Steady State (analysis)

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Analysis title
DAE-models-Steady-State-icon.png 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
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