Published October 31, 2021 | Version v1
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Characteristics of raw water sources and analysis of the optimal model of the mixing process with parameter design in clean water pump installations

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  • 1. University of Lambung Mangkurat

Description

The quality characteristics of raw water sources in the regional integrated drinking water supply system (SPAM) of Banjarbakula were investigated and found to maintain the supply of drinking water quantity and quality in accordance with drinking water standards. The optimum model for the mixing process of raw water and poly aluminum chloride (PAC) and pump stroke for the input of water sources from rivers to obtain a composition setting that is in accordance with the raw water sources of each region in the region was selected and determined. So the optimum parameter setting model between alum water, raw water and pump stroke for each raw water source is known and is regionally integrated as a result of a comprehensive study. The integration of Taguchi parameter design and response surface can complement each other and become two methods that go hand in hand in the process of optimizing clean water products. Parameter design provides a very practical optimization step, the basis for this formation refers to the factorial fractional experimental design. However, the absence of statistical assumptions that follow the stages of analysis makes this method widely chosen by researchers and practitioners. With the experimental design of the raw water mixing process, turbidity such as 5 lt/sec, 10 lt/sec, 15 lt/sec, 20 lt/sec and 25 lt/sec and % PAC concentration 5 ppm, 10 ppm, 15 ppm, 20 ppm and 25 ppm with a pump installation stroke of 5 %, 10 %, 15 %, 20 % and 25 % were used. In the process of adding PAC, always pay attention and observe the behavior of the attractive force of the floating particles (flock). The particles were then subjected to SEM (scanning electron microscopy) to determine the dimensions of the flock grains deposited

