Speaker
Description
Designing efficient chemical reactors requires bridging the gap between laboratory-scale experiments and industrial applications; a task often challenged by the complex interplay between reaction kinetics and transport phenomena. Miniaturization of experimental setups can reduce material costs but also amplifies these transport effects, especially in packed beds where geometric constraints strongly influence flow behavior.
In this work, we employ a fully open-source framework, starting from pore scale computational fluid dynamics (CFD) to explore how catalyst geometry influences reactive transport within packed-bed reactors. Digital reconstructions of real catalyst particles of arbitrary morphology were created using Blender, and used to simulate fluid flow and species dispersion in realistic packed-bed reactors, capturing key hydrodynamic features such as bypass zones and stagnant regions using the mean age theory. This steady state analysis is used as a diagnostic tool to quantify local residence time distributions and identify transport heterogeneities inside complex geometry.
To connect numerical modeling with real world reaction kinetics, we applied this general framework to a specific heterogeneous catalysis application, that of Aqueous Phase Reforming, which generates hydrogen from crude glycerol in wastewater. For this case, a kinetic model was derived from batch reactor experiments (where mass transfer limitations are absent,) and adapted to the CFD framework in OpenFOAM where we can investigate accurately the interplay between transport and reactions phenomena by easily reproducing different kinds of catalyst geometries and operating condition.
In particular, reactive pore scale CFD is used to evaluate the performance of a packed-bed reactor by means of its conversion and yield. The reactions were implemented as a boundary condition on the catalytic external surface, and fluid flow is considered only outside the catalyst. This methodology was then also compared to a more accurate model that resolves also the species transport inside the catalyst, increasing the accuracy of the simulation, at the cost of increasing computational expense and numerical instability.
Lastly, multiphase interactions are incorporated through a pore scale mixture-transport formulation capable of describing liquid–gas–solid systems with algebraic closure relations for slip velocity. This model was developed to simulate the reacting flow and of two fluid phases in a solid porous media taking simplification to allow either phase to act as the dispersed without raise to prohibitive computation cost.
This methodology provides a versatile and computationally efficient tool to investigate multiphase catalytic processes beyond a specific reaction system, offering insights relevant to a wide range of reactor technologies.
Acknowledgments: PNRR M4C2, Investimento 1.4 - Avviso n. 3138 del 16/12/2021 - CN00000013 National Centre for HPC, Big Data and Quantum Computing (HPC) - CUP E13C22000990001
| Country | Italy |
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