Generic Reaction Package Framework¶
The generic reaction package framework is still under development. Whilst the current framework is functional, features are still being developed and added.
The generic reaction package framework builds upon the existing framework for implementing reaction packages within IDAES, and will not prevent the use of custom written reaction packages in the future. Whilst it is hoped that the generic framework will be able to handle most common applications, users with more unusual systems or those solving computationally intensive problems may need to write custom reaction packages for their cases.
The Generic Reaction Package Framework breaks down reaction packages into a number of components which can be assembled in a modular fashion. Users need only provide those components which they require for their system of interest, and components can be drawn from libraries of existing components or provided by the user as custom code. Details on how to set up the definition of a reaction package using the generic framework are given here.
The components which make up a generic reaction package are as follows:
- Associate the reaction package with an appropriate thermodynamic property package.
- Define the basis of the reaction terms for the reaction package.
- Define the rate-based reactions of interest in the system.
- Define the equilibrium-based reactions of interest in the system. Nore that phase equilibrium is generally handled in the thermodynamic property package.
The following sections will describe how to define a reaction package using the Generic Reaction Package Framework along with the libraries of sub-models currently available. Finally, the developers section describes how to go about defining your own custom components to use when creating custom property packages.
Within most IDAES models “parameters” are in fact defined as Pyomo ‘Vars’ (i.e. variables) which are fixed at their defined values. Whilst Params would seem to be the logical choice for these, parameter estimation problems require the parameters being estimated to be defined as Vars so that the solver is free to vary them.