Python module to solve the 1D, steady, spherical slurry system outlined in Wong et al. (2021) (see also Wong et al. 2018).
Conda:
conda install -c jnywong nondim-slurry
Pip:
pip install nondim-slurry
Git:
Find the latest version of the repository here.
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
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Open
scripts/parameter_search.py
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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
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Run
parameter_search.py
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Admire the output:
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Open
scripts/sensitivity.py
-
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)
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Run
sensitivity.py
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Admire the output:
- Jenny Wong - University of Leeds - Institut de Physique du Globe de Paris - Institut des Sciences de la Terre
- Chris Davies - University of Leeds
- Chris Jones - University of Leeds
This project is licensed under the MIT License - see the LICENSE.md file for details
- ERC SEIC
- Del Duca Foundation
- EPSRC Centre for Doctoral Training in Fluid Dynamics
🎉