Abrol, S., Lu, M., Hill, D., Herrick, A., and Edgar, T. F. (2010). Faster dynamic process simulation using in situ adaptive tabulation. Industrial and Engineering Chemistry Research, 49(17), 7814–7823.

Adomian, G. (1984). Convergent series solution of nonlinear equations. Journal of Computational and Applied Mathematics, 11(2), 225–230.

Adomian, G. (1986). A New Approach to the Heat Equation - An Application of the Decomposition Method. Journal of Mathematical Analysis and Applications, 113, 202–209.

Adomian, G. (1988). A review of the decomposition method in applied mathematics. Journal of Mathematical Analysis and Applications, 135(2), 501–544.

Adomian, G. (1991). A review of the decomposition method and some recent results for nonlinear equations. Computers and Mathematics with Applications, 21(5), 101–127.

Arabia, S. (2015). Some Modifications of Adomian Decomposition Methods for Nonlinear Partial Differential Equations. Ijrras, 23(May), 164–173.

Cao, Y., Swartz, C. L. E., Flores-Cerrillo, J., and Ma, J. (2016). Dynamic modeling and collocation-based model reduction of cryogenic air separation units. AIChE Journal, 62(5), 1602–1615.

Dones, I., and Preisig, H. A. (2010). Model simplification and time-scale assumptions applied to distillation modelling. Computers and Chemical Engineering, 34(5), 732–743.

Elsaid, A. (2012). Adomian Polynomials: a Powerful Tool for Iterative Methods of Series Solution of Nonlinear Equations. 2(4), 381–394.

Fatoorehchi, H., and Abolghasemi, H. (2014). Approximating the minimum reflux ratio of multicomponent distillation columns based on the Adomian decomposition method. Journal of the Taiwan Institute of Chemical Engineers, 45(3), 880–886.

Fatoorehchi, H., Abolghasemi, H., and Rach, R. (2015). A new parametric algorithm for isothermal flash calculations by the Adomian decomposition of Michaelis-Menten type nonlinearities. Fluid Phase Equilibria, 395, 44–50.

Fernandes, P. R. B., and Trierweiler, J. O. (2009). Local thermodynamic models networks for dynamic process simulation. Industrial and Engineering Chemistry Research, 48(18), 8529–8541.

Fu, Y., and Liu, X. (2017). An advanced control of heat integrated air separation column based on simplified wave model. Journal of Process Control, 49, 45–55.

Hankins, N. P. (2007). A Non-Linear Wave Model with Variable Molar Flows for Dynamic Behaviour and Disturbance Propagation in Distillation Columns. Chemical Engineering Research and Design, 85(1 A), 65–73.

Hwang, Y. L. (1995). Wave Propagation in Mass-Transfer Processes: From Chromatography to Distillation. Industrial and Engineering Chemistry Research, 34(8), 2849–2864.

Ito, E. H. C., Secchi, A. R., Gomes, M. V. C., and Paiva, C. R. (2018). Development of a gas composition soft sensor for distillation columns: A simplified model based and robust approach. In M. R. Eden, M. G. 

Ierapetritou, & G. P. B. T.-C. A. C. E. Towler (Eds.), 13 International Symposium on Process Systems Engineering (PSE 2018) (Vol. 44, pp. 661–666). Elsevier.

Kamath, R. S., Grossmann, I. E., and Biegler, L. T. (2010). Aggregate models based on improved group methods for simulation and optimization of distillation systems. Computers and Chemical Engineering, 34(8), 1312–1319.

Kumar, M., and Singh, N. (2010). Modified Adomian Decomposition Method and computer implementation for solving singular boundary value problems arising in various physical problems. Computers and Chemical Engineering, 34(11), 1750–1760.

Ledent, T., and Heyen, G. (1994). Dynamic approximation of thermodynamic properties by means of local models. Computers & Chemical Engineering, 18(Suppl.), S87–S91.

Linhart, A., and Skogestad, S. (2009). Computational performance of aggregated distillation models. Computers & Chemical Engineering, 33(1), 296–308.

Linhart, A., and Skogestad, S. (2010). Reduced distillation models via stage aggregation. Chemical Engineering Science, 65(11), 3439–3456.

Nentwich, C., and Engell, S. (2016). Application of surrogate models for the optimization and design of chemical processes. 2016 International Joint Conference on Neural Networks (IJCNN), 1291–1296.

Schδfer, P., Caspari, A., Kleinhans, K., Mhamdi, A., and Mitsos, A. (2019). Reduced dynamic modeling approach for rectification columns based on compartmentalization and artificial neural networks. AIChE Journal, 65(5), e16568.

Valleriote, A., Dorigo, L., Secchi, A. R., and Biscaia, E. C. (2012). Reduced Rigorous Models for Efficient Dynamic Simulation and Optimization of Distillation Columns. In I. D. L. Bogle & M. B. T.-C. A. C. E. Fairweather (Eds.), 22 European Symposium on Computer Aided Process Engineering (Vol. 30, pp. 1262–1266). Elsevier.

Younker, J. M. (2011). Numerical integration of the chemical rate equations via a discretized adomian decomposition. Industrial and Engineering Chemistry Research, 50(6), 3100–3109.