Get an Overview about the Design Tools for DYMOLA

Model experimentation involves running simulations for various combinations of parameters to determine the modeled system’s properties. Model calibration helps user to tune parameters such that the simulation results are in good agreement with the measured data. Design optimization improve system dynamics for multiple criteria and multiple Use Cases. In general these options helps user to perform simulation effectively and manage the models easily.

Model Exploration and Management in Dymola

Dymola streamlines parameter sweeps, automates model calibration for real-world data, and enhances system performance through design optimization. It also offers robust model management, including encryption and version control.

Sweeping Parameters
Design Optimization
Model Calibration
Model Management

Few models are simulated only once. In fact, running several simulations with different parameters and comparing the results is one of the most fundamental user tasks. This can be done with scripts in Dymola or from Python, or using the built-in functionality.

Dymola has a modern user interface that allows the user to drag-and-drop variables that will be used to sweep and to visualize the results. When sweeping one parameter, you have the choice of plotting the full trajectories or just the points at end of simulation. When sweeping two parameters Dymola will plot a surface from the last points. For three or more parameters, scatter plots are used.

Parameter sweeps automatically run in parallel on all available cores of the computer's processor.