Modeling of the Full-Scale Secondary Sedimentation Basin Using the GPS-X Model

Safi A. Hasan, Basim K. Nile, Ahmed M. Faris

Abstract


The secondary sedimentation basin is being modeled in this study for the first time using the GPS-X model instead of the computational fluid dynamics (CFD) model. This study was conducted in the extended-aeration Al-Hur treatment plant that struggles with unstable sedimentation in its sedimentation tank. After collecting and entering the data into the GPS-X model, the model was calibrated and validated, and the results were statistically examined based on R and RMSE. To determine the efficiency of the sedimentation tank, the following scenarios were investigated: 1) testing the efficiency in removing pollutants; 2) conducting state point analysis (SPA); and 3) measuring the concentration of sludge in the layers of the sedimentation basin. Six factors were considered during the sensitivity analysis, namely sludge volume index (SIV), surface area, underflow rate (RAS), pumped flow (WAS), maximum settling velocity, and liquid temperature. The calibration and validation results were within the specified limits, and the secondary sedimentation basin demonstrated high efficiency in removing pollutants, with the analysis point (SPA) obtaining the highest MLSS concentration of 3000 mg/L. The sludge concentrations in the lower layers were 7000 mg/L, while those in the upper layer were 18 mg/L. These results suggest that a lower (100 ml/g) sludge volume index corresponds to a better sedimentation basin efficiency. Increasing the surface area of sedimentation basins can positively affect their efficiency, while increasing waste-activated sludge, maximum settling velocity, and liquid temperature may reduce pollutants and improve the sedimentation process. The GPS-X model is demonstrated as an excellent tool for understanding and predicting the work behavior of sedimentation basins, making this model particularly valuable for the management of sewage treatment plants.

 

Doi: 10.28991/CEJ-2024-010-09-017

Full Text: PDF


Keywords


Sedimentation; GPS-X; SVI; Maximum Settling Velocity; State Point Analysis.

References


Patziger, M., Kainz, H., Hunze, M., & Józsa, J. (2012). Influence of secondary settling tank performance on suspended solids mass balance in activated sludge systems. Water Research, 46(7), 2415–2424. doi:10.1016/j.watres.2012.02.007.

Li, B., & Stenstrom, M. K. (2013). Research advances and challenges in one-dimensional mathematical modeling of secondary settling tanks—a critical review. 86th Annual Water Environment Federation Technical Exhibition and Conference, WEFTEC 2013, 6, 3934–3952. doi:10.2175/193864713813685458.

Li, B. (2016). One-Dimensional Modeling of Secondary Settling Tanks. The Regents of the University of California, California, United States.

Mashi, A. L., & Rahama, M. S. (2015). Effects of Sludge Settleability in Final Sedimentation Tank. International Journal of Scientific & Engineering Research, 6(7), 2229–5518.

Ekama, G. A., & Marais, P. (2004). Assessing the applicability of the 1D flux theory to full-scale secondary settling tank design with a 2D hydrodynamic model. Water Research, 38(3), 495–506. doi:10.1016/j.watres.2003.10.026.

Hazen, A. (1904). On sedimentation. Transactions of the American Society of Civil Engineers, 53(2), 45-71. doi:10.1061/TACEAT.0001655.

Dick, R. I., & Vesilind, P. A. (1969). The Sludge Volume Index: What Is It? In Journal (Water Pollution Control Federation), 41(7), 1285–1291.

Mursalim, I. A., Pallu, M. S., Selintung, M., & Rahim, I. R. (2021). The effectiveness of increasing the amount of Return Activated Sludge (RAS) in wastewater with a combination biofilter system on bulking parameters. IOP Conference Series: Earth and Environmental Science, 841(1), 12026. doi:10.1088/1755-1315/841/1/012026.

Kriš, J., & Hadi, G. A. (2008). Study the effect of temperature on sedimentation tanks performance. Water Supply and Water Quality. 8th International Scientific and Technical Conference on Water Supply and Water Quality, 439–453.

