Property Based Process and Product Synthesis and Design

This thesis describes the development of a general framework for solving process and product design problems. Targeting the desired performance of the system in a systematic manner relieves the iterative nature of conventional design techniques. Furthermore, conventional component based methods are not capable of handling problems, where the process or product objectives are driven by functionalities or properties rather than chemical constituency. The framework is meant to complement existing composition based methods by being able to handle property driven problems. By investigating the different roles a property model plays at different stages of the solution to a design problem, it is discovered that by decoupling the constitutive equations, that make up the property model, from the balance and constraint equations of the process or product model, a significant reduction in problem complexity is achieved including an added flexibility compared to existing solution methods. The decoupling of the constitutive equations allows for reformulating a conventional forward problem into two reverse problems. The first reverse problem is the reverse of a simulation problem, where the process model is solved in terms of the constitutive (synthesis/design) variables instead of the process variables, thus providing the synthesis/design targets. The second reverse problem (reverse property prediction) solves the constitutive equations to identify unit operations, operating conditions and/or products by matching the synthesis/design targets. The reverse problem formulation technique extends the application range of the numerical solvers as well as the models themselves, thus it is possible to identify alternative designs that conventional methods are not capable of finding. A novel way of representing the constitutive variables is presented in this thesis. The framework is based on tracking functionalities or properties of the process streams rather than the chemical constituency. The motivation for developing this framework comes from a number of cases where conventional composition based methods fail to adequately solve the design problems. The methodology for tracking stream functionalities or properties is referred to as property clustering. The clusters are derived to obey the principles of intra- and interstream conservation, which allow for the development of consistent additive rules along with their ternary representation, thereby facilitating visualization on triangular diagrams. An important feature of the clustering technique is the ability to reduce a high dimensional problem into a two or three dimensional space allowing for visualization of the problem. The developed framework provides a systematic methodology for solving process and product design problems. The reverse problem formulation techniques allow for easier identification of optimal solutions and the property clustering techniques enable the systematic solution of problems that are driven by physical properties rather than components. It should be emphasized that the work presented here introduces the general framework of reverse problem formulation, where the links between the two formulated reverse problems are the constitutive variables. One representation of such variables is the property clustering methodology presented here, but the general framework is applicable to any representation of the properties.