Python code that solves the 1D, steady, spherical slurry equations outlined in Wong et al (in prep) (see also Wong et al. 2018)
Project description
slurpy
Solve the 1D, steady, spherical slurry system outlined in Wong et al. (in prep) (see also Wong et al. 2018).
Getting Started
Prerequisites
Installing
Conda:
conda install nondim-slurry
Pip:
pip install nondim-slurry
Git: Download the latest version of the repository here.
A simple example
Sample scripts can be found within the module package slurpy/scripts
.
-
Open
parameter_search.py
-
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
-
Run
parameter_search.py
-
Admire the output:
Example: Sensitivity study
-
Open
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)
-
Run
sensitivity.py
-
Admire the output:
Links
Authors
- Jenny Wong - Institut de Physique du Globe de Paris
- Chris Davies - University of Leeds
- Chris Jones - University of Leeds
License
This project is licensed under the MIT License - see the license.md file for details
Acknowledgments
- Del Duca Foundation
- EPSRC Centre for Doctoral Training in Fluid Dynamics
:tada:
Project details
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