Generating stochastic input signals such as noise in physical systems is traditionally implemented using discrete random number generators based on discrete time-events.
Within the Modelica community, random number generators free of time-events have recently been proposed in order to increase the performance of system simulations.
However, the impact of such signals on commonly used solvers, such as DASSL or Radau IIA, is still under discussion.
In order to provide better understanding for modeling practitioners, we examine the influence of event-free noise models on simulation performance.
To this end, we conduct practical simulation experiments with systems of three sizes, two solvers, and different parameters.
Results indicate that step-size control can handle event-free noise generators well and that they outperform sampled generators.
The findings can be related to other time-dependent system inputs
