Optimization of a Three-Phase Catalytic Slurry Reactor Using Reduced Statistical Models

The main contribution of this work is to propose the use of a statistical procedure to generate simplified models from a detailed deterministic one for Real Time Optimization. Such models are also used as a tool to map the optimal and feasible region. These simplified models are useful in online optimization coupled to control implementations, since detailed rigorous models may demand time and high computational burden for their solution, which hampers the success of online purposes. In order to illustrate the application of the procedure, a three-phase catalytic reactor was considered. A dynamic heterogeneous mathematical model formulation of the o-cresol hydrogenation reaction was used to simulate the reactor steady-state response to different inlet conditions. The proposed statistical procedure (factorial design) generated simplified models for the reactor exit temperature and the reactant conversion, two useful pieces of process information. The use of these models in an optimization problem is then presented as an illustration of their application in an online real time optimization in a two-layer fashion. The simplified models turn possible the identification of the range of optimal solutions as well as the mapping of the region of optimal solutions very quickly compared to the use of full models, allowing the system to be flexibly operated at high level of performance.