orcaflex-mooring-iteration-scipy-method
Sub-skill of orcaflex-mooring-iteration: Scipy Method (+2).
Best use case
orcaflex-mooring-iteration-scipy-method is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcaflex-mooring-iteration: Scipy Method (+2).
Teams using orcaflex-mooring-iteration-scipy-method 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scipy-method/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-mooring-iteration-scipy-method Compares
| Feature / Agent | orcaflex-mooring-iteration-scipy-method | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of orcaflex-mooring-iteration: Scipy Method (+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
# Scipy Method (+2) ## Scipy Method ``` 1. Define objective function: residual = current_tension - target_tension 2. Optimization variables: line lengths 3. scipy.optimize.fsolve minimizes residuals 4. Length changes distributed across sections proportionally ``` ## Newton-Raphson Method ``` 1. Calculate Jacobian: J[i,j] = ∂T_i/∂L_j 2. Calculate residuals: r_i = T_current_i - T_target_i 3. Solve: J × ΔL = -r 4. Update: L_new = L_old + damping × ΔL 5. Repeat until convergence ``` ## EA-Based Method ``` 1. From catenary theory: ΔL ≈ ΔT × L / EA 2. Calculate tension error: ΔT = T_current - T_target 3. Calculate length change: ΔL = ΔT × L / EA 4. Apply with damping 5. Repeat until convergence ```
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