A control methodology for the feed water temperature to optimize SWRO desalination process using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Kim:2009:DS1,
  author =       "Seung Joon Kim and Sanghoun Oh and Young Geun Lee and 
                 Moon Gu Jeon and In S. Kim and Joon Ha Kim",
  title =        "A control methodology for the feed water temperature
                 to optimize SWRO desalination process using genetic
                 programming",
  journal =      "Desalination",
  year =         "2009",
  volume =       "247",
  pages =        "190--199",
  number =       "1-3",
  ISSN =         "0011-9164",
  keywords =     "genetic algorithms, genetic programming, Seawater
                 reverse osmosis (SWRO)",
  URL =          "http://www.sciencedirect.com/science/article/B6TFX-4X502WT-P/2/35e0f68a8e3e5dcddf34a87ddbc4703a",
  DOI =          "doi:10.1016/j.desal.2008.12.024",
  abstract =     "This paper presents a novel methodology to determine
                 an optimized control method for feed water temperature
                 in a seawater reverse osmosis (SWRO) desalination
                 process using genetic programming (GP) which is an
                 evolutionary algorithm used to find functional forms
                 through training data. Two functional models were
                 determined by GP with operation data collected over
                 four years from Fujairah SWRO plant. The models showed
                 high accuracy (>99.0percent) in terms of the average
                 error rate between the observed and the predicted
                 values. The first model involved the permeate water
                 flow rate with a functional temperature correction
                 factor (TCF), water transfer coefficient, and net
                 driving pressure (NDP) and the second is the salt
                 passage ratio with a functional TCF, salt transfer
                 coefficient, and total dissolved solids (TDS) in the
                 feed. To determine the optimized control of the feed
                 water temperature, a new control methodology with the
                 two functional models was proposed and applied to a
                 simulation of the feed water temperature, which showed
                 better performance in terms of the permeate flow rate.
                 Applying the optimized control of feed water
                 temperatures to a plant under identical operational
                 conditions, it was found that the permeate flow rate
                 could be increased by approximately 900 m3/day under a
                 steady condition of 600 ppm in permeate TDS.",
}

Genetic Programming entries for Seung Joon Kim Sanghoun Oh Young Geun Lee Moongu Jeon In S Kim Joon Ha Kim

Citations