Generate CFD visualization figures with PyVista and vision-based QA.
npx skills add https://github.com/csml-rpi/AI-CFD-Scientist --skill cfd-viz
Please help me install this Agent Skill. Skill: cfd-viz Source: https://github.com/csml-rpi/AI-CFD-Scientist/tree/main/cfd-skills/cfd-viz Command: npx skills add https://github.com/csml-rpi/AI-CFD-Scientist --skill cfd-viz
It streamlines the creation of high-quality visualization figures for CFD cases using PyVista, enabling clear and publication-ready graphics.
Provide a case directory and specify the desired mode (interpret or full), then run the agent-generated script to create visualizations fitting the specified mode and quality criteria.
High-intent search queries and answers about installing and using this skill.
You can generate publication-quality CFD visualizations without manual scripting by providing a case directory and selecting a mode. The tool automates figure creation using PyVista, applying vision-based QA to ensure graphics meet publication standards.
For CFD case validation, you can create diagnostic figures including mesh overviews, velocity contours, pressure contours, streamlines, y+ maps, and residual histories. These quick diagnostic plots help validate physics efficiently.
Yes, PyVista supports comparative plot generation for multiple CFD cases. You can produce publication-quality figures with consistent styling across cases, including comparison panels, profile plots, and vortex iso-surfaces.
You can use CFD visualization automation to produce research paper figures. It standardizes styling across multiple cases to ensure high-quality, consistent graphics suitable for academic publications and presentations.
The difference between interpret and full visualization modes is the output scope. Specifying a mode tailors the generated script to create visualizations fitting either quick diagnostics or detailed comparative plots matching the selected quality criteria.
Vision-based QA ensures CFD figure readability by automatically evaluating the generated visualizations against publication standards. This mechanism verifies that the output figures are clear, readable, and suitable for academic use without requiring manual review.
SoljournerVisualize 3D CFD velocity fields, pressure contours, and streamlines with PyVista.
TabithaFannyGenerate publication-quality figures and LaTeX comparison tables from data.
xjtulycAutomate OpenFOAM CFD case setup, solver execution, and headless post-processing.
gracefullightGenerate static, animated, and interactive plots with Matplotlib.
