Fea Structural logo

Fea Structural

CommunityPopular
Cai-aa
fea-structural

Deep integration with finite element analysis tools for structural simulation across static, dynamic, and nonlinear domains

Overview

PublisherCai-aa
RepositoryCAE-Agent-Hub
Skill namefea-structural
Stars
1K
Forks
130
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Cai-aa on GitHub. Read the source before you install it.

Installation

Install the Fea Structural AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/reference/fea-structural
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Cai-aa/CAE-Agent-Hub.git /tmp/CAE-Agent-Hub
mkdir -p .claude/skills
cp -r /tmp/CAE-Agent-Hub/Skill/abaqus/reference/fea-structural .claude/skills/fea-structural
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fea Structural in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fea Structural on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fea Structural is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Finite Element Analysis Skill

Purpose

The Finite Element Analysis skill provides deep integration with FEA tools for structural simulation, enabling systematic setup, execution, and post-processing of finite element models across static, dynamic, and nonlinear analysis domains.

Capabilities

  • ANSYS Mechanical, Abaqus, NASTRAN model setup and execution
  • Mesh generation strategies and quality assessment
  • Element type selection and convergence studies
  • Boundary condition specification and load case management
  • Linear and nonlinear static analysis configuration
  • Results post-processing and margin of safety calculation
  • Mesh independence and sensitivity studies
  • Report generation with stress/deflection contours

Usage Guidelines

Model Setup

Geometry Preparation
  1. CAD Import and Cleanup

    • Defeature small holes and fillets (analysis dependent)
    • Remove unnecessary detail
    • Verify watertight geometry
    • Create symmetry conditions if applicable
  2. Geometry Partitioning

    • Partition for mesh control
    • Create virtual topology for hex meshing
    • Identify contact surfaces
    • Define load application regions
Mesh Generation
  1. Element Selection

    Analysis TypeRecommended Elements
    Static stressHex20, Tet10, Quad8
    Thin structuresShell (QUAD4/8, TRIA3/6)
    Beam structuresBEAM/BAR elements
    ContactLinear elements preferred
    NonlinearReduced integration with hourglass control
  2. Mesh Quality Criteria

    Aspect ratio: < 5 (< 3 preferred)
    Jacobian: > 0.6
    Warpage: < 15 degrees
    Skewness: < 0.8
  3. Mesh Refinement

    • Refine at stress concentrations
    • Transition ratios < 1.5
    • Multiple elements through thickness
    • Convergence study requirements

Analysis Configuration

Boundary Conditions
  1. Constraints

    • Fixed (all DOF constrained)
    • Pinned (translations fixed, rotations free)
    • Symmetry (appropriate DOF constrained)
    • Prescribed displacement
  2. Best Practices

    • Avoid over-constraint
    • Use RBE2/RBE3 for load distribution
    • Consider realistic support stiffness
    • Document all assumptions
Load Application
  1. Load Types

    • Pressure (uniform, hydrostatic)
    • Force (point, distributed)
    • Moment/torque
    • Thermal loads
    • Inertial loads (gravity, acceleration)
  2. Load Cases

    • Define all operational load cases
    • Include limit and ultimate factors
    • Combine per applicable standards
    • Document load derivation

Results Post-Processing

Stress Evaluation
  1. Stress Quantities

    • von Mises (ductile materials)
    • Principal stresses (fatigue, brittle)
    • Membrane + bending (shells)
    • Interlaminar (composites)
  2. Margin of Safety

    MS = (Allowable / Applied) - 1
    MS > 0 indicates positive margin
  3. Reporting

    • Maximum stress location and value
    • Stress contour plots
    • Deflection summary
    • Reaction forces verification

Process Integration

  • ME-006: Finite Element Analysis (FEA) Setup and Execution
  • ME-007: Stress and Deflection Analysis
  • ME-009: Nonlinear Structural Analysis

Input Schema

json
{
  "geometry": "CAD file path or description",
  "material": {
    "name": "string",
    "E": "number (Pa)",
    "nu": "number",
    "yield": "number (Pa)",
    "ultimate": "number (Pa)"
  },
  "loads": [
    {
      "type": "pressure|force|moment|thermal",
      "magnitude": "number",
      "location": "string",
      "direction": "array [x,y,z]"
    }
  ],
  "constraints": [
    {
      "type": "fixed|pinned|symmetry",
      "location": "string",
      "dof": "array"
    }
  ],
  "analysis_type": "static|modal|nonlinear",
  "output_requests": ["stress", "displacement", "reactions"]
}

Output Schema

json
{
  "analysis_results": {
    "max_stress": {
      "von_mises": "number (Pa)",
      "location": "string",
      "element_id": "number"
    },
    "max_displacement": {
      "magnitude": "number (m)",
      "location": "string",
      "node_id": "number"
    },
    "reaction_forces": {
      "total": "array [Fx, Fy, Fz, Mx, My, Mz]"
    }
  },
  "margin_of_safety": {
    "yield": "number",
    "ultimate": "number",
    "critical_location": "string"
  },
  "mesh_quality": {
    "element_count": "number",
    "worst_aspect_ratio": "number",
    "convergence_status": "string"
  }
}

Best Practices

  1. Always perform mesh convergence studies for critical analyses
  2. Verify reaction forces match applied loads
  3. Check for rigid body modes in modal analysis
  4. Use appropriate element formulations for contact
  5. Document all modeling assumptions and simplifications
  6. Compare results with hand calculations where possible

Integration Points

  • Connects with CAD Modeling for geometry import
  • Feeds into Fatigue Life Prediction for durability assessment
  • Supports Test Correlation for model validation
  • Integrates with Thermal Analysis for coupled problems

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Fea Structural AI skill do?

Deep integration with finite element analysis tools for structural simulation across static, dynamic, and nonlinear domains

Why use Fea Structural on TypingMind?

Because you install it once and use it with any model. Fea Structural is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fea Structural in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/reference/fea-structural. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fea Structural?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fea Structural?

As many as you like. As long as a model supports skills, you can use Fea Structural with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fea Structural AI skill free?

Yes. It is published on GitHub by Cai-aa under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