Skip to content
Snippets Groups Projects
Select Git revision
  • master default protected
  • release/v0.1.0
  • development
3 results
Compare History
Rahil Doshi's avatar
Add temperature_array processing, update validation, add temperature range...
Rahil Doshi authored 
Add temperature_array processing, update validation, add temperature range validation, remove parsing for EDTA, update models, return tuple of alloy and temperature array with create_alloy_from_yaml
e81164a7
Name Last commit Last update
apps
docs
src/pymatlib
tests
.gitignore
.gitlab-ci.yml
.gitmodules
AUTHORS.txt
LICENSE
MANIFEST.in
README.md
pyproject.toml
requirements.txt
run_all_tests.py
setup.py
README.md

pymatlib

pymatlib

A high-performance Python library for material simulation and analysis with a focus on temperature-dependent properties. pymatlib enables efficient modeling of alloys, interpolation of material properties, and robust energy-temperature conversions for scientific and engineering applications.

Pipeline Status License

Table of Contents

Installation

To install pymatlib, use pip in a virtual environment:

pip install "git+https://i10git.cs.fau.de/rahil.doshi/pymatlib.git"

Quick Start

Creating and Using an Alloy

import pystencils as ps
from pystencilssfg import SourceFileGenerator
from pymatlib.core.typedefs import MaterialProperty
from pymatlib.core.yaml_parser import create_alloy_from_yaml

# Define a temperature field
with SourceFileGenerator() as sfg:
    u = ps.fields("u: float64[2D]", layout='fzyx')

    # Create an alloy from YAML configuration
    alloy = create_alloy_from_yaml("path/to/alloy.yaml", u.center())
    
    # Now you can use the alloy in your simulation
    # Get material properties at specific temperature
    temperature = 1500.0  # Kelvin
    thermal_diffusivity_value = alloy.thermal_diffusivity.evalf(u.center(), temperature)
    print(f"Thermal diffusivity at {temperature}K: {thermal_diffusivity_value} W/(m·K)")

See the tutorials for more detailed examples.

Documentation

Our documentation follows the Diátaxis framework with four distinct types:

Tutorials - Learning-oriented guides

How-to Guides - Problem-oriented instructions

Reference - Information-oriented documentation

Explanation - Understanding-oriented discussions

Key Features

Feature Description
Material Modeling Define complex alloys and their properties using simple YAML configurations
Temperature-dependent Properties Model how material properties change with temperature through various interpolation methods
Energy-Temperature Conversion Perform efficient bilateral conversion between energy density and temperature
High Performance Generate optimized C++ code for computationally intensive simulations
Extensible Design Easily add custom material properties and interpolation methods

Core Components

Alloy

A dataclass representing a material alloy with properties like:

  • Elements and composition
  • Solidus and liquidus temperatures
  • Temperature-dependent material properties

MaterialProperty

A dataclass for material properties that can be:

  • Defined as constant values
  • Specified as key-value pairs for interpolation
  • Loaded from external data files
  • Computed from other properties

InterpolationArrayContainer

Manages data for efficient interpolation between energy density and temperature using:

  • Binary search interpolation for non-uniform data
  • Double lookup interpolation for uniform data

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository
  2. Clone your fork locally: git clone https://github.com/yourusername/pymatlib.git
  3. Create a new branch: git checkout -b feature/your-feature
  4. Make your changes and commit: git commit -m "Add new feature"
  5. Push to the branch: git push origin feature/your-feature
  6. Open a pull request

License

This project is licensed under the GNU General Public License v3 (GPLv3). See the LICENSE file for details.

Contact