Raeesh, M., Devi, T. T., & Hirom, K. (2023). Recent Developments on Application of Different Turbulence and Multiphase Models in Sedimentation Tank Modeling—a Review. Water, Air, and Soil Pollution, 234(1), 5. doi:10.1007/s11270-022-06007-8.

Lasaki, B. A., Maurer, P., & Schönberger, H. (2023). Effect of coupling primary sedimentation tank (PST) and microscreen (MS) to remove particulate organic carbon (POC): a study to mitigate energy demand in municipal wastewater treatment plants. Sustainable Environment Research, 33(1), 25. doi:10.1186/s42834-023-00186-7.

Dairi, S., Khoualdia, W., Mrad, D., Bouamrane, A., Djebbar, Y., & Abida, H. (2023). Improving secondary settling tanks performance by applying CFD models for design and operation. Water Supply, 23(6), 2313–2331. doi:10.2166/ws.2023.136.

Wu, X., Wei, J., Shen, L., & Li, X. (2024). Investigation of the Influence of Operating Parameters on the Settling Performance of a Vertical Sedimentation Tank Through Computational Fluid Dynamics Simulations. Water, Air, and Soil Pollution, 235(5), 1–14. doi:10.1007/s11270-024-07110-8.

Poorkarimi, A., Mafakheri, K., & Maleki, S. (2024). Effect of inlet and baffle position on the removal efficiency of sedimentation tank using Flow-3D software. Journal of Hydraulic Structures, 9(4), 76–87.

Hydromantis, E. S. S. (2017). Inc. GPS-X Technical Reference; Hydromantis ESS. In Inc.: Hamilton, ON, Canada.

Faris, A. M., Zwain, H. M., Hosseinzadeh, M., & Siadatmousavi, S. M. (2022). Modeling of novel processes for eliminating sidestreams impacts on full-scale sewage treatment plant using GPS-X7. Scientific Reports, 12(1), 2986. doi:10.1038/s41598-022-07071-0.

Jasim, N. A. (2020). The design for wastewater treatment plant (WWTP) with GPS X modelling. Cogent Engineering, 7(1), 1723782. doi:10.1080/23311916.2020.1723782.

Mannina, G., Cosenza, A., Vanrolleghem, P. A., & Viviani, G. (2011). A practical protocol for calibration of nutrient removal wastewater treatment models. Journal of Hydroinformatics, 13(4), 575–595. doi:10.2166/hydro.2011.041.

Nile, B. K., Faris, A. M., Alesary, H. F., Jafar, N. N. A., Ismail, H. K., Abdulredha, M., Al Juboury, M. F., Hassan, W. H., Ahmed, L. M., Abid, H. R., & Barton, S. (2024). Simulation study of a practical approach to enhance cadmium removal via biological treatment by controlling the concentration of MLSS. Scientific Reports, 14(1), 1714. doi:10.1038/s41598-023-50843-5.

Rice, E. W., Bridgewater, L., & American Public Health Association (Eds.). (2012). Standard methods for the examination of water and wastewater, Volume 10, American Public Health Association, Washington D.C., United States.

Hamad, N. F., Nile, B. K., Alamir, H. T. A., Faris, A. M., Ismail, H. K., Hassan, W. H., Ahmed, L. M., Alesary, H. F., & Barton, S. (2023). Case study of hydrogen sulfide release in the sulfate-rich sewage drop structure. Journal of Water and Climate Change, 14(10), 3713–3725. doi:10.2166/wcc.2023.283.

Al-Amery, Z. M., Alyaseri, I., & Al-Saadi, R. J. (2023). Deterioration of Wastewater Treatment Processes in Iraq: A Case Study from Al-Samawah. AIP Conference Proceedings, 2806(1), 0163663. doi:10.1063/5.0163663.

Takács, I., Patry, G. G., & Nolasco, D. (1991). A dynamic model of the clarification-thickening process. Water Research, 25(10), 1263–1271.

Faris, A. M., Zwain, H. M., Hosseinzadeh, M., Majdi, H. S., & Siadatmousavi, S. M. (2022). Start-up and operation of novel EN-MBBR system for sidestreams treatment and sensitivity analysis modeling using GPS-X simulation. Alexandria Engineering Journal, 61(12), 10805–10818. doi:10.1016/j.aej.2022.04.026.

