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Modeling of the Aeration System of a Sequencing Batch Reactor

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Modeling of the Aeration System of a Sequencing Batch Reactor Journal of Ecological Engineering Received: 2020.07.15 Revised: 2020.07.30 Volume 21, Issue 7, October 2020, pages 249–256 Accepted: 2020.08.15 Available online: 2020.08.25 https://doi.org/10.12911/22998993/126240 Modeling of the Aeration System of a Sequencing Batch Reactor Jacek Zaburko1, Radosław Głowienka1, Marcin K. Widomski1*, Joanna Szulżyk-Cieplak2, Roman Babko3, Grzegorz Łagód1 1 Lublin University of Technology, Faculty of Environmental Engineering, Nadbystrzycka 40B, 20-618 Lublin, Poland 2 Lublin University of Technology, Faculty of Fundamentals of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland 3 Schmalhausen Institute of Zoology National Academy of Sciences of Ukraine, B. Khmelnitsky 15, 01030 Kyiv, Ukraine * Corresponding author’s e-mail: [email protected] ABSTRACT The use of modern methods as well as modeling and simulation tools in the design of bioreactors allows for the analysis of the flow phenomena in a short period of time without the need of physical model preparation, and thus for the optimization of existing solutions. The article presents the simulations of the aeration process in an SBR- type bioreactor, realized by means of computational fluid dynamics (CFD) and ANSYS 12.1 software. The subject of the analysis was a diffuser of own design. The Design Modeler 12.1 module was used for the preparation of geometry representing the analyzed design, and the discretization of the continuous domain was carried out with the ANSYS Meshing 12.1 tool. The ANSYS Fluent 6.3 solver was used For model calculations. On the basis of the results obtained from the conducted simulations, it is possible to predict the parameters which will increase ef- ficiency and effectiveness without the need to build a real set of prototype models of aeration systems. The results obtained indicate that an increase in the aeration velocity results in a decrease in the minimum Y-axis velocity for both the mixture and air. The observed differences are caused by the shape of the geometric model and the velocity of the air outlet through the openings, which affects the hydraulic process in the chamber. These processes affect both the amount of oxygen dissolved in the bioreactor and the behavior of the suspension in volume. The turbu- lence intensity during the aeration process is concerned mainly in the range from 3.9 to 8.7% and is comparable with the average values of turbulence degree obtained by other researchers. The air bubble diameter ranged from 0.3 to 4.5 mm, in the case of aeration velocity 5.68 cm/s, a significant part of the chamber were air bubbles with a diameter of 2.6 to 3.9 mm, i.e. they were not the limit values. Keywords: modeling of aeration, CFD simulations, SBR INTRODUCTION of several successive cycles usually lasting from several to more than ten hours. The work of the Computer modeling can be used in the design bioreactor is a cyclical process in which succes- of the aeration systems utilized in activated sludge sive phases such as filling, mixing, aeration, sedi- bioreactors [Vanhooren, et al. 2003, Pittoors et mentation and decantation are distinguished. The al., 2014, Sytek-Szmeichel et al., 2016, Hreiz et activated sludge organisms that convert the or- al., 2019]. A biological reactor working in a batch ganic and biogenic compounds into own biomass, system (SBR – sequencing batch reactor) is one gaseous products and water play a key role dur- of the ways to use the activated sludge technology ing the biological decomposition of the pollutants [Singh et al., 2011, Babko et al., 2017]. The pro- contained in wastewater [Hartman, 1996, Babko cesses occurring during the wastewater treatment et al., 2014, Cydzik-Kwiatkowska et al., 2016]. take place sequentially in one tank and consist In order to ensure the right working conditions 249 Journal of Ecological Engineering Vol. 21(7), 2020 for the organisms, the necessary component sup- et al., 2018]. From an economic point of view, plied during the aeration phase must be the right it is reasonable to use computer simulations, be- amount of oxygen for the proper conduct of bio- cause it allows designing and pre-testing a new chemical processes [Traoré et al., 2005, Sobotka structure by calculation, eliminating the need to et al., 2015, Tang et al., 2019]. According to the build many prototypes of the modelled device. literature, the average demand for activated sludge The results obtained at the stage of simulations for oxygen is 2mg O2/l to ensure proper condi- allow for the preparation of a pre-verified set of tions for the nitrification process [Drewnowski, construction solutions, reducing the time neces- 2019, Zhang et al., 2019]. Aeration time depends sary to carry out more under in real conditions or on the