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A systematic model calibration methodology based on multiple errors minimization method for the optimal parameter estimation of ASM1

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Abstract

A one-step model calibration methodology of the activated sludge model no. 1 (ASM1) of a full-scale wastewater treatment plant (WWTP) is proposed. First, the key parameters among all parameters of the ASM1 model are selected by sensitivity analysis based on the effluent quality index. Second, multiple response surface methodology (MRSM) is conducted to find the optimal parameter values of the ASM1 model. Lastly, an MRSM analysis is conducted in order to determine the optimal parameter values. This study was conducted in order to develop a new systematic model calibration methodology that can greatly help the modeler to find the optimal solution by selecting the key parameters and optimizing the parameters. In two case studies of simple activated sludge process and a full-scale plant, the experimental results indicated that the calibrated models can improve the prediction quality of the ASM model and the efficiency of the modeling.

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Authors and Affiliations

  1. Department of Environmental Science and Engineering, Center for Environmental Studies, Kyung Hee University, Seocheon-dong 1, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Korea

    JungJin Lim, MinHan Kim, MinJung Kim, TaeSuk Oh, OnYu Kang, Booki Min & ChangKyoo Yoo

  2. Department of Chemical Engineering, National Institute of Technology (NIT), Tiruchirappalli, 620 015, India

    Ambati Seshagiri Rao

Authors
  1. JungJin Lim
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  2. MinHan Kim
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  3. MinJung Kim
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  4. TaeSuk Oh
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  5. OnYu Kang
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  6. Booki Min
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  7. Ambati Seshagiri Rao
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  8. ChangKyoo Yoo
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Correspondence to ChangKyoo Yoo.

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Lim, J., Kim, M., Kim, M. et al. A systematic model calibration methodology based on multiple errors minimization method for the optimal parameter estimation of ASM1. Korean J. Chem. Eng. 29, 291–303 (2012). https://doi.org/10.1007/s11814-011-0178-2

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  • DOI: https://doi.org/10.1007/s11814-011-0178-2

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