/svFSI

A multi-physics finite element solver for patient-specific blood flow simulation including fluid-structure interaction and cardiac electrophysiology

Primary LanguageFortranOtherNOASSERTION

Introduction

svFSI is a multi-physics finite element solver designed for computational modeling of the cardiovascular system. It is a major component of the ongoing SimVascular SimCardio project that aims to provide the complete pipeline for cardiac modeling, from image segmentation to computational modeling.

Some of the unique capabilities of svFSI include modeling cardiac electrophysiology, biological tissue mechanics, blood flow, and large deformation fluid-structure interaction (FSI). svFSI also offers a wide choice of boundary conditions for performing patient-specific modeling of cardiovascular biomechanics. The code is parallelized using message-passing-interface (MPI) and offers multiple options to choose a linear solver and preconditioner. svFSI can be used as part of the SimVascular software or can be used as a stand-alone solver. It is distributed under a MIT-like open source license.

Binary and Container

Precompiled binaries for Ubuntu and MacOS are available for download from SimTK.

Instructions to build and run svFSI in Docker container are provided here.

Dependence

The following packages are required to build and use svFSI.

  • cmake
  • cmake-curses-gui
  • cmake-gui
  • gcc (version>=4.8.5) with gfortran
  • openmpi or mpich
  • blas & lapack
  • trilinos (optional)

On Ubuntu, most of the dependencies can be installed using apt install. On macOS, the dependencies may be installed using brew. Apart from GNU compilers, svFSI can also be built with Intel oneAPI Toolkits. For more details, please refer to INSTALL.md and INSTALL-DEPS.md.

Quick Build from Source

Users are recommended to build from the source code to access the most recent features and bug fixes. Instructions for a quick build are provided here for a Linux/Mac OS system.

  1. Clone or download the current repository.

  2. Create a build directory

    cd svFSI && mkdir build && cd build

  3. Initiate the CMake terminal interface to generate makefiles.

    ccmake ..

  4. This will automatically search for compilers. Follow instructions if necessary. Press “c” to configure repeatedly until CMake parameters no longer change and CMake presents the option “g” to generate. Press “g” to create makefiles and exit. Run make in the build directory:

    make

    A successful build will generate a solver binary called svFSI in the following directory build/svFSI-build/bin.

    For more advanced users, please refer INSTALL.md for detailed platform-specific instructions to install svFSI.

Build With Trilinos

svFSI also supports compilation with Trilinos. Users can build Trilinos locally following its online documentation.

The recommended Trilinos third-party libraries (TPLs) include Boost, BLAS, HDF5, HYPRE, LAPACK, MPI, and MUMPS. The required Trilinos packages are Amesos, AztecOO, Epetra, EpetraEXT, Ifpack, ML, MueLU, ROL, Sacado, Teuchos, and Zoltan.

To enable Trilinos in svFSI, users need to turn on the option SV_USE_TRILINOS located in the file Code/CMake/SimVascularOptions.cmake as,

option(SV_USE_TRILINOS "Use Trilinos Library with svFSI" ON)

In most cases, users can proceed to build svFSI following the Quick Build, and CMake should be able to locate Trilinos automatically through find_package. In case the automatic way fails, users can also specify the path to Trilinos through ccmake -DCMAKE_PREFIX_PATH:PATH="<Path_to_Trilinos>/lib/cmake/Trilinos;<Path_to_any_other_package>;".

For more detailed instructions, please refer to INSTALL.md.

Run Simulation

svFSI requires a plain-text input file to specify simulation parameters. The syntax of the input file can be found here.

A master template is provided in the current repository, svFSI_master.inp. Users are also recommended to go through the input files in the examples and modify them for their needs.

An MPI-based run can be initiated through

mpiexec -np <number of MPI processes>  <Path to Build>/svFSI-build/bin/svFSI <Path to input file>

Features

svFSI provides the capability to model a variety of physics including unsteady diffusion, linear and nonlinear elastodynamics, convective heat transfer, fluid flows, fluid-structure-interaction (FSI), and cardiac electrophysiology. As the code is modular, the users are provided with a choice to couple these physics depending on their needs. We strongly recommend users to browse through the examples provided in the GitHub repository svFSI-Tests to get a detailed insight into the capability of the code. Also, most of the examples contain established simulation results, which users can use to verify the functionality of svFSI. Here is a list of the main features of svFSI.

