cfd-hypothesis

Generate multiple CFD hypotheses with solver, geometry, and constraint specifications.

40|4|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/csml-rpi/AI-CFD-Scientist --skill cfd-hypothesis
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cfd-hypothesis
Source: https://github.com/csml-rpi/AI-CFD-Scientist/tree/main/cfd-skills/cfd-hypothesis
Command: npx skills add https://github.com/csml-rpi/AI-CFD-Scientist --skill cfd-hypothesis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill transforms CFD literature and research topics into concrete, testable hypotheses for simulation.

Core Features & Use Cases

  • Hypothesis Generation: Produces multiple, distinct CFD hypotheses that are grounded in existing research and literature.
  • Parameter Specification: Each hypothesis includes solver, geometry, and quantitative constraints such as Re, CFL, or mesh size.
  • Use Case: For a research topic like turbulence effects in a specific geometry, generate hypotheses to test different Reynolds numbers and turbulence models efficiently.

Quick Start

Use this Skill to produce CFD hypotheses based on your research topic and literature context by providing literature data and your experiment details.

Frequently Asked Questions about cfd-hypothesis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate testable CFD hypotheses from existing research literature?

Generating CFD hypotheses involves submitting your research topic and literature references to produce multiple distinct simulation proposals including solver, geometry, and quantitative constraints like Reynolds number or mesh size.

What parameters are included when creating CFD simulation hypotheses?

CFD simulation hypotheses include parameter specifications for solver selection, geometry definitions, and quantitative constraints such as Reynolds number, CFL number, and mesh size to guide experiments.

Can I use literature-based research to define turbulence models for CFD experiments?

Yes, literature-based research can define turbulence models for CFD experiments by generating multiple hypotheses to test different Reynolds numbers and turbulence models efficiently for a specific geometry.

Do I need to provide specific geometry details to generate CFD hypotheses?

Yes, providing specific geometry details and research topic context is required to generate CFD hypotheses, as the output includes geometry specifications and quantitative constraints tailored to your simulation experiment setup.

What is the best way to structure CFD simulation experiments for different Reynolds numbers?

The best way to structure CFD simulation experiments for different Reynolds numbers is to generate multiple distinct, literature-grounded hypotheses that specify solver, geometry, and mesh constraints to guide testing efficiently.