The goal of this project is to develop a globally optimum design methodology for the synthesis of process networks. The task will be pursued within the "Infinite DimEnsionAl State space" (IDEAS) framework that the PI has been working on in recent years. The main advantage of the IDEAS approach is that it yields optimization formulations with convex (linear) feasible regions.
Within the IDEAS framework, the synthesis of the overall network is decomposed into the synthesis of an operator network (OP), where process technologies (unit operations) and/or their aggregate effects are represented, and a distribution network (DN), where mixing, splitting, recycling, and bypassing occur. The key development behind IDEAS is the use of a process operator whose domain and range lie in infinite (rather than finite) dimensional space. This process representation allows both consideration of all possible process networks for an a priori given set of technologies, and gives rise to a convex (linear) feasible region. Consequently, when the objective function is convex, all locally optimal solutions of the resulting process network synthesis problems are guaranteed to be globally optimal. Large classes of commonly employed objectives (such as utility cost, volume, area, yield, selectivity, etc.) give rise to linear objective functions and thus infinite linear program IDEAS formulations.
In particular, research is planned in the following areas:
IDEAS approach to synthesis of process networks with MTAC properties Parallel computing implementation of the IDEAS framework IDEAS approach to reactor network synthesis IDEAS approach to reactor/separator network synthesis.
Broad Impact
The IDEAS framework is not limited to chemical engineering processes. Applications from other engineering disciplines are well suited for the IDEAS framework. Examples of such disciplines include, but are not limited to, water resource engineering, pollution prevention and structural engineering. Additionally, mathematical developments in numerical approximation of infinite dimensional linear programs and parallelized solution of large-scale linear programs will be beneficial to operations research.
The knowledge accrued from the project will also be disseminated to and help train undergraduate students, since it will generate software and concepts that will be used in capstone undergraduate design courses. The PI will pursue the development and introduction of an IDEAS based software package for the systematic construction of attainable regions to an undergraduate and graduate course in pollution prevention. The software package will also be made available to other undergraduate and graduate courses.
