OPTIMIZATION OF THE PROCESS OF SELECTION OF TECHNOLOGIES AND EQUIPMENT FOR PURIFICATION OF WASTEWATER OF ELECTROPLATE PRODUCTION

  • Boris V. Ermolenko Mendeleev University of Chemical Technology of Russia
  • Evgeniy N. Kuzin Mendeleev University of Chemical Technology of Russia
Keywords: water treatment, electrochemical waste water integrated mixed-integer linear programming (MILP), optimization

Abstract

More and more attention is being paid to energy and resource efficiency issues, which is why for existing technological processes the solution of optimization problems comes to the fore in order to optimize material costs. No less important is the assessment of the human resource, as well a minimizing the possibility of errors at the stage of making a decision on the implementation / design of new processes. It is the environmental sphere that is associated with a high degree of investment risks and requires a careful approach to justifying the introduction of environmental technologies. As part of the work done, the concept of automated decision making was proposed and an economic and mathematical model was developed for solving the optimization problem for choosing a technology or equipment for wastewater treatment systems of an enterprise using the example of electrochemical enterprises (electroplating production) at the stage of justifying investments. As the main tool for processing input data, it is proposed to use software systems based on the use of partial-integer linear programming methods. As input parameters of the system, the initial concentrations of pollutants, volume flow and the required cleaning efficiency are selected. The main technologies for the treatment and neutralization of wastewater from galvanic production, which are currently used or included in the list of the best available technologies, are presented, and a model is proposed that allows the choice of methods and instrumentation for multi-stage treatment processes to achieve the required quality of discharged water with minimal integral costs for the creation and operation of the designed system. The proposed mathematical model can be used both as a training tool for training specialists in water treatment, and for management personnel in the process of selecting and justifying environmental protection measures or at the stage of supervision of equipment suppliers.

For citation:

Ermolenko B.V., Kuzin E.N. Optimization of the process of selection of technologies and equipment for purification of wastewater of electroplate production. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 2. P. 111-118. DOI: 10.6060/ivkkt.20246702.6913.

References

Hofman J. The key role of computer modelling in ozone water treatment. Comp. Cont. Eng. 2005. V. 16. N 5. P. 40–45. DOI: 10.1049/cce:20050507.

Worch E. Adsorption Technology in Water Treatment-Fundamentals, Processes, and Modeling, Germany. KG, Berlin: Walter de Gruyter, GmbH & Co. 2012. 345 p. DOI: 10.1515/ 9783110240238.

Garibay-Rodriguez J., Rico-Ramirez V., Ponce-Ortega J.M. A Mixed Integer Programming Model for Sustainable Water Management in Macroscopic Systems. 26th Eur. Symp. on Computer Aided Process Eng. 2016. P. 1839–1844. DOI: 10.1016/b978-0-444-63428-3.50311-8.

De Melo J.J., Câmara A.S. Models for the optimization of regional wastewater treatment systems. Euro. J. Oper. Res. 1994. V. 73. N 1. P. 1–16. DOI: 10.1016/0377-2217(94)90134-1.

Mostafa K.S., Bahareh G., Elahe D., Pegah D. Optimization of conventional water treatment plant using dynamic programming. Toxic Ind. Health. 2013. V. 31. N 12. P. 1078–1086. DOI: 10.1177/0748233713485891.

Boah D., Twum S. A Review of Water Quality Optimization Models and Techniques. J. App. Math.Ph. 2020. V. 8. P. 424-433. DOI: 10.4236/jamp.2020.83032.

Najafzadeh M., Zeinolabedini M. Prognostication of Waste Water Treatment Plant Performance Using Efficient Soft com-puting Models: An Environmental Evaluation. Measurement. 2019. No 138. DOI: 10.1016/j.measurement.2019.02.014.

Kachiashvili K., Gordeziani D., Lazarov R., Melikdzha-nian D. Modelling and Simulation of Pollutants Transport in Rivers. App. Math. Mod. 2007. V. 31. P. 1371–1396. DOI: 10.1016/japm.2006.02.015.

Sarda P., Sadgir P. Water Quality Modeling and Management of Surface Water using Soft Tool. Int. J. Sci. Eng. Tech. R. (IJSETR). 2015. V. 4. N 9. P. 2988-2992.

Shridhara T., Ojoawo S., Mahaganesha P., Thippeswary M., Anand R., Sharath B. C-Language Programming for Development of Conventional Water Treatment Plants Decision Support System. Comp. Water, Energy Environ. Eng. 2014. V. 3. P. 129-139. DOI: 10.4236/cweee.2014.34014.

Allahverdipour P., Sattari M.T. Comparing the performance of the multiple linear regression classic method and modern data mining methods in annual rainfall modeling (Case study: Ahvaz city). Water Soil Manag. Mod. 2023. V. 3(2). P. 125-142. DOI: 10.22098/mmws.2022.11337.1120.

Wang Li, Shen Jie. Modeling water treatment process using fuzzy neural network based on subtractive clustering. 27th Chinese Control Conference. 2008. P. 324-328. DOI: 10.1109/chicc. 2008.4605602.

Finney B.A., Grenney W.J., Bishop A.B., Hughes T.C. Mixed Integer Programming Models for Water Resources Management. Reports. 1977. 492 p. https://digitalcommons. usu.edu/water_rep/492.

Koleva M.N., Polykarpou E.M., Liu S., Styan C.A., Pa-pageorgiou L.G. Synthesis of Water Treatment Processes using Mixed Integer Programming. Comp. Aided Chem. Eng. 2015. P. 1379–1384. DOI: 10.1016/b978-0-444-63577-8.50075-9.

