Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
5 Hour(s) 11 Minute(s)
Language
English
Taught by
Cesar Jimenez Navarro
Rating
4 views
Course Overview
Automating postprocessing for researchers and engineers with Python scripts
Automate ParaView Post-Processing with Python — Save Time, Boost Insight, and Create Stunning Visuals
Do you work with CFD or FEA simulation data from tools like ANSYS Fluent, STAR-CCM+, OpenFOAM, SU2, COMSOL, Abaqus, or LS-DYNA?
Tired of repetitive post-processing and manual visualization steps?
This course teaches you how to automate ParaView workflows with Python, helping you process large datasets faster, eliminate repetitive tasks, and create professional-quality scientific visualizations.
What You’ll Learn
Automate ParaView post-processing with Python scripting
Apply advanced filters for CFD and FEA data analysis
Extract key quantities such as gradients, vorticity, and Q-criterion
Work with both steady-state and unsteady (transient) data
Create high-quality animations and presentation-ready visuals
Set up and use remote or parallel processing for large datasets
Course Structure
Introduction to ParaView and Scripting – Learn the interface, key filters, and remote visualization setup
Steady-State Data – Load, organize, and visualize simulation results efficiently
Common and Advanced Filters – Use colormaps, thresholds, gradients, and advanced field operations
Data Extraction – Generate plots, streamlines, and vector visualizations
Unsteady Data – Manage time-dependent simulations and record dynamic animations
Advanced Animations – Produce smooth, high-quality visual sequences for presentations and reports
Why Take This Course
Automate repetitive tasks and save hours of manual work
Turn complex simulation data into clear, insightful visualizations
Improve efficiency and productivity in CFD and FEA workflows
Apply skills across engineering, research, and scientific visualization
Learn from practical, real-world aerospace and engineering examples
Who This Course Is For
Engineers, researchers, and students working with simulation data
Professionals in aerospace, mechanical, and computational sciences
Anyone who wants to master ParaView scripting and streamline their analysis
Enroll Now
Learn how to automate ParaView post-processing with Python, analyze your simulation data more effectively, and create visualizations that communicate results with impact.
Course Content
- 9 section(s)
- 42 lecture(s)
- Section 1 Introduction
- Section 2 Working with steady-state data
- Section 3 Common filters
- Section 4 Data Analysis and Manipulation Filters
- Section 5 Data extraction
- Section 6 Unsteady data
- Section 7 Advanced animations
- Section 8 Formula Student CFD Analysis
- Section 9 Advanced Post-Processing
What You’ll Learn
- Using Filters and Processing Data Programmatically, Automating Visualization Tasks, Creating and Customizing Visualizations, Working with Time-Dependent Data, Batch Processing and Remote Visualization
Skills covered in this course
Reviews
-
SSebastian Nuñez
I have used Paraview to create graphs of my CFD simulations from OpenFOAM before, but only using the tools already present in the GUI. Learning how to implement python scripts to automate visualization tasks has significantly increased my skills to create better graphs that are easier to understand/explain without having to spend so much time working on post processing. While my previous experience with Paraview was helpful for this course, I will recommend this to someone with little to no experience with the software. I would say knowing the basics of python is enough. Additionally, it will be helpful to have some background in CFD to better understand what kind of information you want to display based on your needs. To anyone considering this course: good luck and don't miss out!
