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thermal-fluid-analysis — Claude Code skill: analysis and setup

This skill guides analysis of thermal-fluid systems, experiments, and CFD. Use it to connect numerical results with physical mechanisms, assumptions, and limits of applicability.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add hanhuark/mechanical-engineering-research-skill --skill thermal-fluid-analysis -a claude-code
Open on GitHub

What thermal-fluid-analysis does

The skill structures an analysis from system definition through model selection and evidence checks. It asks the agent to distinguish measured, simulated, derived, assumed, and inferred quantities, while keeping units, sign conventions, property states, and system boundaries clear. It covers heat transfer, fluid mechanics, phase change, HVAC, energy systems, turbomachinery, piping, and thermal management.

For experiments, it calls for calibration, data reduction, heat-loss treatment, repeatability, and uncertainty. For CFD, it asks for the domain, mesh evidence, models, boundary conditions, solver criteria, and validation data. Checks include conservation, dimensional consistency, limiting cases, and an independent estimate where possible. A converged CFD result counts as numerical evidence, not experimental proof; that distinction matters when drawing conclusions.

What it helps with

  • estimate heat transfer and pressure drop in a system
  • check whether a correlation fits the operating regime
  • separate sensor uncertainty from run-to-run variation
  • review CFD mesh evidence and boundary conditions
  • explain the mechanisms behind a plotted change

Example prompts for the agent

  • Review this heat-exchanger CFD model and list its assumptions, credibility checks, and limits.
  • Assess uncertainty in this heat-transfer experiment, separating sensor error from variation between runs.
  • Explain the pressure-drop change in this piping system and state the conditions that could invalidate the conclusion.

How to install thermal-fluid-analysis

1Skills CLI (Vercel)

npx skills add hanhuark/mechanical-engineering-research-skill --skill thermal-fluid-analysis -a claude-code

2Manually: put the files in place

~/.claude/skills/thermal-fluid-analysis/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/thermal-fluid-analysis/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about thermal-fluid-analysis

How do I install thermal-fluid-analysis in Claude Code?

Run npx skills add hanhuark/mechanical-engineering-research-skill --skill thermal-fluid-analysis -a claude-code. The skill file is at ~/.claude/skills/thermal-fluid-analysis/SKILL.md.

What does thermal-fluid-analysis do?

It guides analysis of thermal-fluid systems, experiments, and CFD, with attention to physical mechanisms, assumptions, uncertainty, and model limits.

What CFD details does the skill ask for?

It calls for the domain, mesh and mesh-independence evidence, models, boundary and initial conditions, convergence criteria, and validation data.

Source text

SKILL.md · MIT
---
name: thermal-fluid-analysis
description: Analyze thermal-fluid engineering systems, experiments, CFD, and correlations with explicit assumptions, validity limits, uncertainty, and mechanism-based interpretation. Use for heat transfer, fluid mechanics, phase change, HVAC, energy systems, turbomachinery, piping, or thermal management.
---

# Thermal-Fluid Analysis

## Purpose

Develop decision-ready thermal-fluid analysis without separating numerical output from physical meaning. State what is measured, simulated, derived, assumed, or inferred; retain units, sign conventions, property states, system boundaries, and applicability limits.

## Analysis Workflow

1. Define the system: geometry, working fluid, operating regime, boundary conditions, performance metrics, and constraints.
2. Establish the physical model: governing balances, material properties and their evaluation state, dimensionless groups, competing mechanisms, and expected limiting behavior.
3. Select evidence: standards, handbooks, peer-reviewed work, calibrated measurements, validated CFD, or correlations inside their stated range.
4. Test credibility: dimensional consistency, conservation, order of magnitude, limiting cases, uncertainty/sensitivity, and an independent analytical or empirical check where possible.
5. Conclude by mechanism and tradeoff: performance, pressure drop or pumping power, manufacturability, reliability, cost, safety, scaling, and residual risk.

## Experiments

Report the facility and specimen geometry, instrumentation, calibration, sampling, procedure, data reduction, heat-loss treatment, repeatability, uncertainty propagation, and exclusions. Distinguish sensor uncertainty from run-to-run variability. Do not call a preliminary demonstration validation without a stated comparison target.

## CFD And Modeling

List all assumptions before presenting results and justify each one. State the domain, mesh and mesh-independence evidence, models, wall treatment, property models, boundary and initial conditions, solver/convergence criteria, time step where applicable, and validation data. Treat a converged solution as numerical evidence, not experimental proof.

## Results Discussion

For each important figure, move through: what is plotted; what changes; the physical explanation; and comparison with literature, theory, or an independent data source. Do not merely restate a trend. Explain the regime, competing mechanisms, and the conditions under which the conclusion might fail.

## Final Check

Before finalizing, check regime classification, property variation, phase state, coordinate/sign conventions, uncertainty, model validity, and safety or code constraints. Escalate unknown operating conditions that materially change the conclusion.

© hanhuark · MIT · hanhuark/mechanical-engineering-research-skill

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