Uniform flow field design in porous media filter tower and experimental verification
Introduction
Industrial wastewater with heavy metals causes serious environmental problems all over the world. For sustainable use of water resources, it is very import to remove heavy metal ions from wastewaters in industry, mining, and drainage (Ondruschka and Bley, 2003). Filtration adsorption is a universally-adopted method of removing heavy metal ions in wastewater due to the operability and effectiveness (Elangovan et al., 2008).
Filtration is a process in which fine particles are attached to the adsorbent surface under the action of the driving force or other external forces. While wasterwater flow through the filter the heavy metal ions are attached to the adsorbent (Rice et al., 2013; Shomar and Dare, 2015). Fluid’s flow regime has an important influence on the adsorbent efficiency. The bias flow in filter tower results in low filtration efficiency. For this reason, it is necessary to optimize the filter tower paramenters for the flow uniform in porous media filter tower. In the past decades, researchers have studied the influence of filter tower flow field in different conditions. Shahrokhi et al.(2012) carried out a simulation to study the influence of different numbers of plate on flow field characteristics in the filter tower, and Doppler current meter was used to validate the results of the simulation. The results showed that some plates placed in appropriate position can achieve smaller reflux area and flow field relatively uniform. Lopez et al.(2008) studied qualitative streamline in filter tower. Stagnation time was used to trace particles’ flow inlet velocity and flow characteristics in different regions. The flow field characteristics were better at low flow velocity, that is, the flow field can be improved by the controlling inlet velocity. Researchers have analyzed variables such as filter structural and filter parameters, and the flow velocity and pressure were chosen as the main parameters for evaluation of flow field uniformity (Li and Xu, 2017a, 2017b; Escamilla-Ruiz et al., 2017; Tofighi et al., 2017). These findings had provided a reference for the design of filter tower.
Dybbs and Edwards (1984) studied the flow regime in porous media by laser anemometry and flow visualization, and pore-Reynolds was derived based on Darcy’s law and conventionally defined Reynolds numbers. According to the pore scale and pore velocity of porous media, the pore-Reynolds was proposed to interpret the flow regime in porous media. Fluid flow in a porous media exhibits turbulent characteristics when the pore-Reynolds number becomes above 300. In the recent years, techniques such as direct visualization, laser Doppler anemometry, particle image velocimetry and magnetic resonance imaging etc., have been employed to study the fluid flow regimes inside the porous media (Bu et al., 2014). Through direct observation of the fluid flow regimes inside the porous media, a highly unsteady and chaotic flow regime resembiling turbulence can be obserbved when the pore-Reynolds number becomes was 300 (Takatsu and Masuoka, 2005; Lesage et al., 2004; Horton and Pokrajac, 2009). This conclusion has been widely used in the flow field analysis in porous media, and has been verified (Pedras and de Lemos, 2001; Nakayama and Kuwahara, 2008; Yang. et al., 2014; Kundu et al., 2014). In general, the diameter of activated carbon adsorbent used to adsorb heavy metal ions is in millimeter size level. Therefore, according to the experimental results by Alonzo-Garcia et al. (2021) and Lesage et al. (2004), when porosity range in 0.27−0.8 and the particles diameter is millimeter range, flow regimes can be considered as turbulent flow.
Computational fluid dynamics (CFD) has been widely used to solve practical engineering problems and obtained reliable results. The simulation results are reasonable with experiments (Li et al., 2018). Fourati et al.(2013) predicted the liquid dispersion in absorption gas-liquid packed columns by CFD in order to optimize the design of packed columns. It fills the gap of some experimental results which cannot be directly extrapolated by laboratory scale. Wang et al. (2020) simulated liquid seepage process in a coal granular-type porous media with CFD, and showed the effects of pressure, velocity and pore size. In previous works, the flow field of porous media in the filter tower has been studied, and the effects of parameters and flow regime have been obtained. The experiment based on simulation data was conducted to prove the results, and the simulation data was found similar to experimental data by comparison and analysis (Makhmudov et al., 2017; Bai et al., 2017; Sharafutdinov et al., 2017; Ahfir et al., 2017).
Although various kinds of filter flow field analysis have been done, there are many variable factors affecting the flow regime in porous media filter tower, such as inlet flow velocity and inlet diameter. Therefore, it is difficult to get detailed effects of various variables on the flow regime of the filter tower. Moreover, the researchers focus on the design of a optimal filter tower structure and propose a reasonable method to determine flow field parameters. Although CFD simulation geatly reduces the cost for flow field analysis, a reasonable simulation design is conducive to simplified calculation and more accurate simulation results. It is hard to design an effective filter tower structure by conventional methods and experience. It is necessary to porpose a new design method to optimize the filter tower structure parameters, to improve the adsorption efficiency and to meet the need of the actual engeneering.
In this paper, the porous media filter tower simulation model was built to study the hydrodynamics characteristics with the commercial ANSYS CFD 19.1. Firstly, the throttle plate was proved to improve the flow uniformity in the filter tower. Furthermore, based on the CFD simulation model, the optimal parameter configuration of flow uniformity in filter tower was discussed using the monofactor analysis and orthogonal analysis, which were the design methods of mult-objective optimization. According to monofactor analysis and orthogonal analysis, the variable parameters of each CFD simulation were setup reasonablly. Through the flow velocity and pressure variance analysis (ANOVA), an optimal parameter configuration was obtained. Finally, an experiment based on simulation results was performed and the design method fasibility was proved.
Section snippets
Creating the geometry
The first step of numerical simulation with ANSYS-CFD is creating the geometry of the filter tower. The geometry of the filter tower is shown in Fig. 1.
As shown in Fig. 1, where H is the throttle plate position height which is the distance from the top of the main body of the filter tower, D is the filter tower inlet diameter, and v is the inlet flow velocity. The structure of throttle plate was designed based on a simple pressure loss coefficient model for multi-hole orifice (Zhao and Zhang,
Rusults and discussion
In this section, based on the filter tower model built with CFD, corresponding simulation were performed and simulation results were discussed. Firstly, the influences of throttle palte on the flow field uniformity were verified. Futhermore, in order to obtain the optimal filter tower parameters, monofactor analysis and orthogonal analysis were employed to analyze, and the analysis results were set as simulation condition.
Experimental Verification
In order to verify the optimal parameter combination obtained by the previous simulation, the corresponding experiments were performed. The experimental equipment and parameters were reported in Table 7. In order to ensure reliability and accuracy of results, all the parameters of the corresponding experiments were set in the same conditions as those used in previous simulation. 9 measurement points were selected from the 80 previous measurement points because of experimental equipment limited.
Conclusions
Compared with the original filter tower structure, a throttle plate installed in filter tower can solve the bias flow. CFD was used to simulate the flow field in the filter tower based on the RNG k-ε turbulence model. The monofactor analysis and orthogonal analysis were employed to analyze the influence of filter tower structure parameters on flow field. Moreover, to verify the simulation results, the experiments were performed. The following conclusions can be drawn from the this study.
The
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors would like to acknowledge the support by the Science and Technology Base and Talents Special Project of Guangxi Province (Grant No. AD19259002), the Natural Science Foundation of Guangxi Province (Grant No. 2018GXNSFAA180206, and Grant No. 2018GXNSFAA281312), the National Natural Science Foundation of China (Grant No. 51365006).
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