3D MODELING OF BIOLOGICAL WASTEWATER TREATMENT IN AERATION TANK

M. M. Biliaiev; M. V. Lemesh; O. Y. Gunko; V. O. Zadoia; P. B. Mashykhina; Z. M. Yakubovska

doi:10.15802/stp2020/224619

Authors

M. M. Biliaiev Dnipro National University of Railway Transport named after Academician V. Lazaryan, Ukraine https://orcid.org/0000-0002-1531-7882
M. V. Lemesh Dnipro National University of Railway Transport named after Academician V. Lazaryan, Ukraine https://orcid.org/0000-0002-1230-8040
O. Y. Gunko Dnipro National University of Railway Transport named after Academician V. Lazaryan, Ukraine https://orcid.org/0000-0001-9257-763X
V. O. Zadoia Dnipro National University of Railway Transport named after Academician V. Lazaryan, Ukraine https://orcid.org/0000-0001-9408-4978
P. B. Mashykhina Dnipro National University of Railway Transport named after Academician V. Lazaryan, Ukraine https://orcid.org/0000-0003-3057-9204
Z. M. Yakubovska Ukrainian State University of Chemical Technology, Ukraine https://orcid.org/0000-0002-9893-3479

DOI:

https://doi.org/10.15802/stp2020/224619

Keywords:

water treatment, biological water treatment, mathematical modeling, aeration tank, Monod model

Abstract

Purpose. The main purpose of the article is to develop a 3D CFD model for modeling the process of biological wastewater treatment in an aeration tank. Methodology. For mathematical modeling of the process of biological wastewater treatment in the reactor, taking into account the flow hydrodynamics, geometric shape of the aeration tank, convective-diffusion transfer of the substrate and activated sludge, a 3D CFD model was built. The model is based on the three-dimensional equation of motion of an ideal liquid and the equation of mass conservation for the substrate, activated sludge. The field of sewage flow rate in the aeration tank is calculated based on the velocity potential equation. The process of biological transformation of the substrate is calculated on the basis of the Monod model. The splitting scheme was used for numerical integration of the equations of convective-diffusion transfer of activated sludge and substrate. The splitting is carried out in such a way to take into account the transfer of substrate (activated sludge) in only one direction at each step of splitting. The calculation of the unknown value of the substrate (activated sludge) concentration is carried out according to an explicit scheme. The Richardson method is used to numerically integrate the three-dimensional equation for the velocity potential, and the unknown value of the velocity potential is calculated by an explicit formula. Euler's method is used for numerical integration of equations describing the process of substrate transformation and change in activated sludge concentration (Monod model). Findings. The software implementation of the constructed 3D CFD model is carried out. A description of the structure of the developed software package is provided. The results of a computer experiment to study the process of wastewater treatment in an aeration tank with additional elements are presented. Originality. A new multifactor 3D CFD model has been developed, which allows quick assessing the efficiency of biological treatment in an aeration tank. Practical value. The constructed 3D CFD model can be used to analyze the efficiency of the aeration tank under different operating conditions at the stage of sketch design of wastewater treatment systems.

References

Biliaiev, N. N., & Kozachina, V. A. (2015). Modelirovaniye massoperenosa v gorizontalnykh otstoynikakh: mono-grafiya. Dnepropetrovsk: Aktsent PP. (in Russian)

Biliaiev, N. N., & Nagornaya, E. K. (2012). Matematicheskoye modelirovaniye massoperenosa v otstoynikakh sistem vodootvedeniya: monografiya. Dnepropetrovsk: Novaya ideologiya. (in Russian)

Vasilenko, O. A., Grabovskiy, P. O., Larkina, G. M., Polishchuk, O. V., & Progulny, V. Y. (2010). Rekonstruktsiya i intensyfikatsiya sporud vodopostachannya ta vodovidvedennya: navchalnyy posibnyk. Kyiv: IVNVKP «Ukrgeliotek». (in Ukrainian)

