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A multimodular pseudoheterogeneous model framework for optimal design of catalytic reactors exemplified by methanol synthesis
- Source :
- Chemical Engineering Science. 206:401-423
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Model-based design of chemical reactors via dynamic optimization can be performed using a recently developed approach called Multi-Level Reactor Design (MLRD). As a start, the MLRD method, its extensions and applications over the last ten years are reviewed compactly. In the main part of this contribution, a further extension to the model framework applied within this method allowing for the rigorous consideration of intrapellet transport processes in heterogeneously catalyzed systems is introduced. Accordingly, a system of coupled differential equations describing the mass and energy balance of both, reactor and catalyst pellet is set up. Balance equations are kept strictly distinguished from kinetic approaches, leaving the latter to be easily exchangeable. This leads to a multimodular model structure used to incorporate different models for diffusion flux, heat transport and pressure drop. The type of the extended model structure is “pseudoheterogeneous”, i.e., the domain in which chemical reactions take place is shifted from a commonly applied pseudohomogeneous mixed phase to the catalyst interior while a solid phase on reactor scale is not modelled. Applying the extended and modularized method to methanol synthesis as a case study reveals considerable concentration and temperature gradients inside the catalyst. These are neglected implicitly in pseudohomogeneous approaches which can lead to a violation of the allowed range of operating conditions for a given catalyst. The extended MLRD model framework using a pseudoheterogeneous model overcomes this drawback and allows for apparatus independent reactor design while meeting process specific constraints in both the bulk gas and the catalyst phase. Further, a systematic investigation applying 27 combinations of diffusion flux, heat transport and pressure drop models reveals that a certain performance can be reached with any combination, while the deduced reactor design differs significantly.
- Subjects :
- Optimal design
Pressure drop
Materials science
Scale (ratio)
Applied Mathematics
General Chemical Engineering
02 engineering and technology
General Chemistry
Mechanics
Chemical reactor
021001 nanoscience & nanotechnology
Chemical reaction
Industrial and Manufacturing Engineering
Catalysis
020401 chemical engineering
Scientific method
Phase (matter)
0204 chemical engineering
0210 nano-technology
Subjects
Details
- ISSN :
- 00092509
- Volume :
- 206
- Database :
- OpenAIRE
- Journal :
- Chemical Engineering Science
- Accession number :
- edsair.doi...........c51f7bc39bca09248bb151cf435822c2
- Full Text :
- https://doi.org/10.1016/j.ces.2019.04.036