# PyPEEC - 3D Quasi-Magnetostatic Solver
---
* **Website: [pypeec.otvam.ch](https://pypeec.otvam.ch)**
* **Repository: [github.com/otvam/pypeec](https://github.com/otvam/pypeec)**
* **Conda: [anaconda.org/conda-forge/pypeec](https://anaconda.org/conda-forge/pypeec)**
* **PyPI: [pypi.org/project/pypeec](https://pypi.org/project/pypeec)**
---
## Summary
**PyPEEC** is a **3D quasi-magnetostatic PEEC solver** developed at **Dartmouth College** within the Power Management Integration Center (PMIC).
PyPEEC is a **fast solver** (FFT and GPU accelerated) that can simulate a large variety of **magnetic components** (inductors, transformers, chokes, IPT coils, busbars, etc.).
The tool contains a **mesher** (STL, PNG, and GERBER formats), a **solver** (static and frequency domain), and **advanced plotting** capabilities.
The code is written in **Python** and is fully **open source**!
## Capabilities
**PyPEEC** features the following **characteristics**:
* **PEEC method** with **FFT acceleration**
* Representation of the **geometry** with **3D voxels**
* **Multithreading** and **GPU acceleration** are available
* **Fast** with **moderate memory** requirements
* Import the **geometry** from **STL**, **PNG**, and **GERBER** files
* Draw the **geometry** with stacked 2D **vector shapes** or **voxel indices**
* **Pure Python** and **open source** implementation
* Advanced **plotting** capabilities
* Can be used from the **command line**
* Can be used with **Jupyter notebooks**
* Compatible with **ParaView visualizations**
**PyPEEC** solves the following **3D quasi-magnetostatic problems**:
* Frequency domain solution (DC and AC)
* Conductive and magnetic domains (ideal or lossy)
* Isotropic, anisotropic, lumped, and distributed materials
* Connection of current and voltage sources
* Extraction of the loss and energy densities
* Extraction of the current density, flux density, and potential
* Extraction of the terminal voltage, current, and power
* Computation of the free-space magnetic field
**PyPEEC** has the following **limitations**:
* No capacitive effects
* No dielectric domains
* No advanced boundaries conditions
* No model order reduction techniques
* Limited to voxel geometries
The **PyPEEC** package contains the following **tools**:
* **mesher** - create a 3D voxel structure from STL or PNG files
* **viewer** - visualization of the 3D voxel structure
* **solver** - solver for the magnetic field problem
* **plotter** - visualization of the problem solution
## Warning
The geometry is meshed with a **regular voxel structure** (uniform grid).
Some geometries/problems are not suited for voxel structures (inefficient meshing).
For such cases, PyPEEC can be very slow and consume a lot of memory.
## Project Links
* **PyPEEC**
* [Website](https://pypeec.otvam.ch)
* [Repository](https://github.com/otvam/pypeec)
* [Issues](https://github.com/otvam/pypeec/issues)
* **Releases**
* [PyPI](https://pypi.org/project/pypeec)
* [Conda](https://anaconda.org/conda-forge/pypeec)
* [GitHub](https://github.com/otvam/pypeec/releases)
* **Documentation**
* [Installation](https://pypeec.otvam.ch/content/install.html)
* [Tutorial](https://pypeec.otvam.ch/content/tutorial.html)
* [Examples](https://pypeec.otvam.ch/content/examples.html)
* [Gallery](https://pypeec.otvam.ch/content/gallery.html)
## Author
* Name: **Thomas Guillod**
* Affiliation: Dartmouth College
* Email: guillod@otvam.ch
* Website: https://otvam.ch
## Credits
PyPEEC was created at **Dartmouth College** by the research group of **Prof. Sullivan**:
* Dartmouth College, NH, USA: https://dartmouth.edu
* Dartmouth Engineering: https://engineering.dartmouth.edu
* NSF/PMIC: https://pmic.engineering.dartmouth.edu
The FFT-accelerated PEEC method with voxels has been first described and implemented in:
* Torchio, R., IEEE TPEL, 10.1109/TPEL.2021.3092431, 2022
* Torchio, R., https://github.com/UniPD-DII-ETCOMP/FFT-PEEC
## Copyright
(c) 2023-2024 / Thomas Guillod / Dartmouth College
This Source Code Form is subject to the terms of the Mozilla Public
License, v. 2.0. If a copy of the MPL was not distributed with this
file, You can obtain one at http://mozilla.org/MPL/2.0/.
In order to facilitate the redistribution, this source code is
multi-licensed under the following additional licenses:
LGPLv2, LGPLv3, GPLv2, and GPLv3.