Physics Solved Documentation/Tutorial Examples
Fluid Webpage pipe flow with RCR BC;
dye transportation;
GenBC/cplBC;
Non-Newtonian flow
Structure Webpage; YouTube struct:
block compression;
passive inflation of LV model
ustruct:
block compression;
tension of arterial strip;
active inflation of LV model
Electrophysiology Webpage; YouTube Aliev-Panfilov model;
ten-Tusscher-Panfilov model;
Bueno-Orovio-Cherry-Fenton model;
Purkinje network
FSI Webpage; YouTube ALE:
2D heart valve;
2D flag behind a block;
pressure pulse inside aorta
CMM:
pipe flow with RCR BC;
vein graft

Below, we provide a list of the available choice of constitutive models for different types of equations being solved. Users are also encouraged to implement new constitutive models. Users may use global search tools such as grep to locate the implementations of the available constitutive models in the code using the abbreviated names below.

Abbreviation refers to the variable name in the source code; Full name refers to the generic name of the model; Input keyword refers to the phrase in the input file that can invoke such model.

  1. Available isochoric constitutive models for the structure equation

    Abbreviation Full name Input keyword
    stIso_stVK Saint Venant-Kirchhoff "stVK", "stVenantKirchhoff"
    stIso_mStVK modified Saint Venant-Kirchhoff "m-stVK", "modified-stVK", "modified-stVenantKirchhoff"
    stIso_nHook Neo-Hookean model "nHK", "nHK91", "neoHookean", "neoHookeanSimo91"
    stIso_MR Mooney-Rivlin model "MR", "Mooney-Rivlin"
    stIso_HGO_d Holzapfel-Gasser-Ogden (decoupled) "HGO", "HGO-d", HGO-decoupled"
    stIso_HGO_ma HGO model (modified anisotropy) "HGO-ma", "HGO-modified"
    stIso_Gucci Guccione model "Guccione", "Gucci"
    stIso_HO_d Holzapfel-Ogden model (decoupled) "HO", "Holzapfel", "HO-decoupled", "HO-d"
    stIso_HO_ma HO model (modified anisotropy) "HO-ma", "HO-modified"

  2. Available volumetric constitutive models for the structure equation

    Abbreviation Full name Input keyword
    stVol_Quad Quadratic model "quad", "Quad", "quadratic", "Quadratic"
    stVol_ST91 Simo-Taylor91 model "ST91", "Simo-Taylor91"
    stVol_M94 Miehe94 model "M94", "Miehe94"

  3. Available constitutive models for the fluid equation

    Abbreviation Full name Input keyword
    viscType_Const Constant viscosity (Newtonian model) "Constant", "Const", "Newtonian"
    viscType_CY Carreau-Yasuda non-Newtonian model "Carreau-Yasuda", "CY"
    viscType_Cass Cassons non-Newtonian model "Cassons", "Cass"

  4. Available cardiac electrophysiology models

    Abbreviation Full name Input keyword
    cepModel_AP Aliev-Panfilov model "AP", "Aliev-Panfilov"
    cepModel_BO Bueno-Orovio-Cherry-Fenton model "BO", "Bueno-Orovio"
    cepModel_FN Fitzhugh-Nagumo model "FN", "Fitzhugh-Nagumo"
    cepModel_TTP tenTusscher-Panfilov model "TTP", "tenTusscher-Panfilov"

Documentation

More details can be found on the svFSI page, and direct links to the documentation for different functionalities are provided here:

Tutorial

Pre/Post Processing Tool

We are also maintaining a collection of useful pre and post processing tools that are compatible with svFSI: https://github.com/SimVascular/svFSI-Tools

Contribute to svFSI

We welcome and appreciate all types of contributions to svFSI.

  • Seek support, suggest new features or report bugs, please contact us through GitHub Issues or SimTK forum.
  • Contribute your code to svFSI, please submit a pull request through GitHub.
  • Share your novel applications of svFSI with the community, please consider contribute your case to svFSI-Tests.

Citation

You can cite the software using the following:

@article{svfsi2022,
  title={svFSI: a multiphysics package for integrated cardiac modeling},
  author={Zhu, Chi and Vedula, Vijay and Parker, Dave and Wilson, Nathan and Shadden, Shawn and Marsden, Alison},
  journal={Journal of Open Source Software},
  volume={7},
  number={78},
  pages={4118},
  year={2022}
}