GCAT: grid convergence analysis toolkit

Note

The implementation is completed. Thus, do not expect updates to the code anymore.

Installation

Rye

1. Clone the repository

   git clone https://github.com/gabrielbdsantos/gcat
   cd gcat
   

2. Pin a specific Python version (optional)

   rye pin 3.x
   

3. Install

   rye sync
   

4. Activate the virtual environment.

   source .venv/bin/activate
   

Pip

1. Clone the repository

   git clone https://github.com/gabrielbdsantos/gcat
   cd gcat
   

2. Create a virtual environment (optional)

   python3 -m venv .venv --clear
   

3. Install

   pip install -r requirements.lock
   

4. Activate it

   source .venv/bin/activate
   

Quick start

1. Check the refinement ratios and representative grid sizes.

   $ gcat check --n1 1000 --n2 2000 --n3 3000 --area 0.5
   # Grid summary
   + ------------
     N1 = 2900 elements
     N2 = 1700 elements
     N3 = 1000 elements
     Area = 0.2 m^2
   
   # Representative grid size
   + ------------------------
     h1 = 8.304548 mm
     h2 = 10.846523 mm
     h3 = 14.142136 mm
   
   # Refinement ratio
   + ----------------
     r21 = 1.306094
     r32 = 1.303840
   

2. Compute the grid convergence index

   $ gcat gci --h1 8.30 --h2 10.84 --h3 14.14 --f1 1 --f2 1.02 --f3 1.08
   # Grid summary
   + ---------------------------------------
   h1 = 8.300000e+00 m, f1 = 1.000000e+00
   h2 = 1.084000e+01 m, f2 = 1.020000e+00
   h3 = 1.414000e+01 m, f3 = 1.080000e+00
   
   # GCI (safety factor = 1.25)
   + ---------------------------------------
   GCI21_fine   = 1.235897e-02
   GCI21_coarse = 3.735897e-02
   
   GCI32_fine   = 3.662651e-02
   GCI32_coarse = 1.101559e-01
   
   Asymptotic ratio = 1.019998
   Observed order of convergence = 4.143231
   

References

1. I. B. Celik, U. Ghia, P. J. Roache, C. J. Freitas, H. Coleman, and P. E. Raad, Procedure for Estimation and Reporting of Uncertainty Due to Discretization in CFD Applications,” J. Fluids Eng., vol. 130, no. 7, p. 078001, Jul. 2008, doi: 10.1115/1.2960953.

2. P. J. Roache, Quantification of Uncertainty in Computational Fluid Dynamics, Annu. Rev. Fluid Mech., vol. 29, no. 1, pp. 123–160, Jan. 1997, doi: 10.1146/annurev.fluid.29.1.123.

3. Examining Spatial (Grid) Convergence. https://www.grc.nasa.gov/WWW/wind/valid/tutorial/spatconv.html (accessed Oct. 22, 2020).

License

The code is licensed under the terms of the MIT license. For further information refer to LICENSE.