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References

  • El-Halwagi, M. M., Hamad, A. A., Garrison, G. W. (1996). Synthesis of waste interception and allocation networks. AIChE Journal, 42 (11), 3087–3101. doi: https://doi.org/10.1002/aic.690421109
  • Ling, T.-Y., Soo, C.-L., Phan, T.-P., Lee, N., Sim, S.-F., Grinang, J. (2017). Assessment of the Water Quality of Batang Rajang at Pelagus Area, Sarawak, Malaysia. Sains Malaysiana, 46 (3), 401–411. doi: https://doi.org/10.17576/jsm-2017-4603-07
  • Wanatabe M dan Ushiyama T. (2002). Characteristic and effective application of polymer coagulant. Tokyo: Kurita Water Industries Ltd.
  • Colloidal Dispersions (2019). Coulson and Richardson's Chemical Engineering, 693–737. doi: https://doi.org/10.1016/b978-0-08-101098-3.00014-7
  • Roussy, J., Chastellan, P., Van Vooren, M., Guibal, E. (2005). Treatment of ink-containing wastewater by coagulation/flocculation using biopolymers. Water SA, 31 (3), 369–376. doi: https://doi.org/10.4314/wsa.v31i3.5208
  • Amuda, O., Amoo, I. (2007). Coagulation/flocculation process and sludge conditioning in beverage industrial wastewater treatment. Journal of Hazardous Materials, 141 (3), 778–783. doi: https://doi.org/10.1016/j.jhazmat.2006.07.044
  • Vigneswaran, S., Visvanathan, C. (1995). Water Treatment Processes: Simple Options. CRC Press, 224.
  • Wang, Y. P., Smith, R. (1994). Wastewater minimisation. Chemical Engineering Science, 49 (7), 981–1006. doi: https://doi.org/10.1016/0009-2509(94)80006-5
  • Baxter, C. W., Stanley, S. J., Zhang, Q., Smith, D. W. (2010). Developing Artificial Neural Network Process Models: A Guide For Drinking Water Utilities. University of Alberta.
  • Wang, Y. P., Smith, R. (1995). Wastewater Minimization with Flowrate Constraints. Chemical Engineering Research and Design, 73, 889–904.
  • Ruhsing Pan, J., Huang, C., Chen, S., Chung, Y.-C. (1999). Evaluation of a modified chitosan biopolymer for coagulation of colloidal particles. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 147 (3), 359–364. doi: https://doi.org/10.1016/s0927-7757(98)00588-3
  • Abu Hassan, M. A., Li, T. P., Noor, Z. Z. (2009). Coagulation and flocculation treatment of wastewater in textile industry using chitosan. Journal of Chemical and Natural Resources Engineering, 4 (1), 43–53. Available at: https://core.ac.uk/download/pdf/11782643.pdf
  • Amokrane, A., Comel, C., Veron, J. (1997). Landfill leachates pretreatment by coagulation-flocculation. Water Research, 31 (11), 2775–2782. doi: https://doi.org/10.1016/s0043-1354(97)00147-4
  • Guibal, E., Roussy, J. (2007). Coagulation and flocculation of dye-containing solutions using a biopolymer (Chitosan). Reactive and Functional Polymers, 67 (1), 33–42. doi: https://doi.org/10.1016/j.reactfunctpolym.2006.08.008
  • Koohestanian, A.., Hosseini, M., Abbasian, Z. (2008). The Separation Method for Removing of Colloidal Particles from Raw Water. American-Eurasian J. Agric. & Environ. Sci., 4 (2), 266–273. Available at: https://www.idosi.org/aejaes/jaes4(2)/20.pdf
  • Chen, X., Chen, G., Yue, P. L. (2000). Separation of pollutants from restaurant wastewater by electrocoagulation. Separation and Purification Technology, 19 (1-2), 65–76. doi: https://doi.org/10.1016/s1383-5866(99)00072-6
  • Stephenson, R., Tennant, B. (2003). New Electrocoagulation Process Treats Emulsified Oily Wastewater at Vancouver Shipyards. Environmental Science & Engineering Magazine. Available at: https://esemag.com/archives/new-electrocoagulation-process-treats-emulsified-oily-wastewater-at-vancouver-shipyards/
  • Gómez-López, M. D., Bayo, J., García-Cascales, M. S., Angosto, J. M. (2009). Decision support in disinfection technologies for treated wastewater reuse. Journal of Cleaner Production, 17 (16), 1504–1511. doi: https://doi.org/10.1016/j.jclepro.2009.06.008
  • Dai, J., Qi, J., Chi, J., Chen, S., Yang, J., Ju, L., Chen, B. (2010). Integrated water resource security evaluation of Beijing based on GRA and TOPSIS. Frontiers of Earth Science in China, 4 (3), 357–362. doi: https://doi.org/10.1007/s11707-010-0120-7
  • Doukas, H., Karakosta, C., Psarras, J. (2010). Computing with words to assess the sustainability of renewable energy options. Expert Systems with Applications, 37 (7), 5491–5497. doi: https://doi.org/10.1016/j.eswa.2010.02.061
  • Abdullah, M. P., Yee, L. F., Ata, S., Abdullah, A., Ishak, B., Abidin, K. N. Z. (2009). The study of interrelationship between raw water quality parameters, chlorine demand and the formation of disinfection by-products. Physics and Chemistry of the Earth, Parts A/B/C, 34 (13-16), 806–811. doi: https://doi.org/10.1016/j.pce.2009.06.014
  • Braglia, M., Frosolini, M., Montanari, R. (2003). Fuzzy TOPSIS approach for failure mode, effects and criticality analysis. Quality and Reliability Engineering International, 19 (5), 425–443. doi: https://doi.org/10.1002/qre.528
  • Ross, P. J. (1999). Taguchi techniques for quality engineering: loss function, orthogonal experiments, Parameter and Tolerance Design. McGraw-Hill.
  • Zang, C., Friswell, M. I., Mottershead, J. E. (2005). A review of robust optimal design and its application in dynamics. Computers & Structures, 83 (4-5), 315–326. doi: https://doi.org/10.1016/j.compstruc.2004.10.007
  • Barrado, E., Vega, M., Pardo, R., Grande, P., Del Valle, J. L. (1996). Optimisation of a purification method for metal-containing wastewater by use of a Taguchi experimental design. Water Research, 30 (10), 2309–2314. doi: https://doi.org/10.1016/0043-1354(96)00119-4
  • Tamjidillah, M., Pratikto, Santoso, P. B., Sugiono (2017). The Model of Optimization for Parameter in the Mixing Process of Water Treatment. Journal of Mechanical Engineering, SI 2 (2), 113–122. Available at: http://jmeche.uitm.edu.my/wp-content/uploads/bsk-pdf-manager/P8_T4_04_278.pdf
  • Tamjidillah, M., Pratikto, P., Santoso, P., Sugiono, S. (2017). The model relationship of wastes for parameter design with green lean production of fresh water. Przegląd Naukowy Inżynieria i Kształtowanie Środowiska, 26 (4), 481–488. doi: https://doi.org/10.22630/pniks.2017.26.4.46