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HealStruct: Intelligent Self-Healing Infrastructure

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🌟 Overview

This project is an interdisciplinary initiative aimed at revolutionizing infrastructure maintenance and longevity through the use of self-healing materials.

🎯 Objectives

• 🏗 Design: Incorporate self-healing materials into architectural designs.
• 🧪 Material Science: Research and develop self-healing materials.
• 💻 Simulation: Use computational models to simulate stress and damage.
• 📊 Data Analysis: Utilize data to optimize the self-healing process.
• 🤖 Machine Learning: Implement AI to improve self-healing over time.
• 🚚 Supply Chain: Manage logistics for sourcing and implementing materials.

📊 Data Sources

📚 Material Science Research

• What: Academic papers, lab results, patents.
• Where: PubMed, IEEE Xplore, Google Scholar.
• How: Web scraping or manual collection.

🖥️ Simulation-Generated Data

• What: Stress, strain, and environmental condition data.
• Where: Generated from ANSYS, Rhino, and Grasshopper.
• How: Exported in CSV, JSON, or XML formats.

🛠 Technologies

• 📐 ANSYS: For simulations.
• 🦏 Rhino & Grasshopper: For design and optimization.
• 🐍 Python: For data analysis and machine learning.

📜 License

This project is under the MIT License. See LICENSE.md for details.

📚 Related Repositories

• HealStruct-Material_Science: For storing research papers, summaries, and any code related to material science.
• HealStruct-Structural_Health: Simulated structural health data and analysis for optimizing self-healing materials. ======= <<<<<<< HEAD

HealStruct-Structural_Health

Simulated structural health data and analysis for optimizing self-healing materials.

Structural_Health/main =======

HealStruct-Material_Science

For storing academic papers, lab results, patents, and any code related to material science research.

Material_Science/main main