Steady State (analysis)

Analysis title

Steady State

Provider

Institute of Systems Biology

Class

SteadyStateAnalysis

Plugin

biouml.plugins.modelreduction (Model reduction plug-in)

Description

Find steady state by simuilating model until steady state.

Parameters:

• Input diagram – Input diagram.
• Input state – Input state
• Output type – Output type.
• Result diagram – Result diagram.
• State – Diagram state.
• Simulation result – Simulation result
• Result table – Result table
• Stady state variables – Variables which values will be used for steady state detection. If no variables selected then all variables will be used.
• Relative tolerance – Relative tolerance for steady state.
• Absolute tolerance – Absolute tolerance for steady state.
• Time points number (expert) – Number of consequent time points for steady state detection.
• Start time (expert) – Start time for steady state detection.
• Simulation parameters (expert) – Simulation parameters.
  • Engine type – Engine type.
  • Engine options – Engine options.
    • Initial time – Initial time.
    • Completion time – Completion time.
    • Time increment – Time increment.
    • Simulator name – Simulator name.
    • Simulator options – Simulator options.
      • Absolute tolerance – Absolute tolerance.
      • Relative tolerance – Relative tolerance.
      • Statistics mode – Statistics mode.
      • Integration method – Integration method (ADAMS or BDF)
      • Inner linear solver type – Inner linear solver type
      • Jacobian approximation type – Jacobian approximation type
      • Steps limit – Limitation for solver steps count
      • Minimum time step – Minimum time step.
      • Maximum time step inverted – 1 / maximum time step.
      • Mu – Upper bandwidth of Banded Jacobian
      • Ml – Lower bandwidth of Banded Jacobian
      • Detect incorrect numbers (NaNs and Infs – If true then simulation will end when NaN or Infinity encountered
    • Code generation type – Type of code generation: if auto then BioUML will try to choose by itself.
    • Constraints violation – How to handle constraints violation in the model.
    • Fast reactions handling – Method to handle fast reactions: either as separate ODE system with very fast rate or as algebraic system.
    • Algebraic solver name – Name of algebraic solver which will be used
    • Algebraic Solver parameters – Parameters of algebraic solver which will be used
      • Maximum iterations – Maximum iterations
      • Function tolerance – Function tolerance
      • Minimal gradient tolerance – Minimal gradient tolerance
      • Points tolerance – Points tolerance