Laboratory, Oak Ridge, TN 37831-6181, USA Correspondence should be addressed to Jorge Gabitto; jfgabitto@pvamu.edu Received 27 February 2018; Revised 2 August 2018; Accepted 8 August 2018; Published 10 October 2018 Academic Editor: Iftekhar A. Karimi Copyright © 2018 Jorge Gabitto and Costas Tsouris. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e absorption of carbon dioxide is an important process in many practical applications such as reduction of greenhouse gases, separation and purification processes in the chemical and petroleum industries, and capture of radioactive isotopes in the nuclear fuel cycle e goal of this research is to develop a dynamic model to simulate CO 2 absorption by using different alkanolamines as absorption solvents. e model is based upon transient mass and energy balances for the chemical species commonly present in CO 2 gas-liquid absorption. A computer code has been written to implement the proposed model. Simulation results are discussed. e reported model simulates well the response to dynamic changes in input conditions. e proposed model can be used to optimize and control the separation of carbon-14 in the form of CO 2 in the nuclear industry. 1. Theoretical Considerations 1.1. Introduction. e off-gas stream produced from re- processing used nuclear fuel containing a host of radioactive gases including tritium, iodine, methyl iodide, krypton, xenon, and carbon dioxide. ese gases are hazardous to human health, and some are of considerable economic value. Currently, there is interest in the efficient capture of these gases for recovery or storage purposes [1]. Presently, postcombustion separation of carbon dioxide from flue-gas streams is investigated using membrane sep- aration, low-temperature distillation, physical adsorption by activated carbon and zeolites, chemical absorption by mineral oxides to produce the corresponding carbonates, and chemical absorption by suitable solvents [2]. Chemical ab- sorption by solvents is the most common form of the CO 2 capture process. Amines, and mixtures containing amines, are the most used solvents as these compounds react quickly with CO 2 , maintaining high mass transfer-driving forces [2]. In- dustrially important amines are monoethanolamine (MEA), diethanolamine (DEA), diisopropanolamine (DIPA), and the tertiary amine N-methyldiethanolamine (MDEA). Most industrial processes are operated with aqueous amine solu- tions, but solvents consisting of a mixture of water and a nonaqueous solvent, for example, sulfolane in the Shell- Sulfinol process [3], are also frequently used [4]. Blending of different amines is considered to be attractive because in this way the high absorption capacity of tertiary amines can be combined with the high absorption rates of primary or secondary amines [5]. Blends are also more flexible than singular amines because the relative concentration of the amines can be varied [6]. Other combinations have been considered, such as MEA and 2-amino-2-methyl-1-propanol (AMP). e latter amine is an attractive alternative since it offers higher absorption capacity and lower regeneration energy. Blending MEA with AMP is considered to combine all favorable characteristics of both amines and overcome the unfavorable characteristics [7]. Some studies have been car- ried out considering the influence of the solvent mixed with the alkanolamines. For example, Usubharatana and Tonti- wachwuthikul [8] studied the kinetics of CO 2 capture using methanol mixed into solutions of MEA. e goal of this work is to develop a theoretical model for dynamic simulations of CO 2 absorption using a generic Hindawi International Journal of Chemical Engineering Volume 2018, Article ID 3158147, 11 pages https://doi.org/10.1155/2018/3158147