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
-
Open
scripts/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:
Sensitivity study
-
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)
-
Run
sensitivity.py -
Admire the output:
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
🎉
Metadata
Release files for nondim-slurry 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| nondim-slurry-0.1.tar.gz | 23.2 kB | Without provenance | Details for nondim-slurry-0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| nondim_slurry-0.1-py3-none-any.whl | Python 3 | none | any | Details for nondim_slurry-0.1-py3-none-any.whl |
Total release size: 49.6 kB
Release files / nondim-slurry-0.1.tar.gz
| Download URL | nondim-slurry-0.1.tar.gz |
|---|---|
| Size | 23.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f832c1d9c431693df214ab1e081065adf142df82991c5085e65448a929a044fc
|
|
BLAKE2b-256 checksum How to use checksums |
cbd4d5762b4bdb3d7411e49006f12c39815228298fa5c75d4be521d71aff127d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5
|
Release files / nondim_slurry-0.1-py3-none-any.whl
| Download URL | nondim_slurry-0.1-py3-none-any.whl |
|---|---|
| Size | 26.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b1b5e262a786dd02177d376d01866c3934e1a7d0676555f36e72333ffb1b8166
|
|
BLAKE2b-256 checksum How to use checksums |
7f40e9e4cd0fa89b1ce1ce21c73d92c5a05c06cb9214bdbfebc70cdd38944e23
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5
|
Security for nondim-slurry 0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.