High-fidelity models for optimising catalytic reactor design
The gPROMS Advanced Model Library for Fixed-Bed Catalytic Reactors (AML:FBCR) is a library of high-fidelity modelling components for modelling of tubular, multitubular and other fixed-bed reactors.
Part of PSE's extensive capabilities for reaction engineering, the AML:FBCR is used to create multiscale reactor models capable of representing virtually any fixed-bed reactor configuration to a high degree of predictive accuracy.
Applications and benefits
Optimisation of the design and operation of fixed-bed catalytic reactors requires highly detailed models that can represent the complexity at all levels from the microscale reaction and diffusion phenomena occurring in the catalyst to the macroscale operation within the full industrial reactor geometry.
The AML:FBCR provides high-accuracy catalyst and packed-bed models, plus cooling models, for tubular (including multitubular) and annular reactors. It has been proven in many industry applications for a wide variety of reactions.
There are many benefits to applying the AML:FBCR high-fidelity models. These can be summarised as:
- Reduced model development time. Detailed models can be constructed in weeks rather than months.
- Improved reactor design. Predictive models can be used to optimise many aspects of geometry to ensure uniform operation.
- Improved operations. Similar models can be used to optimise operating conditions and thus enhance catalyst life.
- Realistic "catalyst test bed". Model simulations can be used for designing, screening and ranking catalyst.
- Engineering focus. Support for process development and scale-up, catalyst development and general innovation, as part of a model-based engineering programme.
The AML:FBCR aims to make life easier for reaction engineers by providing a packaged tool that embodies many years' research and development into physics and chemistry representation and modelling techniques. It provides:
- high-fidelity catalyst models with Maxwell-Stefan multicomponent diffusion techniques for intraparticle transport
- 1-D and 2-D catalytic tube models that model all key phenomena related to bed mass and heat transfer
- a variety of cooling models
- easy addition of specific kinetics, physical properties and transport properties
- the hybrid multitubular interface to CFD to incorporate cooling hydrodynamics.
In addition, it comes with all the advantages of the gPROMS environment:
- gPROMS ModelBuilder drag-and-drop flowsheeting to construct composite models
- interaction via specification dialogs
- the ability to execute steady-state and dynamic simulation and optimisation
- state-of-the-art parameter estimation and data analysis capabilities to determine reaction kinetic parameters and heat transfer coefficients from experimental or pilot data
- advanced results management capabilities, including 3-D plots.
The AML:FBCR comprises:
|Ancillary models, AML variable types and connection types||Aggregator|
|Empty tube sections|
|Catalyst Bed – Axial Flow|
|Catalyst bed models where the convective flow is considered in the axial direction|
|Heterogeneous model, separate pellet and fluid conservation equations||Catalyst pellets bed section|
|Adiabatic catalyst pellet bed section|
|Pseudo-homogeneous model, no explicit pellet treatment||Catalyst bed section|
|Adiabatic catalyst bed section|
|Inert pellets||Inert bed section|
|Gas cooled bed section|
|Catalyst Bed – Axial Flow Annular|
|Catalyst bed models where the convective flow is considered in the axial direction and the heat transfer is considered from both inside and outside tube walls, for modelling of catalytic reactor configurations with concentric annular beds||Counter-current annular bed sections|
|Co-current annular bed sections|
|Catalyst Beds – Radial Flow|
|Catalyst bed models where the dominant convective flow is considered in the bed radial direction||Adiabatic flow models for 1D and 2D beds|
|Flow models for 1D and 2D beds with internal cooling|
|Cooling section models||Boiling water cooling section|
|Fixed coolant models|
|Bed and fluid properties models||Bed properties models for 1D and 2D beds|
|Fluid properties models for 1D and 2D beds|
|Fluid properties models inside pellets for 1D and 2D beds|
|Templates for user defined models||Properties parameters|
|Kinetics models for 1D and 2D beds|
|Kinetics models for 1D and 2D beds with 1D pellet|
Models can be combined as required to provide any fixed-bed configuration, simply by dragging the models from the palette (above right) and connecting them with the appropriate stream.
For example, the flowsheet below shows a single tube pilot reactor comprising two 2-D catalyst beds (which could contain different catalyst formulations) between two sections of inert, used for determining bed heat transfer coefficients from experimental data.
The fixed bed models have many different operation modes:
- gas phase
- liquid phase
- homogeneous and inhomogeneous catalyst
- multitubular design
Configuration to your particular reaction
Some models are provided as templates in open form to allow you to configure your own reaction scheme, rate equations, properties and so on.
In these models you can enter any relationships you wish in gPROMS language form.
Other models are specified using the specification dialogs. The example below shows the general settings for the 2-D catalyst pellets section:
Once the complexity of the reaction has been captured in a tube model, a number of tubes can be assembled into a multitubular reactor model, taking the shell-side cooling effects into account in on of the following ways:
- 1-D shell-side model. This is the simplest and fastest approach, and generally gives sufficiently accurate results for design and trouble-shooting purposes.
- CFD shell-side model (below). Where a very high degree of predictive accuracy is required, gPROMS can be linked to a CFD package for calculation of shell-side fluid dynamics and heat transfer coefficients, using PSE's Hybrid gPROMS—CFD Multitubular option.
Typical results are temperature and concentration profiles through catalyst, tube and shell, accurately calculated from validated first-principles models, for example: