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hierarchical-topopt

Automate 2D minimum-compliance topology optimization and export STL geometry.

38|7|Updated Jun 21, 2026
Search Tags:#simulation#STL export#topology optimization#boundary conditions#2D structure
One-click install
npx skills add https://github.com/lamm-mit/ScienceSkills --skill hierarchical-topopt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hierarchical-topopt
Source: https://github.com/lamm-mit/ScienceSkills/tree/main/skills/hierarchical-topopt
Command: npx skills add https://github.com/lamm-mit/ScienceSkills --skill hierarchical-topopt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, numpy, scipy, pyparaview, pandas, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the process of 2D topology optimization for structures, providing the ability to flexibly define boundary conditions and export optimized geometry as STL files.

Core Features & Use Cases

  • Flexible Boundary Conditions: Customize boundary conditions for different loading and support configurations.
  • STL Export: Generate STL files of the optimized structure for further processing.
  • Use Case: Imagine you are designing a bridge. Use this Skill to optimize its structure for minimal compliance, considering various loading conditions and support types.

Quick Start

Run the hierarchical-topopt skill to optimize a bridge structure by providing boundary conditions and loading details.

Frequently Asked Questions about hierarchical-topopt

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform 2D topology optimization and export the result to STL?▼

You can perform 2D topology optimization by providing custom boundary conditions and loading details to the simulation, which then processes the structure and exports the optimized geometry as an STL file.

Can I customize boundary conditions for 2D structural optimization?▼

Yes, you can flexibly customize boundary conditions for 2D structural optimization, allowing you to define various loading and support configurations to accurately simulate different constraints applied to the structure.

Do I need scipy and matplotlib installed to run 2D minimum-compliance topology optimization?▼

Yes, scipy and matplotlib are required dependencies for running 2D minimum-compliance topology optimization. You also need numpy and pandas installed to process boundary conditions, run the simulation, and generate geometry outputs.

What is the best way to optimize a 2D bridge structure for minimal compliance?▼

The best way to optimize a 2D bridge structure for minimal compliance is to use an automated topology optimization workflow where you input specific loading conditions and supports, allowing the simulation to iteratively calculate the optimal geometry.

Are there limitations when exporting 2D topology optimization results as STL files?▼

A key limitation is that the STL export is restricted to 2D optimized geometry. The simulation is designed specifically for 2D minimum-compliance problems, meaning it does not natively handle 3D structural optimization or output 3D meshes.

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