Cantera Outline

Overview of Cantera

• Capabilities
  • High level division of Cantera's capabilities
  • Zero-D, One-D, phase objects, numerics

• Division of capabilities should roughly follow how Cantera source code is divided
  • Apps - utilities for converting between Chemkin and Cantera file formats, parsing input files, comparing output files, etc.
  • Base - more utilities for array storage, printing and logging, XML file parsing, Cantera errors/exceptions,
  • Clib - code for C API
  • Converters
  • Equil
  • Fortran - code for Fortran API
  • Kinetics - classes for getting/setting/calculating reaction network quantities (net production rate source terms, reaction rate parameters, etc.)
  • Matlab - code for Matlab API
  • Numerics - classes for solving ordinary differential equations, evaluating Jacobians, Newton methods, constructing and solving matrices, etc.
  • OneD - classes relating to one-dimensional simulations (domains, stacks, one-dimensional flame simulations, etc.)
  • Python - code for Python API
  • Spectra
  • Thermo
  • TPX
  • Transport
  • ZeroD - classes relating to zero-dimensional Reactors (Reactor, Wall, etc.)

Kinetics

• Discussion of kinetics
  • Separate from reactors themselves
  • Reaction rate source terms
  • Kinetic mechanisms
    • A very simple reaction
    • A very simple reaction network
    • A more complex reaction network
  • Single phase kinetics
    • Source code abstraction
    • Examples of obtaining reaction rates
    • Graphene - how to really USE this information
  • Multiphase surface kinetics
    • Cantera/Surface Coverage Surface coverage, site density, formulation of approach
    • Source code abstraction - Walls vs. SurfPhase vs. (etc.)

Thermodynamics

• Somewhere in our algorithm, looping over domain (or for the single reactor control volume), and we're saying, "update thermo and transport parameters" - focus on how this is being done, what classes its using, what capabilities are available

• Single phase
  • Mixtures
  • Equations of state
  • Equilibrium
  • Piston-cylinder systems

• Multiphase
  • What thermodynamics is there for multiphase systems?
  • Heat transfer to-from surface

Transport

• Follow BSL a bit on this one...

• Mass transfer
  • Cantera Outline/Diffusion Mixture vs. multicomponent diffusion
  • Cantera Outline/Diffusion Coefficients - Diffusion coefficient models
  • Mass transfer coefficients

• Heat transfer
  • Heat diffusivity
  • Heat transfer coefficients

• Momentum transfer
  • Viscosity

• General discussion: non-dimensional analysis, how it relates to Cantera
  • Prandtl matlab examples - comparing transport properties (Prandtl number) for mixture-averaged and multicomponent models

Reactor Design

• Description of generic Cantera reactors, canonical CHE reactor types
• Cantera/Reactor Equations General Cantera reactor equations
• Integral vs. differential reactors
• Isothermal vs. non-isothermal reactors
• Heterogeneous vs. homogeneous
• Transport effects in reactors
• Fogler, Froment/Bischoff, Belfiore

Numerics

Cantera/Fipy PFR

• Division of "numerics" layer and "constitutive equations" layer

• Topics
  • Newton's method
  • Linear algebra
  • Jacobians
  • ODEs

• Zero-dimensional ordinary differential equations
  • Problem type
  • Problem solution techniques

• One-dimensional ordinary differential equations
  • Simplification of a more complex problem (PDE) with assumptions like axisymmetric flow

• Initial value problems
• Boundary value problems
• Advanced boundary conditions

• Surface coverage equations
  • Surface species treated as control volume properties
  • Packaged up into the Reactor's solution vector
  • The hack that makes a boundary condition into part of the domain

• Strategies for coupling Cantera with CFD
  • Interfacing with Chemkin-like programs (Fluent)
  • Constructing your own numerical ODE/PDE solver
  • Scipy: simple kinetic equation integration using Scipy
  • Fipy: simple diffusion problem, coupling with Cantera
  • Fipy: more complex reactor equation(s) and coupling with Cantera

Optimization

• Not going into too much depth
• Optimizing kinetic parameters to fit data
• Optimizing other variables to maximize reactor performance

Mechanics

• Debugging
  • Diving in
  • Picking apart

• Hacking