MaterForge - Materials Formulation Engine with Python

A high-performance Python library for material simulation and analysis. MaterForge enables efficient modeling of pure metals and alloys through YAML configuration files, providing symbolic and numerical property evaluation for various material properties.

Table of Contents

• Key Features
• Installation
• Quick Sart
• YAML Configuration Format
• Documentation
• Contributing
• Known Limitations
• License
• Citation
• Support
• Acknowledgments

🚀 Key Features

• Modular Architecture: Clean separation with algorithms, parsing, and visualization modules
• Flexible Material Definition: Support for both pure metals and alloys
• YAML-Driven Configuration: Define materials using intuitive YAML files
• Temperature-Dependent Properties: Support for complex temperature-dependent material properties
• Symbolic Mathematics: Built on SymPy for precise mathematical expressions
• Piecewise Functions: Advanced piecewise function support with regression capabilities
• Property Inversion: Create inverse functions for energy density and other properties
• Visualization: Automatic plotting of material properties with customizable options
• Material Types: Support for both pure metals and alloys with appropriate phase transition temperatures
• Multiple Property Types: Support for constants, step functions, file-based data, key-value pairs, and computed properties
• Regression Analysis: Built-in piecewise linear fitting with configurable parameters

📦 Installation

Prerequisites

• Python 3.10 or higher
• Required dependencies: numpy, sympy, matplotlib, pandas, ruamel.yaml

Install using pip

pip install materforge

Development Installation

bash git clone https://i10git.cs.fau.de/rahil.doshi/materforge.git cd materforge pip install -e .[dev]

🏃 Quick Start

Basic Material Creation

```python import sympy as sp from materforge.parsing.api import create_material

Create a material with symbolic temperature

T = sp.Symbol('T') materialT = creatematerial('path/to/material.yaml', T)

Access properties

print(f"Heat capacity: {materialT.heatcapacity}")

Evaluate at specific temperature

tempvalue = 1500.0 # Kelvin densityattemp = materialT.evaluatepropertiesattemperature(tempvalue) print(f"Density at {tempvalue}K: {densityat_temp:.2f} kg/m³")

For symbolic expressions with automatic plotting

materialwithplot = creatematerial('steel.yaml', T, enableplotting=True) ```

Working with Piecewise Inverse Functions

```python from materforge.algorithms.piecewise_inverter import PiecewiseInverter

Create inverse energy density function: T = f_inv(E)

if hasattr(material, 'energydensity'): E = sp.Symbol('E') inversefunc = PiecewiseInverter.createenergydensity_inverse(material, 'E')

# Test round-trip accuracy
test_temp = 500.0
energy_val = float(material.energy_density.subs(T, test_temp))
recovered_temp = float(inverse_func.subs(E, energy_val))
print(f"Round-trip: T={test_temp} -> E={energy_val:.2e} -> T={recovered_temp:.2f}")

```

📋 YAML Configuration Format

Supported Property Types

• CONSTANT_VALUE: Simple numeric values
• FILE_IMPORT: Data loaded from CSV/Excel/text files
• TABULAR_DATA: Temperature and corresponding property value pairs
• STEP_FUNCTION: Discontinuous transitions
• PIECEWISE_EQUATION: Symbolic equations over temperature ranges
• COMPUTED_PROPERTY: Properties calculated from other properties

See the YAML schema documentation for detailed configuration options. YAML configuration examples can be found here: - Pure Metals - Alloys

📚 Documentation

Our documentation follows the Diátaxis framework with four distinct types:

Tutorials - Learning-oriented guides

• Getting Started with materforge
• Creating Your First Material Simulation ### How-to Guides - Problem-oriented instructions
• Defining Custom Material Properties
• Converting Between Energy Density and Temperature ### Reference - Information-oriented documentation
• API Reference
• YAML Configuration Schema ### Explanation - Understanding-oriented discussions
• Material Properties Concepts
• Design Philosophy

🤝 Contributing

Contributions are welcome! Please see our Contributing Guide for details on how to get started.

🐛 Known Limitations

• Piecewise Inverter: Currently supports only linear piecewise functions
• File Formats: Limited to CSV, Excel, and text files
• Memory Usage: Large datasets may require optimization for very high-resolution data
• Regression: Maximum 8 segments recommended for stability

📄 License

This project is licensed under the BSD 3-Clause License. See the LICENSE file for details.

📖 Citation

If you use MaterForge in your research, please cite it using the information in our CITATION.cff file.

📞 Support

• Author: Rahil Doshi
• Email: rahil.doshi@fau.de
• Project Homepage: materforge
• Bug Tracker: Issues

🙏 Acknowledgments

• Built with SymPy for symbolic mathematics
• Data handling powered by pandas
• Uses pwlf for piecewise linear fitting
• Visualization powered by Matplotlib
• YAML parsing with ruamel.yaml

MaterForge - Empowering material simulation with Python 🚀