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"description": "# PyPEEC - 3D Quasi-Magnetostatic Solver\n\n---\n* **Website: [pypeec.otvam.ch](https://pypeec.otvam.ch)**\n* **Repository: [github.com/otvam/pypeec](https://github.com/otvam/pypeec)**\n* **Conda: [anaconda.org/conda-forge/pypeec](https://anaconda.org/conda-forge/pypeec)**\n* **PyPI: [pypi.org/project/pypeec](https://pypi.org/project/pypeec)**\n---\n\n## Summary\n\n**PyPEEC** is a **3D quasi-magnetostatic PEEC solver** developed at **Dartmouth College** within the Power Management Integration Center (PMIC). \nPyPEEC is a **fast solver** (FFT and GPU accelerated) that can simulate a large variety of **magnetic components** (inductors, transformers, chokes, IPT coils, busbars, etc.). \nThe tool contains a **mesher** (STL, PNG, and GERBER formats), a **solver** (static and frequency domain), and **advanced plotting** capabilities.\nThe code is written in **Python** and is fully **open source**!\n\n## Capabilities\n\n**PyPEEC** features the following **characteristics**:\n\n* **PEEC method** with **FFT acceleration**\n* Representation of the **geometry** with **3D voxels**\n* **Multithreading** and **GPU acceleration** are available\n* **Fast** with **moderate memory** requirements\n* Import the **geometry** from **STL**, **PNG**, and **GERBER** files\n* Draw the **geometry** with stacked 2D **vector shapes** or **voxel indices**\n* **Pure Python** and **open source** implementation\n* Advanced **plotting** capabilities\n* Can be used from the **command line**\n* Can be used with **Jupyter notebooks**\n* Compatible with **ParaView visualizations**\n\n**PyPEEC** solves the following **3D quasi-magnetostatic problems**:\n\n* Frequency domain solution (DC and AC)\n* Conductive and magnetic domains (ideal or lossy)\n* Isotropic, anisotropic, lumped, and distributed materials\n* Connection of current and voltage sources\n* Extraction of the loss and energy densities\n* Extraction of the current density, flux density, and potential\n* Extraction of the terminal voltage, current, and power\n* Computation of the free-space magnetic field \n\n**PyPEEC** has the following **limitations**:\n\n* No capacitive effects\n* No dielectric domains\n* No advanced boundaries conditions\n* No model order reduction techniques\n* Limited to voxel geometries\n\nThe **PyPEEC** package contains the following **tools**:\n\n* **mesher** - create a 3D voxel structure from STL or PNG files\n* **viewer** - visualization of the 3D voxel structure\n* **solver** - solver for the magnetic field problem\n* **plotter** - visualization of the problem solution\n\n## Warning\n\nThe geometry is meshed with a **regular voxel structure** (uniform grid).\nSome geometries/problems are not suited for voxel structures (inefficient meshing).\nFor such cases, PyPEEC can be very slow and consume a lot of memory.\n\n## Project Links\n\n* **PyPEEC**\n\n * [Website](https://pypeec.otvam.ch)\n * [Repository](https://github.com/otvam/pypeec)\n * [Issues](https://github.com/otvam/pypeec/issues)\n\n* **Releases**\n\n * [PyPI](https://pypi.org/project/pypeec)\n * [Conda](https://anaconda.org/conda-forge/pypeec)\n * [GitHub](https://github.com/otvam/pypeec/releases)\n\n* **Documentation**\n\n * [Installation](https://pypeec.otvam.ch/content/install.html)\n * [Tutorial](https://pypeec.otvam.ch/content/tutorial.html)\n * [Examples](https://pypeec.otvam.ch/content/examples.html)\n * [Gallery](https://pypeec.otvam.ch/content/gallery.html)\n\n## Author\n\n* Name: **Thomas Guillod**\n* Affiliation: Dartmouth College\n* Email: guillod@otvam.ch\n* Website: https://otvam.ch\n\n## Credits\n\nPyPEEC was created at **Dartmouth College** by the research group of **Prof. Sullivan**:\n\n* Dartmouth College, NH, USA: https://dartmouth.edu\n* Dartmouth Engineering: https://engineering.dartmouth.edu\n* NSF/PMIC: https://pmic.engineering.dartmouth.edu\n\nThe FFT-accelerated PEEC method with voxels has been first described and implemented in:\n\n* Torchio, R., IEEE TPEL, 10.1109/TPEL.2021.3092431, 2022\n* Torchio, R., https://github.com/UniPD-DII-ETCOMP/FFT-PEEC\n\n## Copyright\n\n(c) 2023-2024 / Thomas Guillod / Dartmouth College\n\nThis Source Code Form is subject to the terms of the Mozilla Public\nLicense, v. 2.0. If a copy of the MPL was not distributed with this\nfile, You can obtain one at http://mozilla.org/MPL/2.0/.\n\nIn order to facilitate the redistribution, this source code is\nmulti-licensed under the following additional licenses:\nLGPLv2, LGPLv3, GPLv2, and GPLv3.\n\n---\n\n",
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