DOI: 10.5068/d1310b
title: UF pre-treatment of seawater RO feedwater - performance data

description: The datasets represent ultrafiltration (UF) operation, for pre-treatment
 of seawater RO feedwater, over a total period of 422 days.  The
 operational data for UF filtration and backwash were obtained in a field
 study at Port Hueneme (CA) over a wide range of water quality conditions
 and coagulant dose. The data were utilized to develop a machine learning
 model for UF membrane resistance and backwash efficiency.
description: Data of ultrafiltration UF performance (during both filtration
 and backwash) were collected over a 4-year field study of seawater
 desalination with UF feedwater pretreatment.  
description: The data includes a series of datasets for both short-term and
 long-term UF operational periods. Performance data includes the following
 variables: - Microfilter pressure driving
 force<br> - UF transmembrane pressure during filtration<br> -
 UF transmembrane pressure during backwash<br> - Initial UF membrane
 resistance<br> - UF Coagulant dose <br> - UF feedwater
 turbidity<br> - Filtrate temperature<br> - UF backwash
 duration<br> - Filtrate pH<br> - Chlorophyll a (RFU) of
 feedwater<br> - UF Backwash flux<br> - Operation
 time
 ------------------------------------------------------------------------------------------------------------------------------------------------------------ This DATASET Readme.txt file was generated on 2021-03-06 by Yoram Cohen<br> &lt;help text is included in angle brackets, and can be deleted before saving&gt; GENERAL INFORMATION 1. Title of Dataset: Ultrafiltration Performance Data for Treatment of Seawater Reverse Osmosis Feedwater 2. Author Information     A. Principal Investigator Contact Information<br>         Name: Yoram Cohen<br>         Institution: University of California, Los Angeles    <br>         Address: 420 Westwood Plaza, Los Angeles, CA 90095<br>         Email: yoram@ucla.edu     B. Associate or Co-investigator Contact Information<br>         Name: Yang Zhou<br>         Institution: East China University of Science and Technology<br>         Address: Meilong Road 130, Shanghai, China<br>         Email: zhouyangucla@gmail.com     C. Alternate Contact Information<br>         Name: Han Gu<br>         Institution: Orange County Water District<br>         Address: 18700 Ward Street, Fountain Valley, CA 92708<br>         Email: hgu@ocwd.com 3. Date of data collection (single date, range, approximate date): Dates of data collection are provided which each of the dataset files 4. Geographic location of data collection &lt;latitude, longitude, or city/region, State, Country, as appropriate&gt;: Port Hueneme, California, U.S.A 5. Information about funding sources that supported the collection of the data: <br> The United States Office of Naval Research (N00014-11-1-0950 ONR and ONR N00014-09-1-1132), <br> California Department of Water Resources(46-4120 and RD-2006-09), <br> U.S. Bureau of Reclamation (R13AC80025), <br> Naval Facilities Engineering Command (N62583-11-C-0630), <br> and UCLA Water Technology Research (WaTeR) Center. SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: No restrictions, but acknowledgement of the data generators/authors is requested 2. Links to publications that cite or use the data: <br> The Modeling UF Fouling and Backwash of Seawater RO Feedwater Using Neural Network with Evolutionary Algorithm and Bayesian Binary Classification(paper number: DES-S-21-00364); Gu H. et al., Fouling indicators for field monitoring the effectiveness of operational strategies of ultrafiltration as pretreatment for seawater desalination(doi: 10.1016/j.desal.2017.11.038) Gao, L. et al., Self-adaptive cycle-to-cycle control of in-line coagulant dosing in ultrafiltration for pre-treatment of reverse osmosis feed water(doi: 10.1016/j.desal.2016.09.024) 3. Links to other publicly accessible locations of the data: This repository<br> Link:  4. Links/relationships to ancillary data sets: None 5. Was data derived from another source? no<br>     A. If yes, list source(s):  6. Recommended citation for this dataset:  Yang Zhou, Bilal Khan, Han Gu, Panagiotis Christofides and Yoram Cohen, "Performance Data for Ultrafiltration Treatment of Seawater Reverse Osmosis Feedwater", doi: 10.5068/D1310B <br> DATA & FILE OVERVIEW 1. File List: 150 training datasets in training folder, and 30 test datasets in test folder, the datasets in the folder are named as the date of the collection.