Evaluating the structural identifiability of the parameters of the EBPR sub-model in ASM2d by the differential algebra method.

The calibration of ASMs is a prerequisite for their application to simulation of a wastewater treatment plant. This work should be made based on the evaluation of structural identifiability of model parameters. An EBPR sub-model including denitrification phosphorus removal has been incorporated in ASM2d. Yet no report is presented on the structural identifiability of the parameters in the EBPR sub-model. In this paper, the differential algebra approach was used to address this issue. The results showed that the structural identifiability of parameters in the EBPR sub-model could be improved by increasing the measured variables. The reduction factor eta(NO)(3) was identifiable when combined data of aerobic process and anoxic process were assumed. For K(PP), X(PAO) and q(PHA) of the anaerobic process to be uniquely identifiable, one of them is needed to be determined by other ways. Likewise, if prior information on one of the parameters, K(PHA), X(PAO) and q(PP) of the aerobic process, is known, all the parameters are identifiable. The above results could be of interest to the parameter estimation of the EBPR sub-model. The algorithm proposed in the paper is also suitable for other sub-models of ASMs.

[1]  Keith R. Godfrey,et al.  Structural identifiability of non-linear systems using linear/non-linear splitting , 2003 .

[2]  B. Petersen Calibration, identifiability and optimal experimental design of activated sludge models , 2000 .

[3]  A. Holmberg On the practical identifiability of microbial growth models incorporating Michaelis-Menten type nonlinearities , 1982 .

[4]  E. Kolchin Differential Algebra and Algebraic Groups , 2012 .

[5]  C. Cobelli,et al.  Global Identifiability of Nonlinear Model Parameters , 1997 .

[6]  H P Wynn,et al.  Differential algebra methods for the study of the structural identifiability of rational function state-space models in the biosciences. , 2001, Mathematical biosciences.

[7]  Denis Dochain,et al.  Structural Identifiability of Biokinetic Models of Activated-sludge Respiration , 1995 .

[8]  Claudio Cobelli,et al.  Global identifiability of nonlinear models of biological systems , 2001, IEEE Transactions on Biomedical Engineering.

[9]  Mogens Henze,et al.  Activated Sludge Model No.2d, ASM2D , 1999 .

[10]  K R Godfrey,et al.  Global identifiability of the parameters of nonlinear systems with specified inputs: a comparison of methods. , 1990, Mathematical biosciences.

[11]  S. Mathieu,et al.  Estimation of wastewater biodegradable COD fractions by combining respirometric experiments in various So/Xo ratios , 2000 .

[12]  윤석표 Activated Sludge Model No.2를 이용한 하수의 생물학적 질소·인 제거 공정의 처리성 평가 , 1999 .

[13]  Denis Dochain,et al.  Modeling aerobic carbon source degradation processes using titrimetric data and combined respirometric–titrimetric data: Structural and practical identifiability , 2002, Biotechnology and bioengineering.

[14]  Gürkan Sin,et al.  Discussion of “Assessing Parameter Identifiability of Activated Sludge Model Number 1” by Pedro Afonso and Maria da Conceição Cunha , 2004 .

[15]  Denis Dochain,et al.  A simplified method to assess structurally identifiable parameters in Monod-based activated sludge models. , 2003, Water research.

[16]  Peter Reichert,et al.  Practical identifiability of ASM2d parameters--systematic selection and tuning of parameter subsets. , 2002, Water research.

[17]  花田 茂久,et al.  Activated Sludge Model No.3 (ASM3) へのリン除去モジュールの導入とそのキャリブレーション方法の開発 , 2004 .

[18]  J. Babary,et al.  Theoretical and practical identifiability of a reduced order model in an activated sludge process doing nitrification and denitrification , 1998 .

[19]  Maria Pia Saccomani,et al.  DAISY: A new software tool to test global identifiability of biological and physiological systems , 2007, Comput. Methods Programs Biomed..

[20]  Derin Orhon,et al.  Identification and modelling of aerobic hydrolysis – application of optimal experimental design , 2003 .

[21]  Lennart Ljung,et al.  On global identifiability for arbitrary model parametrizations , 1994, Autom..