orcaflex-mooring-iteration-initial-model

Sub-skill of orcaflex-mooring-iteration: Initial Model (+2).

5 stars

Best use case

orcaflex-mooring-iteration-initial-model is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of orcaflex-mooring-iteration: Initial Model (+2).

Teams using orcaflex-mooring-iteration-initial-model should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/initial-model/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/engineering/marine-offshore/orcaflex-mooring-iteration/initial-model/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/initial-model/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How orcaflex-mooring-iteration-initial-model Compares

Feature / Agentorcaflex-mooring-iteration-initial-modelStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Sub-skill of orcaflex-mooring-iteration: Initial Model (+2).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Initial Model (+2)

## Initial Model


1. **Start close to target** - Begin with reasonable pretension estimate
2. **Verify static convergence** - Model must converge before iteration
3. **Check line connectivity** - Ensure proper vessel/anchor connections
4. **Reasonable initial lengths** - Avoid extreme configurations


## Configuration


1. **Start with default damping** (0.7) - Reduce if oscillating
2. **Use appropriate method** - Scipy for most cases
3. **Set realistic tolerances** - 1% is typical for design
4. **Limit iterations** - 50-100 usually sufficient


## Troubleshooting


1. **No convergence** - Reduce damping factor
2. **Oscillating** - Increase damping, check Jacobian
3. **Slow convergence** - Check EA values, initial guess
4. **Invalid lengths** - Set min/max length limits

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