Optimal Control of the Sabatier Process in Microchannel Reactors

TL;DR

This paper develops PDE-based models and optimization techniques for microchannel reactors, specifically the Sabatier process, demonstrating how to enhance reactor performance through numerical optimization and parameter identification.

Contribution

It introduces a coupled PDE model and software for optimizing microreactor design, including parameter identification and multi-variable optimization strategies.

Findings

Models accurately fit experimental data

Optimization improves reactor yield

Software facilitates PDE-constrained optimization

Abstract

We consider the optimization of a chemical microchannel reactor by means of PDE constrained optimization techniques, using the example of the Sabatier reaction. To model the chemically reacting flow in the microchannels, we introduce a three- and a one-dimensional model. As these are given by strongly coupled and highly nonlinear systems of partial differential equations (PDEs), we present our software package cashocs which implements the adjoint approach and facilitates the numerical solution of the subsequent optimization problems. We solve a parameter identification problem numerically to determine necessary kinetic parameters for the models from experimental data given in the literature. The obtained results show excellent agreement to the measurements. Finally, we present two optimization problems for optimizing the reactor's product yield. First, we use a tracking-type cost functional to maximize the reactant conversion, keep the flow rate of the reactor fixed, and use its wall temperature as optimization variable. Second, we consider the wall temperature and the inlet gas velocity as optimization variables, use an objective functional for maximizing the flow rate in the reactor, and ensure the quality of the product by means of a state constraint. The results obtained from solving these problems numerically show great potential for improving the design of the microreactor.