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Curing Temperature

CommunityPopular
Cai-aa
curing-temperature

Define temperature fields for composite curing simulation. Invoke when user needs temperature initialization, temperature changes, or thermal fields for curing steps.

Overview

PublisherCai-aa
RepositoryCAE-Agent-Hub
Skill namecuring-temperature
Stars
1K
Forks
130
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Curing Temperature 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/composite-curing-simulation/setup/curing-temperature
  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/composite-curing-simulation/setup/curing-temperature .claude/skills/curing-temperature
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Curing Temperature 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 Curing Temperature 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 Curing Temperature 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.

Curing Temperature Setup

Description

Define temperature fields for composite curing simulation. Invoke when user needs temperature initialization, temperature changes, or thermal fields for curing steps.

Initial Conditions

The initial temperature is set for all nodes in both instances (tool-1 and P8-1) at the start of the analysis:

*Initial Conditions, type=TEMPERATURE
_PickedSet333, 25.
  • _PickedSet333: Node set covering ALL nodes in both instances (tool-1 and P8-1).
  • Initial temperature: 25°C (room temperature).

_PickedSet333 Definition

The node set _PickedSet333 is defined using generated node ranges for both instances:

*Nset, nset=_PickedSet333, internal, instance=tool-1, generate
    1,  2691,     1
*Nset, nset=_PickedSet333, internal, instance=P8-1, generate
    1,  5445,     1    # (or 3025 for 4-ply model)
  • tool-1: Nodes 1 to 2691 (all tool nodes).
  • P8-1: Nodes 1 to 5445 (all composite nodes for 8-ply model) or 1 to 3025 (for 4-ply model).
  • The generate option creates a sequential node set from the start to end label with the given increment.

Temperature in Each Step

The temperature is updated in each step of the curing cycle using the *Temperature predefined field. The temperature drives the UMAT material response (curing kinetics and glass transition).

vis Step (Viscous State)

*Temperature
_PickedSet333, 150.
  • Temperature changes from 25°C to 150°C.
  • At 150°C, the resin is in a low-viscosity state, allowing flow and compaction.
  • The UMAT subroutine recognizes this as the viscous state.

rub Step (Rubbery State)

*Temperature
_PickedSet333, 180.
  • Temperature changes from 150°C to 180°C.
  • At 180°C, the cure reaction progresses and the material transitions to a rubbery state.
  • The UMAT subroutine recognizes this as the rubbery state.

glassy Step (Glassy State)

*Temperature
_PickedSet333, 25.
  • Temperature changes from 180°C to 25°C (cooling to room temperature).
  • As the material cools below its glass transition temperature (Tg), it transitions to a glassy state.
  • The UMAT subroutine recognizes this as the glassy state.

sp Step (Springback)

*Temperature
_PickedSet333, 25.
  • Temperature maintained at 25°C.
  • The tool is removed (via Model Change) and the composite undergoes springback at room temperature.

Temperature Schedule Summary

StepStart Temp (°C)End Temp (°C)Material State
(initial)2525-
vis25150Viscous
rub150180Rubbery
glassy18025Glassy
sp2525Glassy (springback)

Temperature as a Predefined Field

Temperature is a predefined field in Abaqus, applied to all nodes in the model:

  • The *Temperature keyword assigns a uniform temperature to all nodes in the specified set.
  • The temperature is ramped linearly from the previous step's value to the new value over the step time.
  • The UMAT subroutine receives the current temperature at each integration point and uses it to:
    • Determine the material state (viscous, rubbery, or glassy).
    • Compute the degree of cure (cure kinetics).
    • Update the glass transition temperature (Tg).
    • Calculate thermal strains and cure shrinkage strains.

UMAT and Temperature Interaction

The UMAT subroutine uses temperature as the primary driver for material state transitions:

  1. Viscous state (high temperature, ~150°C): Low resin viscosity, resin flow and compaction occur. The material is soft and deformable.
  2. Rubbery state (intermediate temperature, ~180°C): Cure reaction advances, cross-linking increases. The material becomes rubbery and begins to develop stiffness.
  3. Glassy state (low temperature, ~25°C): Below Tg, the material is rigid and glassy. Residual stresses are locked in during this phase.

The state variables (SDV1-SDV4) are updated based on the temperature history, tracking:

  • Degree of cure progression
  • Glass transition temperature evolution
  • Current material state
  • Accumulated cure strain

Notes

  • The temperature values (25, 150, 180, 25°C) represent a typical three-step curing cycle. Adjust based on the specific resin system and cure schedule.
  • The temperature is applied uniformly to all nodes. For spatially varying temperature fields, use a field variable or mapped temperature data.
  • The _PickedSet333 node set must include all nodes in both instances to ensure uniform temperature application.
  • When changing the mesh (e.g., from 8-ply to 4-ply), update the node range for P8-1 in _PickedSet333 accordingly (5445 for 8-ply, 3025 for 4-ply).
  • The temperature ramp rate is controlled by the step time. Ensure the step time is sufficient for the cure reaction to complete (especially in the rub step).

Frequently asked questions

What does the Curing Temperature AI skill do?

Define temperature fields for composite curing simulation. Invoke when user needs temperature initialization, temperature changes, or thermal fields for curing steps.

Why use Curing Temperature on TypingMind?

Because you install it once and use it with any model. Curing Temperature 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 Curing Temperature in TypingMind?

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

Which AI models can use Curing Temperature?

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 Curing Temperature?

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

Is the Curing Temperature 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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