Experiments in Modelon Impact

The main purpose of Modelon Impact is to simulate and analyze technical systems. To do this, you can perform Experiments in Impact.

An Experiment is always based on a simulation model. The Experiment inherits the properties and parameters of the model and it allows you to vary parameters without changing the model, i.e. the Modelica code itself.

With an Experiment, you can:

• Modify/Change model parameters

• Determine which type of simulation is to be performed (which Custom function will be performed):

  • Analysis in the time domain (Dynamic),
  • Steady-State analysis,
  • Custom function.

• Modify/Adjust solver and compiler settings

Experiment Setup

If you switch to the Experiment layer of your model, you will find two views of your model:

• the Diagram View and
• the Experiment Setup view.

Setup via Diagram View

Using the Diagram View you see the structure of your model, and you can select model components and in the right sidebar, you can change parameters.

Furthermore, on the right side-bar, you can:

• Create/delete/select Experiments via the Experiment Browser,
• Duplicate Experiments,
• Save Experiment settings back to your model,

• Select and set which kind of simulation is to be performed:

  • Dynamic (time domain simulation)
  • Steady-State simulation
  • Custom Function

• Set Execution settings

• Set output filters, in order to limit the result size

Parameters changed for the Experiment are marked with a blue background.

Setup via Experiment Setup View

The Experiment Setup View is a clear interface for configuring Experiments, especially Multi-run experiments.

Multi-run means, that the model is simulated in a kind of batch run with different parameters in order to statistically evaluate the results.

On this view, you can:

• Select the Experiment type:

  • Single run
  • Parameter sweep
  • Statistical analysis

• Add parameters to be changed/modified for the Experiment

• Set modifications (changes) of parameters (according to the selected Experiment type)
• Set output filters, in order to focus more on the requested results and to minimize the result size (recommended for large-scale multi-run experiments)
• Observe the number of cases for Multi-run experiments
• Observe the estimated(!!!) result size per case or in total

Related articles

Simulate a model | Perform Multi-run Experiments | Experiment Types