상하수도학회지 (Journal of Korean Society of Water and Wastewater)

  • 제35권5호
  • /
  • Pages.351-365
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  • 2021
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  • 1225-7672(pISSN)
  • /
  • 2287-822X(eISSN)
대한상하수도학회 (The Korean Society of Water and Wastewater)
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정수처리공정 시뮬레이터 개발 기초연구

Basic study on development of drinking water treatment process simulators

  • 변용훈 (도화엔지니어링 기술개발연구원) ;
  • 신휘수 (도화엔지니어링 기술개발연구원) ;
  • 김호용 (도화엔지니어링 기술개발연구원) ;
  • 정남정 (도화엔지니어링 기술개발연구원)
  • Byun, Yong-Hoon (Technological Development Department, Dohwa Engineering) ;
  • Shin, Hwi-Su (Technological Development Department, Dohwa Engineering) ;
  • Kim, Ho-Yong (Technological Development Department, Dohwa Engineering) ;
  • Jung, Nahm-Chung (Technological Development Department, Dohwa Engineering)
  • 투고 : 2021.08.09
  • 심사 : 2021.10.08
  • 발행 : 2021.10.15
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초록

Water treatment process simulator is the tool for predicting sequential changes of water quality in a train of unit processes. This predicts the changes through governing equations that represent physicochemical performance of each unit processes with an initial and boundary conditions. Since there is no operational data for the design of a water treatment facility, there is no choice but to predict the performance of the facility by assuming initial and boundary conditions in virtual reality. Therefore, a simulator that can be applied in the design stage of a water treatment facility has no choice but to be built as a numerical analysis model of a deductive technique. In this study, we had conducted basic research on governing equations, inter-process data-flow, and simulator algorithms for the development of simulators. Lastly, this study will contribute to design engineering tool development research in the future by establishing the water treatment theory so that it can be programmed in a virtual world and suggesting a method for digital transformation of the water treatment process.

키워드

과제정보

본 연구는 산업통상자원부 World Class 300 Project(R&D) (P0012997, 기반시설 설계엔지니어링 플랫폼 구축 및 응용프로그램 개발 연구)의 지원을 받았습니다.

참고문헌

  1. Adin, A. and Rebhun, M. (1977). A model to predict concentration and head-loss profiles in filtration, J. Am. Water Works. Assoc., 69(8), 444-453. https://doi.org/10.1002/j.1551-8833.1977.tb06787.x
  2. Amy, G.L., Siddiqui, M., Ozekin, K., Zhu, H.W. and Wang, C. USEPA (1998). Empirically Based Models for Predicting Chlorination and Ozonation By-Product: Haloacetic Acids, Chloral Hydrate, and Bromate, EPA-815-R-98-005.
  3. Bache, D.H. (2004). Floc rupture and turbulence: a framework for analysis, Chem. Eng. Sci., 59(12), 2521-2534. https://doi.org/10.1016/j.ces.2004.01.055
  4. Baker, R.W. (2012). Membrane technology and applications, John Wiley & Sons, Chichester, United Kingdom.
  5. Bosklopper, T.G., Rietveld, L.C., Babuska, R., Smaal, B. and Timmer, J. (2004). Integrated operation of drinking water treatment plant at Amsterdam water supply, Water Sci. Technol.: Water Supply, 4(5-6), 263-270. https://doi.org/10.2166/ws.2004.0116
  6. Brezonik, P. and Arnold, W. (2011). Water chemistry: an introduction to the chemistry of natural and engineered aquatic systems, Oxford University Press, New York.
  7. Cha, T., Prognostics and Health Management, Functionbay. (2020). https://functionbay.com/en/technical-tip/single/274(June 29, 2021).
  8. Choi, D.Y. K-water. (2017). Development of Water Treatment Plant Simulator for Establishing Real-time Operation and Management, KIWE-WWRC-17-03.
  9. Edwards, M. (1997). Predicting DOC removal during enhanced coagulation, J. Am. Water Works. Assoc., 89(5), 78-89. https://doi.org/10.1002/j.1551-8833.1997.tb08229.x
  10. Hack, M. and Kohne, M. (1996). Estimation of wastewater process parameters using neural networks, Water Sci. Technol., 33(1), 101-115. https://doi.org/10.1016/0273-1223(96)00163-1
  11. Hamouda, M.A., Anderson, W.B. and Huck, P.M. (2009). Decision support systems in water and wastewater treatment process selection and design: a review, Water Sci. Technol., 60(7), 1757-1770. https://doi.org/10.2166/wst.2009.538
  12. Head, R., Shepherd, D., Butt, G. and Buck, G. (2002). OTTER mathematical process simulation of potable water treatment, Water Sci. Technol.: Water Supply, 2(1), 95-101.
  13. Huisman, L. (1984). Rapid filtration. 2nd Ed., TU delft, Netherlands.
  14. Hydromantis. (2016). WatPro Version 2 Users' Manual. Supplied with Demonstration Version of WatPro, Hydromantis Environmental Software Solution Inc, Ontario, Canada.
  15. Kim, M.S., Cha, D., Lee, K.M., Lee, H.J., Kim, T. and Lee, C. (2020). Modeling of ozone decomposition, oxidant exposures, and the abatement of micropollutants during ozonation processes, Water Res., 169, 115230. https://doi.org/10.1016/j.watres.2019.115230
  16. MassFlow3. (2013). http://www.massflow.kr/Site/intro_massflow3.aspx, (June 23, 2021).
  17. Parker, D.S., Kaufman, W.J. and Jenkins, D. (1972). Floc breakup in turbulent flocculation processes, J. Sanit. Eng. Div., Am. Soc. Civ. Eng., 98(1), 79-99. https://doi.org/10.1061/JSEDAI.0001389
  18. Van der Helm, A.W.C. and Rietveld, L.C. (2002). Modelling of drinking water treatment processes within the Stimela environment, Water Sci. Technol.: Water Supply, 2(1), 87-93. https://doi.org/10.2166/ws.2002.0011