bhajay / incrmt

A C++ implementation of the incompressible reference map technique

IncRMT: A C++ implementation of the incompressible reference map technique

This repository contains an implementation of the incompressible reference map technique (RMT), a numerical method for simulating fluid–structure interaction problems on a single fixed background grid. The code provided here can perform many examples and tests of the method that are described in the following scientific publication:

• Chris H. Rycroft, Chen-Hung Wu, Yue Yu, and Ken Kamrin, Reference map technique for incompressible fluid–structure interaction, Journal of Fluid Mechanics 898, A9 (2020). doi:10.1017/jfm.2020.353

Background

Fluid–structure interaction problems occur in many scientific and industrial applications. Examples include the airflow around a bird's wing, the fluttering of a flag in the wind, or the movement of a ship through the ocean.

The typical approach to simulate a solid is to employ a moving computational mesh that deforms with the solid object. This approach is taken in popular solid mechanics software packages such as Abaqus. However, the typical approach for fluid simulation is to use a fixed background computational mesh, as used in popular fluid mechanics software packages such as Fluent. For fluid–structure interaction problems it is necessary to bridge these two perspectives, and a wide variety of approaches exist in the literature. For example, the widely-used immersed boundary method develops transfer operators for switching between these two approaches [1].

The reference map technique (RMT) is a computational method that allows fluids and solids to be simulated using a single fixed background grid. This greatly simplifies the coupling between the solid and fluid phases. The key idea is to introduce a reference map field, which tracks where the solid started from, and is sufficient to implement large-strain solid mechnics. The original idea was developed by Kamrin, Nave, and Rycroft [2,3,4], to simulate a single compressible solid in a fluid. The numerical methods were subsequently improved by Valkov, Rycroft, and Kamrin [5] to simulate multiple solids.

This repository contains examples and tests of the RMT to support the recent publication by Rycroft et al. listed above. The implementation is a major improvement over previous work, and in particular can simulate incompressible fluids and solids, which is appropriate for many problems.

Compiling the code

The code is written in C++ and uses the OpenMP library for multithreading. It has been tested on Linux, MacOS, and Windows (via Cygwin).

• The code requires on TGMG, a C++ library for solving linear systems using the geometric multigrid method [6,7], which is available as a separate repository on GitHub.

• The code outputs data in a binary format that can be read by the freeware plotting program Gnuplot. The code uses a utils-gp, a collection of tools for processing and analyzing Gnuplot output files. This is available as a separate repository on GitHub.

• The utils-gp repository requires libpng for making for full functionality, but this dependency can be omitted. To make movies of the simulation output FFmpeg is needed.

By default the code assumes that the incrmt, tgmg, and utils-gp repositories are placed in the same parent directory.

To compile the code it is necessary to create a common configuration file called config.mk in the parent directory, which can be used by all three repositories. Several templates are provided in the config directory. To use, copy one of the templates into the parent directory. From the incrmt directory, on a Linux computer, type

cp config/config.mk.linux ../config.mk

On a Mac using GCC 11 installed via MacPorts, type

cp config/config.mk.mac_mp ../config.mk

On a Mac using GCC installed via Homebrew, type

cp config/config.mk.mac_hb ../config.mk

On a Windows computer with Cygwin installed, type

cp config/config.mk.win_cw ../config.mk

After this, the code can be compiled by typing

make

This will build several executables such as ftest, conv_test, and sediment.

Example

The simple three-pronged rotor example that described in Appendix C of the paper can be run using four threads on a 128 × 128 grid with the following command:

OMP_NUM_THREADS=4 ./ftest simple-spin 128

The code will create a directory called sspin_128.odr for the simulation output. (Here, the odr suffix stands for output directory.) The output directory contains files of different types:

• w., the vorticity field at frame n;
• phi., the level set field at frame n;
• X. and Y., the components of the reference map at frame n;
• trace., the fluid tracer positions at frame n stored in binary format;
• track.dat, the position of a special tracer on an arm of the rotor that tracks its rotation;
• header, a small text file containing the number of simulation frames and the time interval simulated.

In Gnuplot, the vorticity field at t = 2π can be plotted using the following commands:

set pm3d map
splot 'sspin_128.odr/w.120' matrix binary

If FFmpeg is installed, then the following command can be used to generate a movie:

./gnuplot_movie.pl -t sspin_128.odr w -10 10

This will generate a QuickTime movie using the H.265 codec called sspin_128_w.mov. Alternatively, to just make the frames without making a movie, the command

./gnuplot_movie.pl -t -w sspin_128.odr w -10 10

can be used. This will create a directory called sspin_128.frames that contains the movie frames as PNG images.

