Scope of Scripting Languages in Automation of CFD simulations

Advantages of Scripting Languages 

  • Scripting languages play a significant role in automating Computational Fluid Dynamics (CFD) simulations.
  • CFD simulations involve complex and repetitive tasks, and scripting languages can streamline and automate various aspects of the simulation process, enhancing efficiency and productivity.
  • Some scripting languages commonly used in this domain include Python, Perl, Bash scripting, and others. Among these, Python is highly favored due to its readability, extensive libraries, and versatility.
  • Here’s how scripting languages are employed in the automation of CFD simulations:
  1. Pre-processing and setup:
    • Scripting can be utilized to automate the generation of mesh files, defining boundary conditions, geometry setup, and preprocessing tasks.
    • Tools like Python with libraries such as PyMesh or other specialized CFD libraries can automate these processes, saving time and reducing human error.
    • Python script can be integrated with commercial and open-source CFD tools like ANSYS FLUENT and OpenFOAM
  2. Parametric studies and optimization:
    • Scripting languages are excellent for running parametric studies by iterating through different simulation setups, varying parameters, and performing optimizations.
    • This enables engineers to explore different design alternatives efficiently.
  3. Post-processing and data analysis:
    • After the simulation, scripting can automate the post-processing phase, analyzing the results, generating visualizations, and extracting specific data points of interest from the simulation output.
  4. Workflow integration:
    • Scripting allows the integration of CFD simulations with other software or tools.
    • For instance, linking CFD simulations with CAD software, data analysis tools, or optimization algorithms can be achieved using scripting.
  5. Job scheduling and management:
    • In high-performance computing (HPC) environments, scripting languages help manage and schedule simulations across multiple computing nodes, optimizing resource utilization and job management.
  6. Customization and extension:
    • Scripting languages provide the flexibility to create custom scripts or plugins to extend the functionality of existing CFD software, tailoring it to specific requirements or automating unique tasks.

Python Script for ANSYS FLUENT

  • ANSYS Fluent provides several ways to automate tasks using scripting languages, such as Scheme or Python.

Python (Script) + Ansys Fluent (CFD solver in C)= PyFluent

  • Please note that ANSYS Fluent provides an API for scripting tasks. The following example demonstrates how to use Python with the ANSYS Fluent API to set up a simple simulation.
  • This code is a basic illustration of how you might automate some tasks in ANSYS Fluent using Python.
  • It’s important to note that the ANSYS Fluent API might require more sophisticated commands or specific procedures to control various aspects of the simulation, depending on your simulation setup.
  • Refer to the scripting documentation of ANSYS  or available APIs for Python to explore a more comprehensive list of commands and functionalities that can be used to script tasks in the CFD solver of FLUENT.
  • The provided script is a simple example and may need modifications and additional commands to suit specific simulation setups or complex tasks.

 Install PythoFluent

  • This is not bundled with the Fluent installation
  • if you are familiar enough with Python programming then you can access PyFluent the same way you access all other Python libraries using GIT Hub

Write Python Script for Simulation 

  • You have to write a script for reading of mesh files, boundary conditions and solver set up and simulation in pythoFLUENT
  • Compile and run the simulations
Script for ANSYS FLUENT in python
Script for ANSYS FLUENT in python

Python Script for Open FOAM

Examples of Python Script

This is a basic example that showcases how you can interact with OpenFOAM using Python. Here’s a breakdown of the script:

  1. Importing necessary libraries: The script imports the required libraries from PyFoam to work with OpenFOAM cases.
  2. Defining the case directory: You specify the path to the OpenFOAM case directory you want to work with.
  3. Accessing and modifying control parameters: In this example, it accesses the control diet file within the case and modifies a parameter (in this case, the endTime).
  4. Saving changes: After modifying the control parameters, the script saves the changes made to the controlDict file.
  5. Running the Open FOAM solver:
    • The script executes the OpenFOAM solver (simpleFoam in this case) for the case you’re working on.
  • Depending on the complexity of your simulations, you may need to script more involved processes, handle errors, perform pre- and post-processing tasks, or control different solvers and utilities within OpenFOAM.
  • Always ensure that you have a good understanding of both Python and OpenFOAM’s structure and functionalities to effectively script and control CFD simulations using Python.
Script for Open foam in python in CFD simulations
Script for Open foam in Python in CFD simulations

How to write a script for CFD simulation in Python for Open Foam

  • Python and OpenFOAM, a popular open-source CFD software package, can be combined to script, automate, and control simulations using the OpenFOAM functionalities.
  • Python is not the native language for OpenFOAM, but it can be used in conjunction with OpenFOAM to automate tasks and control simulations.
  • For this purpose, the PyFoam library is commonly used to interact with OpenFOAM using Python.
  • Here’s a basic example of how you might set up a Python script to control OpenFOAM simulations using the PyFoam library:


  1. Install OpenFOAM: Ensure that OpenFOAM is installed and properly configured.
  2. Python and PyFoam: Install Python (if not installed) and the PyFoam library.
  3. Write the Python Script:
    • Import the necessary Python libraries and PyFoam modules.
    • Set up the OpenFOAM case directory or create a new one if needed.
    • Define and configure the simulation case, including mesh generation, boundary conditions, solvers, and control parameters.
    • Run the simulation using PyFoam commands or by calling OpenFOAM utilities within the script.
    • Post-process the results, extract data, and create plots or reports as required.
  4. Here’s a simplified example of a Python script for running a steady-state incompressible flow simulation with simpleFoam in OpenFOAM using PyFoam:


  • Overall, scripting languages empower CFD engineers and researchers by providing the means to automate and streamline various aspects of the simulation process, reducing manual labor, increasing efficiency, and allowing a more in-depth exploration of design spaces.
  • Python’s popularity in this domain is largely due to its extensive libraries, readability, and the ease with which it can be integrated with various CFD software and tools.



  1. ANSYS , Providing Python Script for FLUENT 
  2. Wiki foam, Python for Open FOAM
  3. OpenFOAM journal, A General Approach For Python codes in OpenFOAM
  4. Introduction of PythoFOAM, Videos
  5. Ansys Learning, How to Use PythoFLUENT

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