composition of the wastewater, the con- on laboratory scale devices to the minimum. dition of the activated sludge and the required This article presents modeling of the aeration treatment efficiency. [Yahi et al., 2014, Haberm- device – diffuser – and the process in the lab- acher et al., 2015] Good effects are obtained by scale sequencing batch reactor (SBR) implement- using alternating aeration so that unit processes ed with the help of computational fluid dynamics can take place under changing oxygen conditions (CFD) and ANSYS FLUENT software. [Witkowska, 2006, Makowska et al., 2009, Ber- nat et al., 2013, Zhang et al., 2017, Łagód, et al., 2019]; hence, the aeration phase was recognized MATERIALS AND METHODS as the most important part of the bioreactor work cycle [Drewnowski et al., 2019]. The effective- The subject of the research is an inverted T- ness of the aeration process largely depends on shaped diffuser with 1 mm diameter holes char- the use of an appropriate oxygen supply system to acterized by 1% turbulence intensity generated the bioreactor, which includes blowers, pipelines, in the form of a geometric model that has been throttles and diffusers [Drewnowski et al., 2018, discretized in a preprocessor. The model cross- Drewnowski et al., 2019, Rosso et al., 2008, Wag- sections are presented in Figure 1. ner et al., 2002, Piotrowski et al., 2019]. The op- The following physicochemical proper- timal choice is, therefore, an aeration system with ties of liquids and air at 20°C were introduced low energy consumption and high efficiency [Leu to the FLUENT Database program: water den- et al., 2009, Łagód et al., 2019, Drewnowski et al., sity − 998.2 kg/m3, air density − 1.225 kg/m3, 2019]. Owing to the use of computer simulations, water viscosity − 0.001003 kg/(m∙s), air viscos- in a short time it is possible to obtain the knowl- ity − 1.7894 ∙ 10–5 kg/(m ∙ s), surface tension edge of the mechanisms and hydraulic processes − 0.0725 N/m. occurring in the bioreactor chamber, taking into The simulations were carried out for four air account the way aeration systems work based on outlet velocities from the diffuser openings and real data under various operating conditions, and for two cross-sections of the geometric model. enables accurate analyses regarding fluid flow or The air outlet velocities were 3 cm/s, 5.68 cm/s, energy exchange [Fayolle et al., 2007, Karpińska 9 cm/s and 12 cm/s. While conducting the simu- et al., 2017]. Modelling CFD (computational lations, the following parameters were focused fluid dynamics) allows predicting which changes upon: in a given project will increase the performance • average velocity values (for mixture, water, without having to modify or install physical sys- air), tems. The numerical methods and systems on • velocity values in the direction of the Y axis which CFD modeling is based are constantly im- (for mixture and air), proved, which is why the simulation results are • turbulence intensity (for the mixture), becoming more and more reliable. The use of the • diameter of air bubbles. numerical method of fluid mechanics also allows optimizing the designed structure, and thus gen- The research was based on the Realizable erate the material and energy savings, leading to K-Εpsilon turbulence model for a two-dimen- the reduction of the negative environmental im- sional object using a double precision solver (due pact of various devices and machines, improve- to two phases: water and air). This model predicts ment of their safety and performance as well as the behavior and performance of flat and round shortening the time of preparing a new structure outflows, and provides better flow simulation re- [Małecka et al., 2011, Yang et al., 2011, Alizadeh sults, taking into account boundary layer rotation 250 Journal of Ecological Engineering Vol. 21(7), 2020 Figure 1. Model cross-sections (a, b) made with the DESIGN MODELER tool under severely adverse pressure gradients, sepa- The values of the model constants are as ration and circulation [Zhang et al., 2019]. follows: s s The transport equations for kinetic energy of C1ε = 1.44, C2 = 1.9, k = 1.0, ε = 1.2. turbulence – k and dissipation and energy – ε take the form of [Cable, 2009]: k turbulent kinetic energy RESULTS AND DISCUSSION k k ku t G G Tables Y 1S and 2 summarize the results obtained t x j x x k b M k j j k j (1) after the simulation in the FLUENT module. On t k the basis of Tables 1 and 2, an overall increase in k ku j Gk Gb YM Sk t x j x j k x j the average mixture and water velocity, velocity ε dissipation on the Y axis for the mixture, and mixture tur- bulence intensity with an increase in the outlet 2 t velocity of air from the diffuser openings can be u j C1S C2 C1 C3 Gb S t x j x j x j seen.k The differencesk between the average veloc- (2) 2 ity of the mixture and the water are very small t u j C1S C2 C1 C3 Gb S – they appear only in the thousandth part.
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