Numerous research efforts have been reported in published literature that propose the design of solvents as part of the broader flowsheet process design. Capturing the synergies and interactions between the designed solvents and the processes in which they are utilized leads to process-solvent schemes of optimum economic performance. Existing design methods focus on optimizing process design characteristics such as process structure and size, topology of recycle streams and solvent feed flowrates, to name a few. Subsequently, the performed optimization is combined with a method for the generation of solvent design alternatives hence the effects of various solvent options in the economic design of the particular process addressed are fully explored. However, processes are essentially dynamic environments susceptible to variations in operating parameters and influence from exogenous disturbances. For example, a solvent-process scheme designed for optimality under the assumption of certain purity levels in the process feed streams or constant process pressure, will not necessarily be optimal if any of those parameters vary during the process operation, as is often the case in industrial practice. Available approaches aiming to design solvent-process schemes of optimum performance often overlook the effects of such variations as is generally assumed that a properly designed control system will eventually compensate for such effects. While a number of methods have been developed to address process design optimality under operating parameter variations, the effects of using alternative solvent options in process design under operating variability that explicitly considers the controllability properties of the overall design have yet to be addressed systematically.

In this work, we address the economic and static controllability behavior of different solvent candidates introduced into a framework that enables optimal process design while considering variations in process parameters and disturbances in process operation. The employed process design framework consists of a design and a nonlinear sensitivity analysis stage. The separation process design stage is facilitated by use of orthogonal collocation on finite elements (OCFE) techniques for stagewise separation units that allows the reduction of the model size while maintaining a rigorous mathematical representation of the occurring phenomena. The nonlinear sensitivity analysis stage investigates the steady-state effects of process parameters and conditions in the optimal operating point that is imposed by an underlined control scheme. The imposed control scheme categorizes control objectives and preferences in the usage of manipulated variables in a multivariable centralized fashion (Seferlis and Grievink, 2001). As a result, a sensitivity matrix around optimal operating points is developed that reflects the variability of process variables in response to changes in process parameters. It is within this framework that a number of alternative solvents with varying chemical structure and physical properties are introduced in order to study their effects in optimal design under operating parameter variations. The solvents are selected and introduced into process design as discrete options drawn from a solvent set designed for optimality using a multi-objective optimization computer aided molecular design method, based on a previously developed approach by Papadopoulos and Linke (2005). In this respect, each solvent constitutes an additional design parameter in the formulated optimization problem, demonstrating alternating process design directions under the imposed operating parameter variations. The performed sensitivity analysis generates useful insights regarding the imposed control framework and the range of parameter variations within which the solvents demonstrate optimum performance. Furthermore, it allows the adaptive modification of the process design characteristics, inclusive of the available solvent options, in order to enhance the process behavior under the influence of operating variations. The proposed approach is demonstrated through case studies in separation through extractive distillation of a number of mixtures. The focus is maintained in assessing the effects of different solvents in process design and steady-state controllability properties under operating variability, while the impact of this variability at the solvent design stage is beyond the scope of this work.

References cited

Papadopoulos, A.I., Linke, P. (2005). Multi-objective molecular design for integrated process-solvent systems synthesis. AICHE J., 52(3), 1057

Seferlis, P., Grievink, J., (2001). Process Design and Control Structure Screening Based on Economic and Static Controllability Criteria, Comput. Chem. Eng., 25, 177.