Hanife Dokht Ghayour S., Soleimapour M., Babazadeh R. An integrated mixed-integer linear programming (MILP) model for urban water supply chain optimization. J. App. R. Water Wastewater. 2020. V. 7. N 2. P. 102-110.

Qasem N.A.A., Mohammed R.H., Lawal D.U. Removal of heavy metal ions from wastewater: a comprehensive and critical review. Npj Clean Water. 2021. V. 4(1). 503 p. DOI: 10.1038/s41545-021-00127-0.

Madhavi V., Reddy A.V.B., Reddy K.G., Madhavi G., Prasad T. An overview on research trends in remediation of chromium. Res. J. Rec. Sci. 2013. V. 2. N 1. P. 71–83.

Qin X.Y., Chai M.R., Ju D. Y., & Hamamoto, O. Investigation of plating wastewater treatment technology for chromium, nickel and copper. IOP Conf. Ser.: Earth Environ. Sci. 2018. V. 191. 012006. DOI: 10.1088/1755-1315/191/1/012006.

Sharma D., Chaudhari P.K., Dubey S., Prajapati A.K. Electrocoagulation Treatment of Electroplating Wastewater: A Review. J. Environ. Eng. 2020. V. 146. N 10. 03120009. DOI: 10.1061/(asce)ee.1943-7870.0001790.

Azmi A.A., Jai J., Zamanhuri N.A., Yahya A. Precious Metals Recovery from Electroplating Wastewater: A Review. IOP Conf. Ser.: Mater. Sci. Eng. 2018. V. 358. 012024. DOI: 10.1088/1757-899x/358/1/012024.

Feng N., Sugiura S., Shimada T., Maekawa A. Develop-ment of a high-performance electrochemical wastewater treatment system. J. Hazard. Mater. 2003. V. 103. P. 65-78. DOI: 10.1016/s0304-3894(03)00222-x.

Dermentis K., Christoforidis A., Valsamidou E. Removal of nickel, copper, zinc and chromium from synthetic and industrial wastewater by electro coagulation. Int. J. Environ. Sci. 2011. V. 1. N 5. P. 697-710.

Sun Y. Effects of Ozone on COD Reduction in Electroplating Wastewater. In: Materials Engineering—From Ideas to Prac-tice: An EPD Symposium in Honor of Jiann-Yang Hwang. The Minerals, Metals & Materials Series. Ed. by B. Li et al. Cham: Springer. 2021. P. 241-248. DOI: 10.1007/978-3-030-65241-8_23.

Hewehy M.A., Razek T.M., Hamid M.A., Morsy R.M. Electrochemical Treatment of Electroplating Wastewater Using Carbon and Aluminum Electrodes. J. Environ. Sci. China. 2016. V. 33. P. 25-41. DOI: 10.21608/JES.2016.25102.

Hosseini S.S., Bringas E., Tan N.R., Ortiz I., Ghahramani M., Shahmirzadi M. A. Recent progress in development of high-performance polymeric membranes and materials for metal plating wastewater treatment: A review. J. Water Proc. Eng. 2016. V. 9. P. 78–110. DOI: 10.1016/j.jwpe.2015.11.005.

Peng C., Meng H., Zhang J., Lu S. Treatment of electroplat-ing wastewater. J. Univ. Sci. Technol. 2013. V. 10. P. 8–11.

Kolesnikov A.V., Savel’ev D.S., Kolesnikov V.A., Davydkova T.V. Electroflotation extraction of highly disperse ti-tanium dioxide TiO2 from water solutions of electrolytes. Glass Ceram. 2018. V. 75. N 5-6. P. 237–241. DOI: 10.1007/s10717-018-0063-0.

Kuzin E.N., Chernyshev P.I., Vizen N.S., Krutchinina N.E. The Purification of the Galvanic Industry Wastewater of Chromium (VI) Compounds Using Titanium(III) Chloride. Russ. J. Gen. Chem. 2018. V. 88. N 13. P. 2954–2957. DOI: 10.1134/S1070363218130200.

Medvedeva I.V., Medvedeva O.M., Studenok A.G., Studenok G.A., Tseytlin E.M. New composite materials and processes for chemical, physico-chemical and biochemical technologies of water purification. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2023. V. 66. N 1. P. 6-27. DOI: 10.6060/ivkkt.20236601.6538.

Kuzin E.N., Krutchinina N.E. Evaluation of effectiveness of use of complex coagulants for wastewater treatment processes of mechanical engineering. ChemChemTech [Izv. Vyssh.Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2019. V. 62. N 10. P. 140-146. DOI: 10.6060/ivkkt.20196210.5939.

Kuzin E.N., Kruchinina N.E. Obtaining complex titanium-containing coagulants by the method of chemical dehydration. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2022. V. 65. N 5. P. 103-111. DOI: 10.6060/ivkkt. 20226505.6578.

Published
2023-12-29
How to Cite
Ermolenko, B. V., & Kuzin, E. N. (2023). OPTIMIZATION OF THE PROCESS OF SELECTION OF TECHNOLOGIES AND EQUIPMENT FOR PURIFICATION OF WASTEWATER OF ELECTROPLATE PRODUCTION. ChemChemTech, 67(2), 111-118. https://doi.org/10.6060/ivkkt.20246702.6913
Section
CHEMICAL TECHNOLOGY (inorganic and organic substances. Theoretical fundamentals)