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Reverse Osmosis Simulation Data

Publicly accessible License 

This dataset consists of computational fluid dynamics (CFD) output for various spacer configurations in a feed-water channel in reverse osmosis (RO) applications. Feed-water channels transport brine solution to the RO membrane surfaces. The spacers embedded in the channels help improve membrane performance by disrupting the concentration boundary layer growth on membrane surfaces. Refer to the "Related Work" resource below for more details. This dataset considers a feed-water channel of length 150mm. The inlet brine velocity and concentration are fixed at 0.1m/s and 100kg/m3 respectively. The diameter of the cylindrical spacers is fixed as 0.3mm and six varying inter-spacer distances of 0.75mm, 1mm, 1.5mm, 2mm, 2.5mm, and 3mm are simulated. The dataset comprising the steady, spatial fields of solute concentration, velocity, and density near each spacer is placed in the folder corresponding to the spacer configuration considered. We run two sets of CFD simulations and include the outputs from both sets for each configuration: (1) with a coarser mesh, producing low-resolution (LR) data of spatial resolution 20x20, and (2) with a finer mesh, producing high-resolution (HR) data of spatial resolution 100x100. These data points can be treated as images with the quantities of interest as their channels and can be used to train machine learning models to learn a mapping from the LR images as inputs to the HR images as outputs.

Citation Formats

TY - DATA AB - This dataset consists of computational fluid dynamics (CFD) output for various spacer configurations in a feed-water channel in reverse osmosis (RO) applications. Feed-water channels transport brine solution to the RO membrane surfaces. The spacers embedded in the channels help improve membrane performance by disrupting the concentration boundary layer growth on membrane surfaces. Refer to the "Related Work" resource below for more details. This dataset considers a feed-water channel of length 150mm. The inlet brine velocity and concentration are fixed at 0.1m/s and 100kg/m3 respectively. The diameter of the cylindrical spacers is fixed as 0.3mm and six varying inter-spacer distances of 0.75mm, 1mm, 1.5mm, 2mm, 2.5mm, and 3mm are simulated. The dataset comprising the steady, spatial fields of solute concentration, velocity, and density near each spacer is placed in the folder corresponding to the spacer configuration considered. We run two sets of CFD simulations and include the outputs from both sets for each configuration: (1) with a coarser mesh, producing low-resolution (LR) data of spatial resolution 20x20, and (2) with a finer mesh, producing high-resolution (HR) data of spatial resolution 100x100. These data points can be treated as images with the quantities of interest as their channels and can be used to train machine learning models to learn a mapping from the LR images as inputs to the HR images as outputs. AU - Nadakkal Appukuttan, Sreejith A2 - Sitaraman, Hariswaran A3 - Egan, Hilary DB - Open Energy Data Initiative (OEDI) DP - Open EI | National Renewable Energy Laboratory DO - 10.7481/2478402 KW - energy KW - water KW - reverse osmosis KW - clean water KW - AI surrogate KW - data-driven KW - data KW - CFD KW - dataset KW - resource extraction KW - RO KW - brine KW - membrane surface LA - English DA - 2024/04/22 PY - 2024 PB - National Renewable Energy Lab - NREL T1 - Reverse Osmosis Simulation Data UR - https://doi.org/10.7481/2478402 ER -
Export Citation to RIS
Nadakkal Appukuttan, Sreejith, et al. Reverse Osmosis Simulation Data. National Renewable Energy Lab - NREL, 22 April, 2024, NAWI. https://doi.org/10.7481/2478402.
Nadakkal Appukuttan, S., Sitaraman, H., & Egan, H. (2024). Reverse Osmosis Simulation Data. [Data set]. NAWI. National Renewable Energy Lab - NREL. https://doi.org/10.7481/2478402
Nadakkal Appukuttan, Sreejith, Hariswaran Sitaraman, and Hilary Egan. Reverse Osmosis Simulation Data. National Renewable Energy Lab - NREL, April, 22, 2024. Distributed by NAWI. https://doi.org/10.7481/2478402
@misc{OEDI_Dataset_6475, title = {Reverse Osmosis Simulation Data}, author = {Nadakkal Appukuttan, Sreejith and Sitaraman, Hariswaran and Egan, Hilary}, abstractNote = {This dataset consists of computational fluid dynamics (CFD) output for various spacer configurations in a feed-water channel in reverse osmosis (RO) applications. Feed-water channels transport brine solution to the RO membrane surfaces. The spacers embedded in the channels help improve membrane performance by disrupting the concentration boundary layer growth on membrane surfaces. Refer to the "Related Work" resource below for more details. This dataset considers a feed-water channel of length 150mm. The inlet brine velocity and concentration are fixed at 0.1m/s and 100kg/m3 respectively. The diameter of the cylindrical spacers is fixed as 0.3mm and six varying inter-spacer distances of 0.75mm, 1mm, 1.5mm, 2mm, 2.5mm, and 3mm are simulated. The dataset comprising the steady, spatial fields of solute concentration, velocity, and density near each spacer is placed in the folder corresponding to the spacer configuration considered. We run two sets of CFD simulations and include the outputs from both sets for each configuration: (1) with a coarser mesh, producing low-resolution (LR) data of spatial resolution 20x20, and (2) with a finer mesh, producing high-resolution (HR) data of spatial resolution 100x100. These data points can be treated as images with the quantities of interest as their channels and can be used to train machine learning models to learn a mapping from the LR images as inputs to the HR images as outputs.}, url = {https://waterdams.nawihub.org/submissions/18}, year = {2024}, howpublished = {NAWI, National Renewable Energy Lab - NREL, https://doi.org/10.7481/2478402}, note = {Accessed: 2025-04-25}, doi = {10.7481/2478402} }
https://dx.doi.org/10.7481/2478402

Details

Data from Apr 22, 2024

Last updated Jan 2, 2025

Submitted Oct 10, 2024

Organization

National Renewable Energy Lab - NREL

Contact

Saumya Sinha

303.384.6764

Authors

Sreejith Nadakkal Appukuttan

National Renewable Energy Lab - NREL

Hariswaran Sitaraman

National Renewable Energy Laboratory NREL

Hilary Egan

National Renewable Energy Laboratory NREL

DOE Project Details

Project Name NAWI Integrated Data and Analysis

Project Lead Melissa Klembara

Project Number 36496

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