FiPy is a Python-based software tool that solves partial differential equations using a finite volume method. It is used for modeling physical systems and analyzing numerical simulations.
FiPy is a powerful and freely available software that serves as an object-oriented, partial differential equation (PDE) solver. This software is based on a standard finite volume (FV) approach and has been developed in the Metallurgy Division and Center for Theoretical and Computational Materials Science (CTCMS), in the Materials Science and Engineering Laboratory (MSEL) at the National Institute of Standards and Technology (NIST).
The solution of coupled sets of PDEs is ubiquitous in numerical simulation science problems, and there are numerous PDE solvers utilizing different languages and numerical approaches. However, many of these solvers are proprietary, expensive, and difficult to customize, causing scientists to expend considerable resources developing limited tools for specific problems.
FiPy offers an extensible and powerful alternative to such solvers using the FV method and Python. As a result, scientists are given the ability to customize their numerical simulations freely at no cost. Python provides the advantage of an existing suite of tools for sparse matrices, array calculations, and data rendering, among others.
The FiPy framework includes terms for transient diffusion, convection, and standard sources, enabling the solution of arbitrary combinations of coupled elliptic, hyperbolic, and parabolic PDEs. Users can model phase field treatments of polycrystalline, dendritic, and electrochemical phase transformations, as well as employ a level set treatment of the electrodeposition process.
In summary, using FiPy for numerical simulation will save users a considerable amount of time and money, while providing them with a powerful and flexible tool for solving a wide range of scientific problems. FiPy requires Python, NumPy, matplotlib, and PySparse.
The solution of coupled sets of PDEs is ubiquitous in numerical simulation science problems, and there are numerous PDE solvers utilizing different languages and numerical approaches. However, many of these solvers are proprietary, expensive, and difficult to customize, causing scientists to expend considerable resources developing limited tools for specific problems.
FiPy offers an extensible and powerful alternative to such solvers using the FV method and Python. As a result, scientists are given the ability to customize their numerical simulations freely at no cost. Python provides the advantage of an existing suite of tools for sparse matrices, array calculations, and data rendering, among others.
The FiPy framework includes terms for transient diffusion, convection, and standard sources, enabling the solution of arbitrary combinations of coupled elliptic, hyperbolic, and parabolic PDEs. Users can model phase field treatments of polycrystalline, dendritic, and electrochemical phase transformations, as well as employ a level set treatment of the electrodeposition process.
In summary, using FiPy for numerical simulation will save users a considerable amount of time and money, while providing them with a powerful and flexible tool for solving a wide range of scientific problems. FiPy requires Python, NumPy, matplotlib, and PySparse.
What's New
Version 1.1: N/A