PModels :: Predictive models for polymer systems
- PModels can predict properties of polymer blends and composites.
- Input: properties of the components + composition + additional parameters.
- Output: property of the final system (i.e. of the polymer blend or composite).
Principle
>>> # Standard import of PModels package
>>> import pmodels as pm
>>>
>>> # Estimate arbitrary property P of a polymer blend
>>> # (P1,P2) = properties of components, v2 = vol.fraction of component 2
>>> P = pm.lin.P(P1=1, P2=3, v2=0.5)
>>>
>>> # Estimate elastic modulus, E, and yield stress, Y, of a polymer blend
>>> # (E1,E2 and Y1,Y2) = props of the components, v2 = vol.fract., A = adhesion
>>> E = pm.ebm.E(E1=1, E2=3, v2=0.5)
>>> Y = pm.ebm.Y(Y1=20, Y2=100, v2=0.5, A=1)
Installation
- Requirement: Python with sci-modules = numpy, matplotlib, scipy, pandas
pip install pmodels= PModels package itself (uses all packages above)
Quick start
- Worked example = basic calculations with PModels.
- DropBox folder with more examples, including test data.
Documentation, help and examples
- PyPI repository - the stable version to install.
- GitHub repository - the current version under development.
- GitHub Pages with examples and complete package documentation.
Versions of PModels
- Version 0.1 = key calculations
- Version 0.2 = basic docstrings added
- Version 0.3 = improved init file = simple API
- Version 0.4 = standard docstrings, improved code, deployed in GitHub
Metadata
Release files for pmodels 0.4
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