Input data for swolfpy's life-cycle process models (swolfpy_inputdata).
Project description
Input data for swolfpy’s life-cycle process models (swolfpy_inputdata)
Free software: GNU GENERAL PUBLIC LICENSE V2
Website: https://swolfpy-project.github.io
Documentation: https://swolfpy.readthedocs.io.
Repository: https://github.com/SwolfPy-Project/swolfpy-inputdata
Features
Input data for Life-cycle process models of swolfpy
Common data (e.g., molecular weights, heating values)
Material properties (46 common waste fractions; e.g., Food waste, Yard waste)
Chemical properties (e.g., carbon content, methane yield)
Physical properties (e.g., moisture content, density)
Material dependent process model inputs (e.g., separation efficiency for each waste fraction in the trommel)
Material indepent process model inputs
Built-in Monte Carlo simulation
Field |
Description |
---|---|
Category |
Category of the input (e.g., energy recovery, post closure) |
Dictonary_Name |
Name of the dictionary and attribute (whitespace is not allowed) |
Parameter Name |
Short name of the parameter (whitespace is not allowed) |
Parameter Description |
Longer description of the parameter |
Amount |
Default value for the parameter |
Unit |
Unit of the parameter (e.g., MJ/Mg, kW, hours/day) |
Uncertainty_type |
0: Undefined, 2: Lognormal, 3: normal, 4: Uniform, 5: Triangular, 7: Discrete Uniform |
Loc |
Mean for lognormal and normal distribution |
scale |
Standard deviation for lognormal and normal distribution |
shape |
Shape parameter for Weibull, Gamma or Beta distributions |
Minimum |
Lower bound/minimum for lognormal, normal, uniform, triangular, and discrete uniform distributions |
maximum |
Upper bound/maximum for lognormal, normal, uniform, triangular, and discrete uniform distributions |
Reference |
|
Comment |
Installation
1- Download and install miniconda from: https://docs.conda.io/en/latest/miniconda.html
2- Update conda in a terminal window or anaconda prompt:
conda update conda
3- Create a new environment for swolfpy:
conda create --name swolfpy python=3.9
4- Activate the environment:
conda activate swolfpy
5- Install swolfpy_inputdata in the environment:
pip install swolfpy_inputdata
6- Use in python (e.g., Landfill model):
import swolfpy_inputdata as spid data = spid.LF_Input() model.calc() #Example: Returs the actk parameter in landfill data.LF_gas['actk'] #Example: Returns input data in dataframe format data.Data
History
1.1.0 (2023-07-30)
Downgrade to Python 3.9
1.0.0 (2023-06-03)
Upgrade to Python 3.10
Add PreCommit
0.2.4 (2022-04-05)
Add Multi-family and commercial Waste collection
Add Animal feed production (AnF)
0.2.3 (2021-11-24)
Update Landfill
0.2.1 (2021-10-02)
New models: Gasification & Syngas combustion (GC), Refuse-Derived Fuel (RDF), Home composting (HC)
0.1.9 (2021-05-10)
Life cycle cost, input data for TS, References
0.1.0 (2020-05-06)
First release on PyPI. Data for the Life-cycle process models include: LF, WTE, Composting, AD, SS_MRF, reprocessing and Collection.
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