multiscale-homogenization | Computational Homogenization calculation in macroscopic

by MinhNguyenIKM Python Version: Current License: No License

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kandi X-RAY | multiscale-homogenization Summary

multiscale-homogenization is a Python library. multiscale-homogenization has no bugs, it has no vulnerabilities and it has low support. However multiscale-homogenization build file is not available. You can download it from GitHub.

Computational Homogenization calculation in macroscopic and microscopic structurures. The microscopic BVPs are solved by FFT method. The macroscopic BVPs are solved by FEM method (we use PyFEM framework based on the book Nonlinear Finite Element Analysis of Solids and Structures of Rene' de Borst et. al.)

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multiscale-homogenization has a low active ecosystem.

It has 1 star(s) with 3 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

multiscale-homogenization has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of multiscale-homogenization is current.

Quality

multiscale-homogenization has no bugs reported.

Security

multiscale-homogenization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

multiscale-homogenization does not have a standard license declared.

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Without a license, all rights are reserved, and you cannot use the library in your applications.

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multiscale-homogenization releases are not available. You will need to build from source code and install.

multiscale-homogenization has no build file. You will be need to create the build yourself to build the component from source.

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Install multiscale-homogenization

You can download it from GitHub.
You can use multiscale-homogenization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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