REDUCED-ORDER DYNAMIC MODELS FOR SEPARATION PROCESSES

One of the major difficulties with the mathematical models of staged countercurrent separation systems is the large dimensionality of the process model. This thesis is concerned with reduced-order steady state and dynamic models for processes such as distillation, absorption and extraction. The model reduction procedure is based on approximating the composition and flow profiles in the column using polynomials. The method of orthogonal collocation is used to develop the equations describing the separation column. The number of equations required to describe the system is thus drastically reduced. The method is extended to accommodate multifeed separation systems. An index called ORP (Order Reduction Parameter) is developed to predict a-priori, the extent of order reduction achievable and to provide guidelines for choosing the reduced-order model of the appropriate size for a column. The reduction procedure is modified to account for the highly nonlinear composition profiles of the nonkey components in a multicomponent separation system.; The method is applied to the modeling and simulation of staged separation systems ranging from binary absorbers to complete distillation columns. The accuracy of the approximation is established by comparison of the steady state profiles and transient responses to that of rigorous stage-by-stage dynamic models.