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# optframework: Optimization-Based Framework for Kernel Parameter Identification in Multi-Material Population Balance Models

![Logo](bild/logo_dpbe.png)

**Repo**: [On Github](https://github.com/adin888/PSD_opt)  (``https://github.com/adin888/PSD_opt``) \
**Authors**: Frank Rhein ([frank.rhein@kit.edu](mailto:frank.rhein@kit.edu)), Haoran Ji ([haoran.ji@kit.edu](mailto:haoran.ji@kit.edu)). \
**Affiliation**: Karlsruhe Institute of Technology (KIT), Institute of Mechanical Process Engineering and Mechanics

This project provides **Python-based solvers and optimizers** for the **Population Balance Equation (PBE)**.  

Depending on the application, users can choose the most suitable solver to predict the evolution of particle systems.  
For cases with experimental data, the optimization framework can be used to determine **kernel parameters** that best match experimental conditions, improving prediction accuracy.

- See {doc}`Quick Start <quickstart>` for simple usage examples of the solvers.  
- Visit {doc}`Overview <overview/overview>` to understand the overall project structure.  
- For a full list of class attributes and their meanings, refer to {doc}`Attributes <attributes>`.  
  
The documentation also includes two advanced guides:  

- {doc}`Adding a Custom Kernel Model <advanced_guide/custom_kernel_model>`  
- {doc}`Adapting a Custom Solver to the Optimizer <advanced_guide/custom_optimizer>`  


```{toctree}
:caption: 'Contents:'
:maxdepth: 6

quickstart
overview/overview
attributes
advanced_guide/custom_kernel_model
advanced_guide/custom_optimizer
references
api/optframework

```

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