Learn COMSOL-MULTIPHYSICS-SCRIPTING with Real Code Examples
Updated Nov 27, 2025
Installation Setup
Install COMSOL Multiphysics and required modules
Optional: Install MATLAB if using MATLAB API scripting
Verify licenses for desired modules and scripting interface
Set working directory and environment variables for scripts
Test sample model scripts to confirm setup
Environment Setup
Install COMSOL Multiphysics
Install MATLAB for LiveLink scripting (optional)
Set working directories for scripts and model files
Ensure required modules are licensed and installed
Test with a sample script to validate setup
Config Files
Model files (.mph) with all simulation components
MATLAB or Java scripts for automation
Data input files (CSV, MAT, Excel)
Custom functions or S-Functions for physics extensions
Toolbox or module configuration files
Cli Commands
mphstart - Launch COMSOL server
mphload('model.mph') - Load a model
model.study('std1').run - Run a study programmatically
mphsave('model.mph') - Save updated model
mphplot(model, 'pg1') - Generate plots automatically
Internationalization
Supports multiple languages in GUI and messages
Numeric formats follow system locale
Custom labels and annotations can be localized
Data files compatible with international standards
Integration with global engineering teams
Accessibility
Accessible via GUI, MATLAB, or Java scripts
Remote batch execution supported via scripting
HPC cluster support for large parametric studies
Results exportable for other applications
Automation allows reproducible workflows
Ui Styling
GUI is COMSOL Model Builder
Plots generated via API or GUI
Dashboard and 2D/3D plots for results
Export figures in multiple formats
Optional custom visualization in MATLAB
State Management
Model state encapsulated in COMSOL objects
Parameters can be modified dynamically
Batch simulations maintain consistent parameter sets
Results logged in workspace or exported files
Version control ensures reproducibility
Data Management
Input parameters from MATLAB variables or external files
Simulation results stored in MATLAB arrays or files
Large datasets handled with memory-efficient techniques
Automated postprocessing for visualization or reporting
Integration with databases for design optimization