RAPID

Advanced reactor designs with multiple catalysts are game-changers for process intensification. These reactors transform large, complex processes with multiple reactors to one-shot reactors, where complex reaction mechanisms can be exploited within a single unit. Such designs lead to layered and mixed catalyst beds that overcome equilibrium limitations, manage heat effects and improve product selectivity. These graded bed reactors have been considered for a number of reactive systems, ranging from Fischer-Tropsch synthesis, benzene hydrogenation, oxidative coupling of methane and steam reforming. This project develops and applies a new approach for the optimization of graded bed systems, based on EO-based optimization of fully discretized DAE (differential-algebraic equations) and PDAE (partial differential-algebraic equations) models. Known as direct transcription, this approach has been widely applied to challenging dynamic optimization problems, adapted to large-scale optimization software and is generally much faster and more reliable than with standard commercial tools. In particular, for graded beds, this approach stabilizes exponential forward modes and applies specialized regularization strategies in order to handle singular problem characteristics. As the target application, this project is especially devoted to improving the design and optimization methodologies for syngas to olefin (STO) processes, with emphasis on producing light (<C5=) olefins. Here, the optimization process significantly advances the synergies between methanol synthesis catalysts for syngas reactions and zeolite catalysts that produce light olefins.