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Machine Learning Representations For Optimization Of Process Systems, Logan Watts

Chemical Engineering Undergraduate Honors Theses

The optimal operation of chemical processes provides the foundation for optimization problems to determine the most effective way to operate or design a given process. Chemical processes can be represented as nonlinear systems of equations with decision variables, resulting in a problem that can be solved through nonlinear solvers. The downfalls of nonlinear solvers create the need for improved methods of finding globally optimal solutions to the design or operation of a chemical process. The project will seek to evaluate the use of artificial neural networks to approximate nonlinear systems of equations for the purpose of optimizing chemical processes. The …