<br> All datasets are included in the uploaded zipped file. 2. Relationship between files, if important: Files are independent with all file descriptors and operating conditions provided in each dataset 3. Additional related data collected that was not included in the current data package: There is no additional uncollected data 4. Are there multiple versions of the dataset?  No<br>     A. If yes, name of file(s) that was updated: <br>         i. Why was the file updated? <br>         ii. When was the file updated?  <br> METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: <br> The pertinent publications containing experimental design/protocols used in data collection are referenced below: Gu, H. et al., Fouling indicators for field monitoring the effectiveness of operational strategies of ultrafiltration as pretreatment for seawater desalination <br> doi: 10.1016/j.desal.2017.11.038 Gao, L. et al., Self-adaptive cycle-to-cycle control of in-line coagulant dosing in ultrafiltration for pre-treatment of reverse osmosis feed water<br> doi: 10.1016/j.desal.2016.09.024 2. Methods for processing the data: <br> Data collection is detailed in the manuscript referenced below:<br> Gu, H. et al., Fouling indicators for field monitoring the effectiveness of operational strategies of ultrafiltration as pretreatment for seawater desalination<br> doi: 10.1016/j.desal.2017.11.038 Gao, L. et al., Self-adaptive cycle-to-cycle control of in-line coagulant dosing in ultrafiltration for pre-treatment of reverse osmosis feed water<br> doi: 10.1016/j.desal.2016.09.024 3. Instrument- or software-specific information needed to interpret the data: <br> Data files are in Excel format. A total of 180 datasets are included in the uploaded Zipped file 4. Standards and calibration information, if appropriate: No 5. Environmental/experimental conditions: <br> All experimental conditions are in the dataset. Information regarding meteorological conditions (if needed) <br> can be obtained from local Meteorological stations given the specified dates of data collections. 6. Describe any quality-assurance procedures performed on the data: <br> Gu, H., Fouling indicators for field monitoring the effectiveness of operational strategies of ultrafiltration as pretreatment for seawater desalination<br> doi: 10.1016/j.desal.2017.11.038 Gao., L. et al., Self-adaptive cycle-to-cycle control of in-line coagulant dosing in ultrafiltration for pre-treatment of reverse osmosis feed water<br> doi: 10.1016/j.desal.2016.09.024 7. People involved with sample collection, processing, analysis and/or submission: <br> Yang Zhou, Bilal Khan, Han Gu, Panagiotis Christofides, Yoram Cohen and Gao, Larry. DATA-SPECIFIC INFORMATION FOR Files <br> The files are number as given below:<br> #TR1-#TR85   (TR -training dataset followed by the dataset number)<br> #TR98-#TR150 (TR -training dataset followed by the dataset number)<br> ##TE1-#TE20  (TE- test dataset followed by the dataset number)<br> #TE26-#TE30  (TE- test dataset followed by the dataset number) &lt;repeat this section for each dataset, folder or file, as appropriate&gt; 1. Number of variables: 23 2. Number of datasets: 105; 3. Dates of collection indicator in each dataset 4. Total number of variables:23  <br> Time and Date<br> UF Inflow Rate<br> UF Element 1 (E1) Inflow rate<br> UF Element 2 (E2) Inflow rate<br> UF Element 3 (E3) Inflow rate<br> UF Backwash Flow Rate<br> Filtrate pH<br> MF Inlet Pressure<br> MF Trans-filter Pressure<br> UF Inlet Filtration Pressure<br> UF Feed-Side Backwash Pressure<br> UF filtrate side backwash Pressure<br> UF Filtrate-side Pressure<br> UF Filtrate Turbidity<br> UF Feedwater Turbidity<br> UF Feed Pump RPM<br> Filtrate Temperature<br> Coagulant Dose<br> Initial UF Resistance<br> Filtration Duration<br> Backwash Flux<br> Backwash Duration (2) Datasets #TR86-#TR97 and #TE21-#TE25<br> (Dataset #TE23 is for UF oepration during a storm event) 1. Number of variables: 24 2. Number of datasets: 17 3. Dates of collection indicater in each dataset 4. Total nummber of variables:24  <br> Time and Date<br> UF Inflow Rate<br> UF Element 1 (E1) Inflow rate<br> UF Element 2 (E2) Inflow rate<br> UF Element 3 (E3) Inflow rate<br> UF Backwash Flow Rate<br> Filtrate pH<br> MF Inlet Pressure<br> MF Trans-filter Pressure<br> UF Inlet Filtration Pressure<br> UF Feed-Side Backwash Pressure<br> UF filtrate side backwash Pressure<br> UF Filtrate-side Pressure<br> UF Filtrate Turbidity<br> UF Feedwater Turbidity<br> UF Feed Pump RPM<br> Filtrate Temperature<br> Coagulant Dose<br> Chlorophyll RFU<br> Initial UF Resistance<br> Filtration Duration<br> Backwash Flux<br> Backwash Duration