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Python code that solves the 1D, steady, spherical slurry equations outlined in Wong et al (in prep, EPSL) (see also Wong et al. 2018)

Project description

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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

Installing

Conda:

conda install -c jnywong nondim-slurry

Pip:

pip install nondim-slurry

Git:

Find the latest version of the repository here.

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
  1. Run parameter_search.py

  2. 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)
  1. Run sensitivity.py

  2. Admire the output:

hello!

Links

Authors

  • 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

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • ERC SEIC
  • Del Duca Foundation
  • EPSRC Centre for Doctoral Training in Fluid Dynamics

:tada:

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