
An improved 1D reactive Burger-Diehl settler model for secondary settling tank denitrification
- Author
- Gamze Kirim, Elena Torfs (UGent) and Peter A. Vanrolleghem
- Organization
- Abstract
- An improved 1D reactive settler model is pursued in order to increase the understanding of reactive settling processes and obtain a better prediction of the nitrogen mass balance in wastewater treatment systems. The developed model is based on the 1D Burger-Diehl settler model with compression function and the Activated Sludge Model No. 1 biological reactions. Specific attention was paid in the model development phase to optimal selection of settling velocity functions and integration of the correct clarifier geometry. A unique measurement campaign was carried out with different operational scenarios to quantify the denitrification in a secondary settling tank. A detailed step-wise calibration effort demonstrated that by choosing an appropriate settling velocity function (power-law structure) and considering the true clarifier geometry allows to accurately capture the biomass concentration profile, total sludge mass, sludge blanket height, and the reaction rates. The resulting model is able to accurately describe total suspended solids (TSS) and nitrate concentration profiles throughout a settling tank under different operational conditions. As such the model can be applied in further scenario analysis and system optimization. Practitioner Points A unique measurement campaign was carried out to obtain detailed data for a reactive settler model development.A 1-D reactive settler model is developed based on the Burger-Diehl framework including ASM1 biokinetics and the clarifier geometry.An extensive calibration and model selection effort was performed. The model accurately predicts measured concentration profiles in the settling tank.The developed model can be integrated in a plant-wide model to properly calculate the nitrogen mass balance of a WRRF.
- Keywords
- WET-WEATHER FLOW, ACTIVATED-SLUDGE, SIMULATION-MODEL, VELOCITY MODEL, CALIBRATION, SELECTION, REMOVAL, IMPACT, clarifier geometry, mathematical modeling, reactive settling, rising, sludge, secondary sedimentation, separation process modeling
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01GSFWE75D7RPRMRGP1JP06F8G
- MLA
- Kirim, Gamze, et al. “An Improved 1D Reactive Burger-Diehl Settler Model for Secondary Settling Tank Denitrification.” WATER ENVIRONMENT RESEARCH, vol. 94, no. 12, 2022, doi:10.1002/wer.10825.
- APA
- Kirim, G., Torfs, E., & Vanrolleghem, P. A. (2022). An improved 1D reactive Burger-Diehl settler model for secondary settling tank denitrification. WATER ENVIRONMENT RESEARCH, 94(12). https://doi.org/10.1002/wer.10825
- Chicago author-date
- Kirim, Gamze, Elena Torfs, and Peter A. Vanrolleghem. 2022. “An Improved 1D Reactive Burger-Diehl Settler Model for Secondary Settling Tank Denitrification.” WATER ENVIRONMENT RESEARCH 94 (12). https://doi.org/10.1002/wer.10825.
- Chicago author-date (all authors)
- Kirim, Gamze, Elena Torfs, and Peter A. Vanrolleghem. 2022. “An Improved 1D Reactive Burger-Diehl Settler Model for Secondary Settling Tank Denitrification.” WATER ENVIRONMENT RESEARCH 94 (12). doi:10.1002/wer.10825.
- Vancouver
- 1.Kirim G, Torfs E, Vanrolleghem PA. An improved 1D reactive Burger-Diehl settler model for secondary settling tank denitrification. WATER ENVIRONMENT RESEARCH. 2022;94(12).
- IEEE
- [1]G. Kirim, E. Torfs, and P. A. Vanrolleghem, “An improved 1D reactive Burger-Diehl settler model for secondary settling tank denitrification,” WATER ENVIRONMENT RESEARCH, vol. 94, no. 12, 2022.
@article{01GSFWE75D7RPRMRGP1JP06F8G, abstract = {{An improved 1D reactive settler model is pursued in order to increase the understanding of reactive settling processes and obtain a better prediction of the nitrogen mass balance in wastewater treatment systems. The developed model is based on the 1D Burger-Diehl settler model with compression function and the Activated Sludge Model No. 1 biological reactions. Specific attention was paid in the model development phase to optimal selection of settling velocity functions and integration of the correct clarifier geometry. A unique measurement campaign was carried out with different operational scenarios to quantify the denitrification in a secondary settling tank. A detailed step-wise calibration effort demonstrated that by choosing an appropriate settling velocity function (power-law structure) and considering the true clarifier geometry allows to accurately capture the biomass concentration profile, total sludge mass, sludge blanket height, and the reaction rates. The resulting model is able to accurately describe total suspended solids (TSS) and nitrate concentration profiles throughout a settling tank under different operational conditions. As such the model can be applied in further scenario analysis and system optimization. Practitioner Points A unique measurement campaign was carried out to obtain detailed data for a reactive settler model development.A 1-D reactive settler model is developed based on the Burger-Diehl framework including ASM1 biokinetics and the clarifier geometry.An extensive calibration and model selection effort was performed. The model accurately predicts measured concentration profiles in the settling tank.The developed model can be integrated in a plant-wide model to properly calculate the nitrogen mass balance of a WRRF.}}, articleno = {{e10825}}, author = {{Kirim, Gamze and Torfs, Elena and Vanrolleghem, Peter A.}}, issn = {{1061-4303}}, journal = {{WATER ENVIRONMENT RESEARCH}}, keywords = {{WET-WEATHER FLOW,ACTIVATED-SLUDGE,SIMULATION-MODEL,VELOCITY MODEL,CALIBRATION,SELECTION,REMOVAL,IMPACT,clarifier geometry,mathematical modeling,reactive settling,rising,sludge,secondary sedimentation,separation process modeling}}, language = {{eng}}, number = {{12}}, pages = {{17}}, title = {{An improved 1D reactive Burger-Diehl settler model for secondary settling tank denitrification}}, url = {{http://doi.org/10.1002/wer.10825}}, volume = {{94}}, year = {{2022}}, }
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