Search Navigation Menu
DOE Data Explorer title logo U.S. Department of Energy
Office of Scientific and Technical Information
Search Scientific Data

Title: WaterTAP 0.7 Release

Abstract

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

Authors:
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »; ; ; ; ; « less
+ Show Author Affiliations
  1. National Energy Technology Laboratory
Publication Date:
Other Number(s):
5d1fb205-4735-4988-899c-932ececdd49b
Research Org.:
National Energy Technology Laboratory - Energy Data eXchange; NETL
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Subject:
IDAES; Process Systems Engineering; Technoeconomic Assessment; Water Treatment; WaterTAP
OSTI Identifier:
2336713
DOI:
https://doi.org/10.18141/2336713

Citation Formats

Atia, Adam, Knueven, Bernard, Arnold, Travis, Barber, Hunter, Beattie, Keith, Bi, Xiangyu, Bianchi, Ludovico, Dudchenko, Alexander V, Garciadiego, Alejandro, Gunter, Dan, Holly, Marcus, Ladshaw, Austin, Lee, Andrew, Amusat, Oluwamayowa, Panda, Kinshuk, Pesce, Michael, Sitterley, Kurban A, Wang, Chenyu, Allu, Srikanth, Li, Yalin, Rao, Akshay, Tucker, Carson, Young, Ethan, Zhang, Zhuoran, and Bartholomew, Timothy. WaterTAP 0.7 Release. United States: N. p., 2022. Web. doi:10.18141/2336713.
Copy to clipboard
Atia, Adam, Knueven, Bernard, Arnold, Travis, Barber, Hunter, Beattie, Keith, Bi, Xiangyu, Bianchi, Ludovico, Dudchenko, Alexander V, Garciadiego, Alejandro, Gunter, Dan, Holly, Marcus, Ladshaw, Austin, Lee, Andrew, Amusat, Oluwamayowa, Panda, Kinshuk, Pesce, Michael, Sitterley, Kurban A, Wang, Chenyu, Allu, Srikanth, Li, Yalin, Rao, Akshay, Tucker, Carson, Young, Ethan, Zhang, Zhuoran, & Bartholomew, Timothy. WaterTAP 0.7 Release. United States. doi:https://doi.org/10.18141/2336713
Copy to clipboard
Atia, Adam, Knueven, Bernard, Arnold, Travis, Barber, Hunter, Beattie, Keith, Bi, Xiangyu, Bianchi, Ludovico, Dudchenko, Alexander V, Garciadiego, Alejandro, Gunter, Dan, Holly, Marcus, Ladshaw, Austin, Lee, Andrew, Amusat, Oluwamayowa, Panda, Kinshuk, Pesce, Michael, Sitterley, Kurban A, Wang, Chenyu, Allu, Srikanth, Li, Yalin, Rao, Akshay, Tucker, Carson, Young, Ethan, Zhang, Zhuoran, and Bartholomew, Timothy. 2022. "WaterTAP 0.7 Release". United States. doi:https://doi.org/10.18141/2336713. https://www.osti.gov/servlets/purl/2336713. Pub date:Mon Dec 19 23:00:00 EST 2022
Copy to clipboard
@article{osti_2336713,
title = {WaterTAP 0.7 Release},
author = {Atia, Adam and Knueven, Bernard and Arnold, Travis and Barber, Hunter and Beattie, Keith and Bi, Xiangyu and Bianchi, Ludovico and Dudchenko, Alexander V and Garciadiego, Alejandro and Gunter, Dan and Holly, Marcus and Ladshaw, Austin and Lee, Andrew and Amusat, Oluwamayowa and Panda, Kinshuk and Pesce, Michael and Sitterley, Kurban A and Wang, Chenyu and Allu, Srikanth and Li, Yalin and Rao, Akshay and Tucker, Carson and Young, Ethan and Zhang, Zhuoran and Bartholomew, Timothy},
abstractNote = {The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.},
doi = {10.18141/2336713},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Dec 19 23:00:00 EST 2022},
month = {Mon Dec 19 23:00:00 EST 2022}
}
Copy to clipboard
Dataset:
View Dataset
DOI: https://doi.org/10.18141/2336713
Save / Share:
Export Metadata
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.

Similar records in DOE Data Explorer and OSTI.GOV collections: