(82c) Coupling Process Simulation and Computational Fluid Dynamics to Efficiently Design and Improve Multi-Scale Processes

Almost all real-world processes are multiscale processes, which mean that they have important features at different scales in time and/or space. Typically, not all scales can be resolved, so that for simulations of such processes certain assumptions or simplifications have to be made.

In the process industry for example, simulations are performed on a range of different scales and different purposes. Flow-sheet simulations are used for designing and validating the full process from raw material to the final product in terms of heat and mass balances, sizing and cost. Process simulations are conducted to get a deeper understanding of the underlaying chemical, physical or biological processes in unit operations, a basic step in a process. Such simulations are typically done with simplifying assumptions regarding the flow and other properties like ideal mixing in stirred tanks or plug-flow in tube-like devices and their focus is on the accurate description of the detailed physics. Finally, CFD simulations allow the detailed analysis of flow, turbulence and other relevant parameters in the equipment.

Since most processes depend, more or less, on local conditions, there is an obvious benefit to integrating process models into CFD. In practice, however, the applicability of this approach is limited mainly for the following reasons:

Depending on the system under investigation, the additional equations to be solved can generate a considerable overhead and lead to long computing times.

• The chemical-physical processes often happen on different time scales to the flow and mixing time scale.
• For design studies or variation calculations during design phase as well as during operation, results are required in a short time, usually in seconds or in a few minutes. This typically cannot be achieved with a CFD simulation.

Nevertheless, combining different scales can be very beneficial in terms of accuracy as well as getting a deeper understanding of the underlaying physics as previously shown e.g. for a wet granulation process [1].

In this contribution we show a new automated coupling method between the CFD tool Simcenter STAR-CCM+ and the process modelling tool gPROMS by PSE, where Simcenter STAR-CCM+ solves for all flow properties and gPROMS evaluates the fine scales based on the solution provided. The coupling between both codes is done in an automatic way. This includes the domain decomposition, the calculation of and the transfer of all relevant variables.

The details of the coupling as well as the superiority of this approach will be demonstrated for a packed bed reactor.

Packed bed reactors are one of the working horses in the chemical and process industry. They are used amongst others for highly exothermic or endothermic catalytic reactions like (partial-)oxidation or (dry, steam) reformation of Hydrocarbons, which is typically done in multi-tubular reactors. These types or reactor are used since several decades but there is still room for improvement of the performance of these reactors and rigorous simulations can help here to achieve desired goals with lower upfront invest. Recent advances in modeling particle-resolved packed beds [1,2,3] allows a detailed inside in the flow, species and temperature distribution in the beds and therefore also into the conversion of the surface reactions. Based on these simulations, model parameters for simplified 1D-models can be estimated [4].

References:

1. Eppinger, et al.; DEM-CFD simulations of fixed bed reactors with small tube to particle diameter ratios, https://doi.org/10.1016/j.cej.2010.10.053
2. G. D. Wehinger et al.: Detailed numerical simulations of catalytic fixed-bed reactors: Heterogeneous dry reforming of methane, https://doi.org/10.1016/j.ces.2014.09.007
3. N. Jurtz et al.: Advances in fixed-bed reactor modeling using particle-resolved computational fluid dynamics (CFD), https://doi.org/10.1515/revce-2017-0059
4. N. Jurtz et al.: Determination of Effective Transport Parameters from Particle-Resolved CFD Simulations for a Simplified Fixed-Bed Reactor Modeling (65a), AIChE Spring Meeting 2019, New Orleans