PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Research of the process of biological wastewater treatment under conditions of uneven load of the treatment system

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The main purpose of the article is to develop a multifactorial model for rapid assessment of the efficiency of biological wastewater treatment reactors. A mathematical model of the process of biological wastewater treatment has been developed based on: changes in the concentration of organic contaminants in the bioreactor over time, taking into account the uneven flow of wastewater to the treatment plant, the process of substrate entering the bioreactor (different amounts may enter at different times). The software implementation of the proposed algorithm for solving the corresponding model problem in Python is carried out. The results of computer experiments on the study of the efficiency of wastewater treatment in biological treatment reactors for different operating conditions of facilities are presented. In particular, such processes were considered with taking into account the unevenness of the load, because the maximum cleaning loads are in the morning and in the evening. The task was solved to simulate a real situation and show how cleaning takes place at the maximum load at a certain time of the day. The results obtained will be useful for calculations in the design of biological treatment facilities or in the reconstruction of existing bioreactors for their prospective operation under new operating conditions.
Wydawca
Rocznik
Tom
Strony
32--38
Opis fizyczny
Bibliogr. 25 poz., rys., wykr.
Twórcy
  • National University of Water and Environmental Engineering, Institute of Energy, Automatics and Water Management, Department of Automation, Electrical Engineering and Computer-integrated Technologies, 11 Soborna St, 33028, Rivne, Ukraine
autor
  • National University of Water and Environmental Engineering, Institute of Energy, Automatics and Water Management, Department of Automation, Electrical Engineering and Computer-integrated Technologies, 11 Soborna St, 33028, Rivne, Ukraine
  • National University of Water and Environmental Engineering, Institute of Energy, Automatics and Water Management, Department of Automation, Electrical Engineering and Computer-integrated Technologies, 11 Soborna St, 33028, Rivne, Ukraine
  • National University of Water and Environmental Engineering, Institute of Energy, Automatics and Water Management, Department of Automation, Electrical Engineering and Computer-integrated Technologies, 11 Soborna St, 33028, Rivne, Ukraine
  • Rivne State University of Humanities, Faculty of Mathematics and Informatics, 31 Plastova St, 33000, Rivne, Ukraine
Bibliografia
  • Brockmann, D. et al. (2021) “Wastewater treatment using oxygenic photogranule-based process has lower environmental impact than conventional activated sludge process,” Bioresource Technology, 319, 124204. Available at: https://doi.org/10.1016/j.biortech.2020.124204.
  • Chan, Y.J. et al. (2009) “A review on anaerobic–aerobic treatment of industrial and municipal wastewater,” Chemical Engineering Journal, 155, pp. 1–18. Available at: https://doi.org/10.1016/j.cej.2009.06.041.
  • Chang, P. et al. (2023) “Multi-objective Pigeon-inspired optimized feature enhancement soft-sensing model of wastewater treatment process,” Expert Systems with Applications, 215, 119193. Available at: https://doi.org/10.1016/j.eswa.2022.119193.
  • Dette, H. et al. (2005) “Robust and efficient design of experiments for the Monod model,” Journal of Teoretical Biology, 234(4), pp. 537–550. Available at: https://doi.org/10.1016/j.jtbi.2004.12.011.
  • Ghangrekar, M.M. and Shinde, V.B. (2007) “Performance of membrane-less microbial fuel cell treating wastewater and effect of electrode distance and area on electricity production,” Bioresource Technology, 98(15), pp. 2879–2885. Available at: https://doi.org/10.1016/j.biortech.2006.09.050.
  • Han, H. et al. (2023) “Dynamic–static model for monitoring waste-water treatment processes,” Control Engineering Practice, 132, 105424. Available at: https://doi.org/10.1016/j.conengprac.2022.105424.
  • Jiménez-García, G. and Maya-Yescas, R. (2019) “Mathematical modeling of mass transport in partitioning bioreactors,” in S. Huerta-Ochoa, C.O. Castillo-Araiza, G. Quijano (eds.) Advances in Chemical Engineering. Advances and Applications of Partitioning Bioreactors: Vol. 54. Cambridge, San Diego, Oxford, London: Elsevier, pp. 53–74. Available at: https://doi.org/10.1016/bs.ache.2019.01.001.
  • Kazemi, P. et al. (2021) “Data-driven techniques for fault detection in anaerobic digestion process,” Process Safety and Environmental Protection, 146, pp. 905–915. Available at: https://doi.org/10.1016/j.psep.2020.12.016.
