https://github.com/jnywong/nondim-slurry
Welcome! Here you will find the Python code that solves the 1D, steady, spherical slurry equations outlined in Wong et al (2021) (see also Wong et al. 2018)
https://github.com/jnywong/nondim-slurry
Last synced: 2 months ago
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Welcome! Here you will find the Python code that solves the 1D, steady, spherical slurry equations outlined in Wong et al (2021) (see also Wong et al. 2018)
- Host: GitHub
- URL: https://github.com/jnywong/nondim-slurry
- Owner: jnywong
- License: mit
- Created: 2020-03-20T09:54:35.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-10-14T08:55:18.000Z (over 3 years ago)
- Last Synced: 2025-03-20T11:11:34.920Z (3 months ago)
- Language: Python
- Homepage:
- Size: 1.81 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
[](https://travis-ci.org/jnywong/nondim-slurry)
[](https://doi.org/10.5281/zenodo.4446750)
# slurpy
Python module to solve the 1D, steady, spherical slurry system outlined in Wong et al.
(2021) (see also Wong et al. 2018).
## Getting Started
### Prerequisites
- [Python](https://www.python.org/)
### Installing
Conda:
```
conda install -c jnywong nondim-slurry
```
Pip:
```
pip install nondim-slurry
```
Git:
Find the latest version of the repository [here](https://github.com/jnywong/nondim-slurry).
## Package structure
```
slurpy/
__init__.py
coreproperties.py
data_utils.py
getparameters.py
lookup.py
lookupdata/
denPREM.csv
gravPREM.csv
presPREM.csv
radAK135.csv
radPREM.csv
vpAK135.csv
vpPREM.csv
plot_utils.py
scripts/
parameter_search.py
seismic.py
sensitivity.py
slurry.py
```
## Example scripts
### Parameter search
1. Open `scripts/parameter_search.py`
2. Enter some input parameters. For example, try:
```
# %% MODEL INPUTS
# Show plots?
plotOn=1 # show temp, xi, solid flux and density profiles
# Input parameters
layer_thicknesses=np.array([150e3]) # (m)
thermal_conductivities=np.array([100.]) # (W m^-1 K^-1)
icb_heatfluxes=np.array([3.4]) # (TW)
csb_heatfluxes=np.array([7.4]) # (TW)
h=0.05 # stepsize of heat flux through parameter space
```
3. Run `parameter_search.py`
4. Admire the output:
### Sensitivity study
1. Open `scripts/sensitivity.py`
2. Enter some input parameters. For example, try:
```
# %% MODEL INPUTS
# Save plot?
saveOn=0
# Input parameters
layer_thickness=150e3 # (m)
thermal_conductivity=100. # (W m^-1 K^-1)
icb_heatflux=2.5 # (TW)
csb_heatflux=5.0 # (TW)
h=0.05 # stepsize of heat flux through parameter space
# Sensitivity study
csb_temp = np.arange(4500.,6100.,100) # (K)
csb_oxy = np.arange(2,12.5,0.5) # (mol.%)
sed_con= np.array([1e-5,1e-4,1e-3,1e-2,1e-1]) # (kg s/m^3) pre-factor in sedimentation coefficient, b(phi)
```
3. Run `sensitivity.py`
4. Admire the output:
## Links
* [PyPI](https://pypi.org/project/nondim-slurry/)
* [Anaconda Cloud](https://anaconda.org/jnywong/nondim-slurry)
## Authors
* [**Jenny Wong**](https://jnywong.github.io/) - *University of Leeds - Institut de Physique du Globe de Paris - Institut des Sciences de la Terre*
* [**Chris Davies**](https://environment.leeds.ac.uk/see/staff/1225/dr-chris-davies) - *University of Leeds*
* [**Chris Jones**](https://eps.leeds.ac.uk/maths/staff/4042/professor-christopher-jones-) - *University of Leeds*
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
## Acknowledgments
* ERC SEIC
* Del Duca Foundation
* EPSRC Centre for Doctoral Training in Fluid Dynamics
:tada: