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OpenIFEM: A High Performance Modular Open-Source Software of the Immersed Finite Element Method for Fluid-Structure Interactions
Author(s) -
Jie Cheng,
Feimi Yu,
Lucy T. Zhang
Publication year - 2019
Publication title -
computer modeling in engineering and sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.341
H-Index - 60
eISSN - 1526-1506
pISSN - 1526-1492
DOI - 10.32604/cmes.2019.04318
Subject(s) - computer science , modular design , software , fluid–structure interaction , finite element method , computational science , extensibility , discretization , compressibility , set (abstract data type) , supercomputer , modularity (biology) , open source , distributed computing , parallel computing , operating system , programming language , engineering , structural engineering , mathematics , mathematical analysis , biology , genetics , aerospace engineering
We present a high performance modularly-built open-source software - OpenIFEM. OpenIFEM is a C++ implementation of the modified immersed finite element method (mIFEM) to solve fluid-structure interaction (FSI) problems. This software is modularly built to perform multiple tasks including fluid dynamics (incompressible and slightly compressible fluid models), linear and nonlinear solid mechanics, and fully coupled fluid-structure interactions. Most of open-source software packages are restricted to certain discretization methods; some are under-tested, under-documented, and lack modularity as well as extensibility. OpenIFEM is designed and built to include a set of generic classes for users to adapt so that any fluid and solid solvers can be coupled through the FSI algorithm. In addition, the package utilizes well-developed and tested libraries. It also comes with standard test cases that serve as software and algorithm validation. The software can be built on cross-platform, i.e., Linux, Windows, and Mac OS, using CMake. Efficient parallelization is also implemented for high-performance computing for large-sized problems. OpenIFEM is documented using Doxygen and publicly available to download on GitHub. It is expected to benefit the future development of FSI algorithms and be applied to a variety of FSI applications.

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