I-Corps: Robust Equation-oriented Chemical Process Optimizer

University Of Texas At Austin, Austin TX

Investigators

Abstract

This I-Corps project focuses on applying rigorous optimization tools to solve process design optimization problems. For example, the broader impact/commercial potential of this I-Corps project can be associated with giving chemical process designers access to modern optimization techniques. While critical to all chemical companies, optimizing the design of a chemical process (in terms of choosing the process temperatures, pressures, flow rates, etc., that give the best economic performance) is still largely carried out empirically by design engineers. The workflow is typically iterative, labor-intensive and time-consuming, and the optimality of the outcome is not guaranteed. The proposed activity will place at the fingertips of engineers in the chemical, petrochemical, natural gas and other process industries a new computational framework that uses rigorous optimization tools to find the best process design. The commercial potential ranges from increasing the number of process alternatives that can be considered at the design stage, to supporting optimal investment decisions in new production facilities or upgrading existing ones. The proposed activity also has important potential societal impact: investment in US-based chemical production facilities (spurred by recent developments in accessing domestic shale gas and oil resources) will create new jobs and advance the training and development of the current and future workforce engaged in the design and operation of chemical plants. Applying rigorous optimization tools to solve process design optimization problems has been hindered by numerical challenges posed by solving the process model - a set of very nonlinear equations corresponding to material and energy balances for reactors, distillation towers, heat exchangers, etc. found in a chemical and other process plant. The project relies on a recently-invented computational approach for solving and optimizing process flowsheet models. The approach involves a systematic mathematical reformulation of the model equations, resulting in equivalent expressions that can be solved reliably using common numerical methods. A library of unit operation models which can be linked together to create a mathematical model of an entire process is also available, and has been extensively validated on the design optimization of academic and industrial test problems. The commercialization of this work will bridge the large gap that currently exists between industrial practice and the numerous recent advances in optimization theory.