A unified modeling framework for the optimal design and dynamic simulation of staged reactive separation processes

A unified modeling approach that combines the rigorous non-equilibrium (NEQ) rate-based balance equations with the model-order reduction properties of orthogonal collocation on finite elements (OCFE) approximation techniques is employed for the optimal design, operation optimization and dynamic simulation of complex staged reactive separation processes. The NEQ/OCFE process model formulation involves the rigorous description of mass and heat transfer phenomena, phase equilibrium relations and chemical reactions in both gas and liquid phases in a limited but sufficient for an accurate representation of the column behavior, number of collocation points. In addition, polynomial approximation as implemented in the OCFE techniques, transforms the staged column domain into a continuous analog. Hence, a significant degree of modeling detail is maintained, while a more compact model formulation than the equivalent full-order (tray-by-tray) model is used. The NEQ/OCFE modeling framework has been proved particularly efficient in the optimal design of reactive absorption and distillation columns especially those with multiple side feed and product streams mainly due to the elimination of binary decision variables associated with the existence of column stages in any given column section. Furthermore, the compact model size and the demonstrated ability of the OCFE approximation to accurately identify the optimal solution and reveal the dynamic characteristics of complex reactive separation columns make the proposed modeling framework particularly attractive for real-time optimization and control applications. Distinctive process examples such as the reactive absorption of nitrogen oxides (NO,) from a gas stream by a weak HNO3 aqueous solution in the industrial production of nitric acid, as well as the production of ethyl acetate by reactive distillation clearly demonstrate the merits and strengths of the NEQ/OCFE modeling framework. (c) 2006 Elsevier Ltd. All rights reserved.