Dynamic Optimization of Chemically Reacting Stagnation Flows

This paper presents a dynamic-optimization algorithm that can be used to minimize a generalized objective function. It is demonstrated for a chemical-vapor-deposition (CVD) process in a stagnation-flow reactor. The equations describing the chemically reacting flow are written in a transient compressible similarity form. After discretizing the spatial derivatives on a finite-volume mesh, the system becomes a set of differential-algebraic equations (DAE). The optimization algorithm is a shooting-type approach that is designed specifically to work with large nonlinear systems of DAEs. The algorithm is demonstrated using an example from the CVD growth of a thin-film YBCO high-temperature superconductor.