(481e) Multi-Objective Catalyst Shape Optimization for Solid-Catalyzed Gas-Phase Reactions with q-Expected Hypervolume Improvement Via Particle-Resolved CFD Simulations
AIChE Annual Meeting
2022
2022 Annual Meeting
Catalysis and Reaction Engineering Division
Modeling and Analysis of Chemical Reactors II
Wednesday, November 16, 2022 - 1:42pm to 2:00pm
This presentation describes an integrated workflow for multi-objective optimization (MBO) of optimal catalyst shape in fixed bed reactor from computational generation and meshing of arbitrary-shaped particles in randomly packed beds through to the CFD calculation. The workflow, physics engine based automated packed bed reactor generation, geometry processing with shrink-wrap method for contact regions handling, and particle-resolved CFD simulations for continuum-scale fluid dynamics to simulate solid-catalyzed gas-phase reactions (methanol, dimethyl-ether, Fischer-Tropsch synthesis) in a fixed-bed reactor. The effect of the shape of catalyst particle is investigated with sphere, cylinder, trilobe, quadrilobe, cross-web and Raschig ring. Since the discrete element method is computationally costly to be implemented, a rigid-body model in Blender that showed accurate agreement for porosity compared to DEM in the commercial software STAR-CCM+ is applied. Furthermore, MBO which use Gaussian process as a surrogate model, and q-expected hypervolume improvement (qEHVI) as an acquisition is utilized to reduce the required number of CFD simulations for optimal catalyst shape selection. The resulting Pareto front yields near-optimal particle shapes with significantly reduced simulation time compared to conventional methods reported. We anticipate that this integrated workflow can be applied not only to optimal packed-bed reactor design problems with arbitrary-shaped catalyst particles but also to an expansion of any solid-catalyzed gas-phase reactions.