Karelin, Ya. A., Zhukov, D. D., Zhurov, V. N., & Repin, B. N. (1973). Ochistka proizvodstvennykhstochnykh vod v aerotenkakh. Moscow: Stroyizdat. (in Russian)

Laskov, Yu. M., Voronov, Yu. V., & Kalitsun, V. I. (1981). Primery raschetov kanalizatsionnykh sooruzheniy. Moscow: Vysshaya shkola. (in Russian)

Oleynik, A. Y., & Airapetyan, T. S. (2015). The modeling of the clearance of waste waters from organic pollutions in bioreactors-aerotanks with suspended (free flow) and fixed biocenoses. Reports of the National Academy of Sci-ences of Ukraine, 5, 55-60. DOI: https://doi.org/10.15407/dopovidi2015.05.055 (in Ukrainian)

Alharbi, A. O. M. (2016). The biological treatment of wastewater: mathematical models. Bulletin of the Australian Mathematical Society, 94(2), 347-348. DOI: https://doi.org/10.1017/S0004972716000411 (in English)

Amaral, A., Gillot, S., Garrido-Baserba, M., Filali, A., Karpinska, A. M., Plósz, B. G., … Rosso, D. (2019). Modelling gas–liquid mass transfer in wastewater treatment: when current knowledge needs to encounter engineering practice and vice versa. Water Science and Technology, 80(4), 607-619. DOI: https://doi.org/10.2166/wst.2019.253 (in English)

Babaei, A. A., Azadi, R., Jaafarzadeh, N., & Alavi, N. (2013). Application and kinetic evaluation of upflow anaero-bic biofilm reactor for nitrogen removal from wastewater by Anammox process. Iranian Journal of Environmental Health Science and Engineering, 10(1), 1-8. DOI: https://doi.org/10.1186/1735-2746-10-20 (in English)

Bomba, A., Klymiuk, Y., Prysiazhniuk, I., Prysiazhniuk, O., & Safonyk, A. (2016). Mathematical modeling of wastewater treatment from multicomponent pollution by through microporous filling. AIP Conference Proceedings, 1773, 040003-1-040003-11. DOI: https://doi.org/10.1063/1.4964966 (in English)

Dapelo, D., & Bridgeman, J. (2020). A CFD strategy to retrofit an anaerobic digester to improve mixing perfor-mance in wastewater treatment. Water Science and Technology, 81(8), 1646-1657. DOI: https://doi.org/10.2166/wst.2020.086 (in English)

Gao, H., & Stenstrom, M. K. (2019). Development and applications in computational fluid dynamics modeling for secondary settling tanks over the last three decades: A review. Water Environment Research, 92(6), 796-820. DOI: https://doi.org/10.1002/wer.1279 (in English)

Gao, H., & Stenstrom, M. K. (2020). Influence of Model Parameters and Inlet Turbulence Boundary Specification Methods in Secondary Settling Tanks: Computational Fluid Dynamics Study. Journal of Environmental Engineer-ing, 146(5), 04020028-1-04020028-12. DOI: https://doi.org/10.1061/(ASCE)EE.1943-7870.0001689 (in English)

Gao, H., & Stenstrom, M. K. (2020). Computational Fluid Dynamics Analysis for Improving Secondary Settling Tank Performance. World Environmental and Water Resources Congress 2020, 212-224. DOI: https://doi.org/10.1061/9780784482988.021 (in English)

Griborio, A. (2004). Secondary Clarifier Modeling: A Multi-Process Approach. Dissertation and Theses. University of New Orleans: USA. (in English)

Mocanu, C. R., & Mihaillescu, R. (2012). Numerical Simulation Wastewater Treatment Aeration Processes. U. P. B. Sci. Bull., Series D, 74(2), 191-198. (in English)

Pereda, M., & Zamarreno, J. M. (2011). Agent–based modeling of an activated sludge process in batch reactor. 19th Mediterrian Conference on Control and Automation Aquis (рр. 1128-1133). DOI: https://doi.org/10.1109/med.2011.5983027 (in English)