Many other types of simulation are possible with the ftest code, most of which are taken from the associated publication. To see a complete list type

./ftest

Code structure

The code is structured around several C++ classes:

• The fluid_2d class contains the core routines for running a simulation. It allocates memory for the fluid and solid fields, and contains the main routines for updating these.

• The field data structure contains all of the fields required to simulate the fluid in one grid cell. The fluid_2d class allocates a two-dimensional array of the field data structure to perform the simulation.

• The object class is a pure virtual class that specifies the geometry and characteristics of a solid object. Many classes are derived from this, such as obj_circle describing a solid circle, and obj_flapper describing an actuated rod that can swim via a flapping motion.

• The obj_field class contains all of the data required to simulate one solid object. It is linked to a corresponding object type, and also contains information on the object's material characteristics. It contains a level set array for tracking the object's boundary. It allocates a two-dimensional array of the s_field data structure, which contains all of the simulation fields required to represent a solid.

• The sim_type class is a pure virtual class that specifies to global initial and boundary conditions of the simulation.

The simulation method requires two linear systems to be solved during each timestep: the marker-and-cell (MAC) projection, and the approximate projection using the finite-element method (FEM). The code contains classes that describe these linear systems, which are used by the TGMG library. There is a hierarchy

• mgs_base, containing data common across all linear systems
  • mgs_mac, containing data that is common for all MAC systems
    • mgs_mac_const_rho, the MAC system for constant density simulation, which allows for some significant optimization
    • mgs_mac_varying_rho, the MAC system for varying density simulation
  • mgs_fem, containing data that is common for all FEM systems
    • mgs_fem_const_rho, the FEM system for constant density simulation, which allows for some significant optimization
    • mgs_fem_varying_rho, the FEM system for varying density simulation

During the simulation initialization, the code checks to see whether objects with varying density are in use, and allocates the const_rho or varying_rho class variants accordingly.

Known issues

This code is designed to accompany the 2020 publication by Rycroft et al. It is a research code and still requires additional development to make it into a general-purpose fluid–structure simulation tool. In particular, it has the following known issues:

• Certain parts of the code, such as the extrapolation routines, are not multithreaded. This results in a loss of parallel efficiency for high numbers of OpenMP threads.

• In cases of extreme deformation near the object boundaries, the extrapolation routines may cause fictitious solid to be created within the fluid. This can cause the simulation to terminate prematurely.

• For simulations with multiple objects the code currently creates a separate obj_field class for every one. Each obj_field class contains globally-defined fields for the reference map, stress tensor, and level set, even though the object may only occupy a small region of the domain. Thus the memory and performance do not scale well to very large numbers (i.e. >100) of objects. This could be rectified with localized allocation of the simulation fields for each object.

• If an object has a high component of stress tangential to its boundary, the current stress-blurring mechanism can cause the nearby fluid to be accelerated. This is only noticeable at low viscosities and high stresses, and will be addressed in the future.

Contact

For questions about the code, contact Chris Rycroft.

Bibliography

1. Charles S. Peskin, The immersed boundary method, Acta Numerica 11, 479–517 (2002). doi:10.1017/S0962492902000077

2. Ken Kamrin, Stochastic and deterministic models for dense granular flow, Ph.D. thesis, Massachusetts Institute of Technology (2008). DSpace

3. Ken Kamrin and Jean-Christophe Nave, An Eulerian approach to the simulation of deformable solids: application to finite-strain elasticity, arXiv:0901.3799 (2009).

4. Ken Kamrin, Chris H. Rycroft, and Jean-Christophe Nave, Reference map technique for finite-strain elasticity and fluid–solid interaction, Journal of the Mechanics and Physics of Solids 60, 1952–1969 (2012). doi:10.1016/j.jmps.2012.06.003

5. Boris Valkov, Chris H. Rycroft, and Ken Kamrin, Eulerian method for multiphase interactions of soft solid bodies in fluids, Journal of Applied Mechanics 82, 041011 (2015). doi:10.1115/1.4029765

6. James W. Demmel, Applied Numerical Linear Algebra, SIAM (1997). doi:10.1137/1.9781611971446

7. William L. Briggs, Van Emden Henson, and Steve F. McCormick, A Multigrid Tutorial, Second Edition, SIAM (2000). doi:10.1137/1.9780898719505

8. James A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press (1999). ISBN:9780521645577 (1999).