Abaqus Optimization

CommunityPopular

Cai-aa

abaqus-optimization

Configure Tosca optimization. Use when user mentions design response, objective function, optimization constraint, or SIMP penalty. Base module for topology/shape optimization.

Overview

Publisher	Cai-aa
Repository	`CAE-Agent-Hub`
Skill name	`abaqus-optimization`
Stars	1K
Forks	130
Bundled files	3
License	MIT
Links	Skill source Repository

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.
3 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 Abaqus Optimization AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/optimization/abaqus-optimization
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/optimization/abaqus-optimization

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/optimization/abaqus-optimization .claude/skills/abaqus-optimization

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Abaqus Optimization 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 Abaqus Optimization 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 Abaqus Optimization 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.

Abaqus Optimization Skill

This skill configures optimization tasks in Abaqus. It's the base module - for complete workflows, route to /abaqus-topology-optimization or /abaqus-shape-optimization.

When to Use This Skill

Route here when user mentions:

"design response", "objective function", "optimization constraint"
"SIMP penalty", "material interpolation"
Low-level optimization setup (not complete workflows)

Route elsewhere:

Complete topology optimization workflow → /abaqus-topology-optimization
Complete shape optimization workflow → /abaqus-shape-optimization
Running the optimization → /abaqus-job

Prerequisites

Before optimization setup:

✅ Working static analysis that converges
✅ Appropriate mesh density
✅ Full Abaqus license with Tosca (not Learning Edition)

Workflow: Setting Up Optimization

Step 1: Understand User's Goal

Ask if unclear:

What to optimize? Weight, stiffness, frequency, stress?
What constraints? Volume limit, stress limit, displacement limit?
Manufacturing? Casting (draw direction), additive (min feature size)?

Step 2: Choose Objective-Constraint Pair

User Wants	Objective	Constraint
Lightest structure that's stiff enough	Minimize volume	Compliance ≤ limit
Stiffest structure at given weight	Minimize compliance	Volume ≤ 30%
Avoid resonance	Maximize frequency	Volume ≤ target
Reduce peak stress	Minimize max stress	Volume ≤ target

Most common: Minimize compliance with volume ≤ 30%

Step 3: Define Design Responses

Design responses are the quantities optimization tracks:

Response	When to Use
`VOLUME`	Almost always (for volume constraint)
`STRAIN_ENERGY`	Stiffness optimization
`EIGENFREQUENCY`	Vibration/resonance
`STRESS`	Stress-constrained design
`DISPLACEMENT`	Deflection limit

Step 4: Set Objective Function

The objective is what gets optimized:

MINIMIZE_MAXIMUM - For compliance, stress
MAXIMIZE_MINIMUM - For frequency

Step 5: Add Constraints

Constraints limit the design space:

RELATIVE_LESS_THAN_EQUAL - Percentage (volume ≤ 30%)
ABSOLUTE_LESS_THAN_EQUAL - Fixed value (stress ≤ 200 MPa)

Step 6: Consider Manufacturing

Constraint	Purpose
Min member size	Prevents thin, unmanufacturable features (3-5mm typical)
Symmetry	Mirrors design about plane
Draw direction	Enables mold/casting extraction
Overhang angle	For additive manufacturing

Step 7: Freeze Critical Regions

Always freeze:

BC application regions (mounting points)
Load application regions
Functional surfaces (mating interfaces)

Key Parameters

Parameter	Recommended	Notes
SIMP penalty	3.0	Higher = sharper boundaries
Volume fraction	0.3-0.4	Start conservative
Min member size	3× mesh size	Prevents checkerboard
Design cycles	30-50	More for complex geometry

Validation Checklist

After setup, verify:

Task created with correct region
At least one design response defined
Objective function set
Volume or other constraint defined
BC/load regions frozen
Manufacturing constraint if needed

Troubleshooting

Problem	Likely Cause	Solution
Checkerboard pattern	No min member size	Add `GeometricRestriction`
Disconnected result	Load path broken	Freeze more regions
Not converging	Constraint too tight	Relax volume fraction
"License error"	No Tosca module	Requires full Abaqus

Code Patterns

For actual API syntax and code examples, see:

API Quick Reference
Common Patterns
Troubleshooting Guide

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 Abaqus Optimization AI skill do?

Configure Tosca optimization. Use when user mentions design response, objective function, optimization constraint, or SIMP penalty. Base module for topology/shape optimization.

Why use Abaqus Optimization on TypingMind?

Because you install it once and use it with any model. Abaqus Optimization 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 Abaqus Optimization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/optimization/abaqus-optimization. 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 Abaqus Optimization?

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 Abaqus Optimization?

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

Is the Abaqus Optimization 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Abaqus Optimization Skill

When to Use This Skill

Prerequisites

Workflow: Setting Up Optimization

Step 1: Understand User's Goal

Step 2: Choose Objective-Constraint Pair

Step 3: Define Design Responses

Step 4: Set Objective Function

Step 5: Add Constraints

Step 6: Consider Manufacturing

Step 7: Freeze Critical Regions

Key Parameters

Validation Checklist

Troubleshooting

Code Patterns

Bundled files

Frequently asked questions

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