Hassan, W. H., Faris, A. M., & Faisal, A. A. H. (2024). Using TOXCHEM model for simulation the hydrogen sulfide behavior in a full-scale MBBR process. Desalination and Water Treatment, 317, 100244. doi:10.1016/j.dwt.2024.100244.

Zwain, H. M., Nile, B. K., Faris, A. M., Vakili, M., & Dahlan, I. (2020). Modelling of hydrogen sulfide fate and emissions in extended aeration sewage treatment plant using TOXCHEM simulations. Scientific Reports, 10(1), 22209. doi:10.1038/s41598-020-79395-8.

Zwain, H. M., Faris, A. M., Hassan, W. H., Soomro, S. e. hyde., & Majdi, A. (2024). Modeling the effects of sidestreams recycling on wastewater treatment plant performance operated by anaerobic-anoxic-oxic (A2/O) processes using GPS-X8 simulation. Results in Engineering, 22, 102173. doi:10.1016/j.rineng.2024.102173.

Mu’azu, N. D., Alagha, O., & Anil, I. (2020). Systematic modeling of municipal wastewater activated sludge process and treatment plant capacity analysis using GPS-X. Sustainability (Switzerland), 12(19), 8182. doi:10.3390/su12198182.

Faris, A. M., Nile, B. K., Mussa, Z. H., Alesary, H. F., Al Juboury, M. F., Hassan, W. H., Al-Bahrani, H. A., & Barton, S. (2022). Fate and emission of methyl mercaptan in a full-scale MBBR process by TOXCHEM simulation. Journal of Water and Climate Change, 13(6), 2386–2398. doi:10.2166/wcc.2022.438.

Wang, J., Li, Q., Qi, R., Tandoi, V., & Yang, M. (2015). Sludge bulking impact on relevant bacterial populations in a full-scale municipal wastewater treatment plant. Process Biochemistry, 49(12), 2258–2265. doi:10.1016/j.procbio.2014.08.005.

Nile, B. K., & Faris, A. M. (2018). The effect of MLSS values on removal of COD and phosphorus using control method of return activated sludge concentration. Journal of Engineering and Applied Sciences, 13(22), 9730–9734. doi:10.3923/jeasci.2018.9730.9734.

Amanatidou, E., Samiotis, G., Trikoilidou, E., Pekridis, G., & Taousanidis, N. (2015). Evaluating sedimentation problems in activated sludge treatment plants operating at complete sludge retention time. Water Research, 69, 20–29. doi:10.1016/j.watres.2014.10.061.

Alattabi, A. W., Harris, C. B., Alkhaddar, R. M., Ortoneda-Pedrola, M., & Alzeyadi, A. T. (2019). An investigation into the effect of MLSS on the effluent quality and sludge settleability in an aerobic-anoxic sequencing batch reactor (AASBR). Journal of Water Process Engineering, 30, 100479. doi:10.1016/j.jwpe.2017.08.017.

Ong, S. L. (1992). Effect of measurement error of settling velocity on secondary sedimentation tank design. Water Environment Research, 64(2), 104–110. doi:10.2175/wer.64.2.2.

Metcalf, & Eddy. (2022). Wastewater Engineering: Treatment and Resource Recovery. McGraw Hill Education, New York, United States.

Wells, S. A., & LaLiberte, D. M. (1998). Winter temperature gradients in circular clarifiers. Water environment research, 70(7), 1274-1279. doi:10.2175/106143098X123642.

Alisawi, H. A. O. (2020). Performance of wastewater treatment during variable temperature. Applied Water Science, 10(4), 89. doi:10.1007/s13201-020-1171-x.


Full Text: PDF

DOI: 10.28991/CEJ-2024-010-09-017

Refbacks

  • There are currently no refbacks.




Copyright (c) 2024 Safi Abed Hasan, Basim Khalil Nile, Ahmed Mektoof Faris

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
x
Message