  • Li, Q. et al. (2015) “Kinetic characterization of thermophilic and mesophilic anaerobic digestion for coffee grounds and waste activated sludge,” Waste Management, 36, pp. 77–85. Available at: https://doi.org/10.1016/j.wasman.2014.11.016.
  • Maaz, M. et al. (2019) “Anaerobic membrane bioreactors for waste-water treatment: Novel configurations, fouling control and energy considerations,” Bioresource Technology, 283, pp. 358–372. Available at: https://doi.org/10.1016/j.biortech.2019.03.061.
  • Narayanan, C. (2012) “Production of phosphate rich biofertiliser using vermicompost and anaerobic digester sludge,” Advances in Chemical Engineering and Science, 2, pp. 187–191.
  • Narayanan, C. and Biswas, S. (2016) “Studies on waste water treatment in three phase semifluidized bed bioreactors: Computer aide analysis and software development,” Journal of Modern Chemistry & Chemical Technology, 7, pp. 1–21.
  • Oehmen, A. et al. (2007) “Advances in enhanced biological phosphorus removal: From micro to macro scale,” Water Research, 41, pp. 2271–2300. Available at: https://doi.org/10.1016/j.watres.2007.02.030.
  • Safonyk, A. and Bomba, A. (2018) “Mathematical simulation of the process of aerobic treatment of wastewater under conditions of diffusion and mass transfer perturbations,” Journal of Engineering Physics and Thermophysics, 91, pp. 318–323. Available at: https://doi.org/10.1007/s10891-018-1751-x.
  • Safonyk, A., Bomba, A. and Tarhonii, I. (2018) “Modeling and automation of the electrocoagulation prcocess in water treatment,” Advances in intelligent systems and computing III, 871, pp. 451–463. Available at: https://doi.org/10.1007/978-3-030-01069-0_32.
  • Safonyk, A., Martynov, S. and Kynytskyi, S. (2019) “Modeling of the contact removal of iron from groundwater,” International Journal of Applied Mathematics, 32(1), pp. 71–82. Available at: https://doi.org/10.12732/ijam.v32i1.7.
  • Safonyk, A., Zhukovskyy, V. and Burduk, A. (2020) “Modeling of biological wastewater treatment process taking into account reverse effect of concentration on diffusion coefficient,” 2020 10th International Conference on Advanced Computer Information Technologies (ACIT), pp. 29–34. Available at: https://doi.org/10.1109/acit49673.2020.9208814.
  • Sánchez-Fernández, A. et al. (2018) “Fault detection based on time series modeling and multivariate statistical process control,” Chemometrics and Intelligent Laboratory Systems, 182, pp. 57–69. Available at: https://doi.org/10.1016/j.chemolab.2018.08.003.
  • Wang, G. et al. (2023) “Activated carbon enhanced traditional activated sludge process for chemical explosion accident wastewater treatment,” Environmental Research, 225, 115595. Available at: https://doi.org/10.1016/j.envres.2023.115595.
  • Wang, R. et al. (2022) “Study on the hydrodynamic performance and treatment effect of a modified biological carrier in wastewater treatment,” Science of The Total Environment, 844, 156974. Available at: https://doi.org/10.1016/j.scitotenv.2022.156974.
  • Xiao, H. et al. (2017) “Fault diagnosis and prognosis of wastewater processes with incomplete data by the auto-associative neural networks and ARMA model,” Chemometrics and Intelligent Laboratory Systems, 161, pp. 96–107. Available at: https://doi.org/10.1016/j.chemolab.2016.12.009.
  • Yun, Y.-M. et al. (2019) “Sulfate reducing bacteria-based wastewater treatment system integrated with sulfide fuel cell for simultaneous wastewater treatment and electricity generation,” Chemosphere, 233, pp. 570–578. Available at: https://doi.org/10.1016/j.chemosphere.2019.05.206.
  • Zabot, G. et al. (2011) “Hybrid modeling of xanthan gum bioproduction in batch bioreactor,” Bioprocess and Biosystems Engineering, 34, pp. 975–86. Available at: https://doi.org/10.1007/s00449-011-0548-5
  • Zarei, S. et al. (2021) “Three-dimensional CFD simulation of anaerobic reactions in a continuous packed-bed bioreactor,” Renewable Energy, 169, pp. 461–472. Available at: https://doi.org/10.1016/j.renene.2021.01.029.
  • Zhang, H. et al. (2015) “Calcium effect on the metabolic pathway of phosphorus accumulating organisms in enhanced biological phosphorus removal systems,” Water Research, 84, pp. 171–180. Available at: https://doi.org/10.1016/j.watres.2015.07.042.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e11186f9-99b4-4326-92fc-dc269aebc296
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.