## Water Pinch Analysis
[Read the docs](https://wateroptim.readthedocs.io/en/latest/)
A powerful pure-Python interface for optimizing industrial water networks
## Installation
``WaterOptim`` runs under Python 3.6+. To install it with [pip](https://pip.readthedocs.io/), run the following:
pip install WaterOptim
To upgrade it with [pip](https://pip.readthedocs.io/), run the following:
pip install --upgrade WaterOptim
## HeadingBasic Usage
``WaterOptim`` proposes water networks with optimized water recovery schemes to preserve freshwater and minimize wastewater production. The tool supports water networks with one or more pollutants.
The optimization strategy includes 3 steps:
- Inventory
- Minimization of Freshwater and Wastewater
- Design of Water-network
The inventory can be carried out on:
- **Water-using process**
- **Sources**
- **Sinks**
**Water-using process** involves pollution transfer. The pollution comes from the product or the process.
The inventory includes:
| Parameters | Description | Unit |
|--|--|--|
| ***mc*** | Mass flowrate of contaminant | kg/h |
| ***cin_max*** | Maximum inlet concentration | ppm |
| ***cout_max*** | Maximum outlet concentration | ppm |
Example of **Water-using process** inventory:
posts = [
{"name":"process 1","cin_max":0,"cout_max":100,"mc":2},
{"name":"process 2","cin_max":50,"cout_max":100,"mc":5},
{"name":"process 3","cin_max":50,"cout_max":800,"mc":30},
{"name":"process 4","cin_max":400,"cout_max":800,"mc":4}
]
**Source** water flow, available for the **REUSE**.
The inventory includes:
|Parameter| Description | Unit|
|--|--|--|
| ***m*** | Water flowrate | m3/h |
| ***c*** | Outlet concentration | ppm |
Example of **Sources** inventory:
sources = [
{'name':'Distillation bottoms','c':0,'m':.8*3600/1000},
{'name':'Off-gas condensate','c':14,'m':5*3600/1000},
{'name':'Aqueous layer','c':25,'m':5.9*3600/1000},
{'name':'Ejector condensate','c':34,'m':1.4*3600/1000}]
**Sink** water requirement. The inventory includes:
|Parameter| Description | Unit|
|--|--|--|
| ***m*** | Water flowrate | m3/h |
| ***cin_max*** | Maximum inlet concentration | ppm |
| | |
Example of ``Sinks`` inventory:
demands = [
{'name':'BFW0','cin_max':0,'m':1.2*3600/1000},
{'name':'BFW','cin_max':10,'m':5.8*3600/1000},
{'name':'BFW1','cin_max':1,'m':19.8*3600/1000}]
## HeadingBasic compilation
Import this module with the following command:
import WaterOptim.wpinch as wp
Compilation of **water-using processes**
r= wp.__pinch__(posts=posts,verbose=True,design=True)
Using the **cascade** attribute you can access the optimization details:
>> r.cascade
| C ppm | Purity | Purity Difference | NWSD | CWSD | PWF | CPWF | FFW |
|--|--|--|--|--|--|--|--|
| - | - | - | - | fw=90.00 | | | |
| 0 | 1.000000 | | -20.00 | | | | |
| | | 0.000050 | | 70.00 | 0.003500 | | |
| 50 | 0.999950 | | -140.00 | | | 0.00 | 70.00 |
| | | 0.000050 | | -70.00 | -0.003500 | | |
| {100} | {0.999900} | {} | {120.00} | {} | {} | {0.00} | {0.00} |
| | | 0.000300 | | 50.00 | 0.015000 | | |
| 400 | 0.999600 | | -10.00 | | | 0.01 | 37.50 |
| | | 0.000400 | | 40.00 | 0.016000 | | |
| 800 | 0.999200 | | 50.00 | | | 0.03 | 38.75 |
| | | 0.999200 | | 90.00 | 89.928000 | | |
| 1000000 | 0.000000 | | 0.00 | | | 89.96 | 89.96 |
| - | - | - | - | ww=90.00 | | | |
|
To display the water network:
>> r.design.draw()
## Dependencies
- [scipy](https://www.scipy.org/)
- [numpy](https://numpy.org/)
- [matplotlib](https://matplotlib.org/)
- [graphviz](https://graphviz.org/)
## Acknowledgments
The authors wish to thank the French National Research Agency [ANR](https://anr.fr/Projet-ANR-17-CE10-0015) for their funding, and the partners of the project [MINIMEAU](https://minimeau.fr/) led by **AgroParisTech** (French higher education and public research institute), in collaboration with **ProSim** (Expert in process simulation) **ACTALIA**, **CRITT**, **CTCPA**, **IFV**, **ITERG** (Centers of expertise for the food industry), and **INRAE ELSA** (French institute for agriculture, food and environment).
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