An article reporting the travails of reproducibility in unsteady CFD studies
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README.md

"Reproducible and replicable CFD: it's harder than you think"

(c) Olivier Mesnard, Lorena A. Barba, 2016.

Article submitted on 13 May 2016. Preprint on arXiv:1605.04339

Decision 25 July 2016: Accept with minor revisions, Computing in Science and Engineering.

Contents

This repository contains the manuscript source files, and supplementary materials including input files, geometry files, running scripts and Jupyter notebooks for all runs reported on in the paper.

The notebook tableOfContents lists the simulations reported in the paper, with a link to their respective report notebook.

In each notebook, we include information about the dependencies needed by each code, the mesh information, the boundary conditions, the parameters for each linear solver, the command-line input to run the simulation and finally the Python post-processing scripts to generate the figures.

Dependencies

The Python scripts rely on the package snake that we developed to post-process and compare the numerical solution from four different CFD codes. The package is hosted on GitHub under the MIT License.


The article reports on a full replication study of our previously published findings on bluff-body aerodynamics of flying snakes (Krishnan et al., 2014).

Over the span of about three years, we ran hundreds of simulations of the flow around a 2D snake geometry, using four different flow solvers. The paper reports on 40 of these runs, telling the story of our mistakes and challenges to complete the replication of our previous findings.

We prepared detailed "Reproducibility packages" for each one of the simulations reported in the paper; they are in the /reproducibilityPackages directory. Each simulation folder contains a Jupyter Notebook, named report, with all the information about the case, and all the data needed to reproduce the calculation.

The folder figures contains all the plots and flow visualizations included in the paper. The Python and bash scripts we used to generate the figures are in the folder reproducibilityPackages/figures.


We used a total of four CFD solvers in the study:

cuIBM--- Used for our original study (Krishan et al., 2014), this code is written in C CUDA to exploit GPU hardware, but is serial on CPU. It uses the NVIDIA Cusp library for solving sparse linear systems on GPU. https://github.com/barbagroup/cuIBM
OpenFOAM--- A free and open-source CFD package that includes a suite of numerical solvers. The core discretization scheme is a finite-volume method applied on mesh cells of arbitrary shape. http://www.openfoam.org
IBAMR--- A parallel code using the immersed boundary method on Cartesian meshes, with adaptive mesh refinement. https://github.com/ibamr/ibamr
PetIBM--- Our own re-implementation of cuIBM, but for distributed-memory parallel systems. It uses the PETSc library for solving sparse linear systems in parallel. https://github.com/barbagroup/PetIBM


LICENSE -- Not all content in this repository is open source. The Python code only is shared under an MIT License. The written content in the Jupyter Notebooks is shared under a Creative Commons Attribution (CC-BY) license. But please note that the manuscript text is not open source; we reserve rights to the article content, which is currently submitted for publication in a journal. Only fair use applies in this case.

References

  • Krishnan, Anush, John J. Socha, Pavlos P. Vlachos, L. A. Barba (2014), Lift and wakes of flying snakes. Physics of Fluids 26, 031901, doi:10.1063/1.4866444
  • Krishnan, Anush, John J. Socha, Pavlos P. Vlachos, L. A. Barba (2013), Body cross-section of the flying snake Chrysopelea paradisi. figshare. doi:10.6084/m9.figshare.705877.v1