The model calibration protocol for parameter estimation of activated sludge model

2008 ◽  
Author(s):  
Won-Young Lee ◽  
Min-Han Kim ◽  
Chang Kyoo Yoo
Keyword(s):  
Parameter Estimation ◽  
Activated Sludge ◽  
Model Calibration ◽  
Activated Sludge Model ◽  
Calibration Protocol

Parameter Estimation and Sensitivity Analysis of an Activated Sludge Model Using Monte Carlo Simulation and the Analyst's Involvement

1993 ◽  
Vol 28 (11-12) ◽  
pp. 219-229 ◽  
Author(s):  
Marcos von Sperling
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Parameter Estimation ◽  
Activated Sludge ◽  
Model Calibration ◽  
Coefficient Of Determination ◽  
Operational Control ◽  
Activated Sludge Model ◽  
Activated Sludge Models

The present work describes an adaptation of the regionalized sensitivity analysis based on Monte Carlo simulations for the parameter estimation and sensitivity analysis of an activated sludge model. The procedure described should be used when observed data are available for the model calibration, which is nevertheless still limited by the problems inherent to activated sludge models (uncertainty and lack of identifiability). The selection between good and bad performance of the model is judged based on the Coefficient of Determination. The application of the procedure to an 11-parameter 4-state dynamic activated sludge model used for operational control was considered satisfactory. The method is simple and yet robust, and the analyst's involvement in the interpretation of the results and decision upon the next steps to be taken increases its controllability.

Model Calibration for the High-Purity Oxygen Activated Sludge Process – Algorithm Development and Evaluation

1993 ◽  
Vol 28 (11-12) ◽  
pp. 163-171 ◽  
Author(s):  
Weibo (Weber) Yuan ◽  
David Okrent ◽  
Michael K. Stenstrom
Keyword(s):  
Activated Sludge ◽  
High Purity ◽  
Model Calibration ◽  
Process Model ◽  
Model Parameters ◽  
Complex Method ◽  
Activated Sludge Process ◽  
Activated Sludge Model ◽  
Kinetic Coefficients ◽  
Calibration Algorithm

A model calibration algorithm is developed for the high-purity oxygen activated sludge process (HPO-ASP). The algorithm is evaluated under different conditions to determine the effect of the following factors on the performance of the algorithm: data quality, number of observations, and number of parameters to be estimated. The process model used in this investigation is the first HPO-ASP model based upon the IAWQ (formerly IAWPRC) Activated Sludge Model No. 1. The objective function is formulated as a relative least-squares function and the non-linear, constrained minimization problem is solved by the Complex method. The stoichiometric and kinetic coefficients of the IAWQ activated sludge model are the parameters focused on in this investigation. Observations used are generated numerically but are made close to the observations from a full-scale high-purity oxygen treatment plant. The calibration algorithm is capable of correctly estimating model parameters even if the observations are severely noise-corrupted. The accuracy of estimation deteriorates gradually with the increase of observation errors. The accuracy of calibration improves when the number of observations (n) increases, but the improvement becomes insignificant when n>96. It is also found that there exists an optimal number of parameters that can be rigorously estimated from a given set of information/data. A sensitivity analysis is conducted to determine what parameters to estimate and to evaluate the potential benefits resulted from collecting additional measurements.

scholarly journals A practical protocol for calibration of nutrient removal wastewater treatment models

2011 ◽  
Vol 13 (4) ◽  
pp. 575-595 ◽  
Author(s):  
Giorgio Mannina ◽  
Alida Cosenza ◽  
Peter A. Vanrolleghem ◽  
Gaspare Viviani
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Nutrient Removal ◽  
Model Calibration ◽  
Wastewater Treatment Plants ◽  
Optimal Parameter ◽  
Model Parameters ◽  
Activated Sludge Model ◽  
Treatment Models ◽  
Glue Method

Activated sludge models can be very useful for designing and managing wastewater treatment plants (WWTPs). However, as with every model, they need to be calibrated for correct and reliable application. Activated sludge model calibration is still a crucial point that needs appropriate guidance. Indeed, although calibration protocols have been developed, the model calibration still represents the main bottleneck to modelling. This paper presents a procedure for the calibration of an activated sludge model based on a comprehensive sensitivity analysis and a novel step-wise Monte Carlo-based calibration of the subset of influential parameters. In the proposed procedure the complex calibration issue is tackled both by making a prior screening of the most influential model parameters and by simplifying the problem of finding the optimal parameter set by splitting the estimation task into steps. The key point of the proposed step-wise procedure is that calibration is undertaken for sub-groups of variables instead of solving a complex multi-objective function. Moreover, even with this step-wise approach parameter identifiability issues may occur, but this is dealt with by using the general likelihood uncertainty estimation (GLUE) method, that so far has rarely been used in the field of wastewater modelling. An example from a real case study illustrates the effectiveness of the proposed methodology. Particularly, a model was built for the simulation of the nutrient removal in a Bardenpho scheme plant. The model was successfully and efficiently calibrated to a large WWTP in Sicily.

Assessment on activated sludge models for acetate biodegradation under aerobic conditions

2009 ◽  
Vol 60 (4) ◽  
pp. 983-994 ◽  
Author(s):  
M. A. Hoque ◽  
V. Aravinthan ◽  
N. M. Pradhan
Keyword(s):  
Parameter Estimation ◽  
Activated Sludge ◽  
Model Calibration ◽  
Aerobic Biodegradation ◽  
Batch Experiments ◽  
Storage Model ◽  
Biodegradation Process ◽  
Ammonia Degradation ◽  
And Storage ◽  
Activated Sludge Models

A comparison of four different established models along with parameter estimation was carried out in order to explain the aerobic biodegradation of acetate in an activated sludge system. These models were investigated using experimental OUR data from batch experiments of three different concentration studies. Model calibration reveals that ASM1 model is not suitable to explain the observed experimental OUR during the famine phase implying storage compounds could play an important role during that stage. Besides, the model corresponds to the accumulation concept and is not well fitted for all concentrations studies though it includes the storage phenomena. Both the ASM3 model and the model for simultaneous storage and growth on substrate can well describe the acetate biodegradation process, however the OUR data alone is not sufficient to justify the suitability of those models. Simulated profiles using the model outputs demonstrate that storage is overestimated while ammonia degradation is underestimated in ASM3 compared to simultaneous growth and storage model. The current study also gives reasonable outcomes related to parameter estimation as compared with previous study which is statistically interpreted in this paper.

Fault Diagnosis System of A2/O Process Based on Parameter Estimation and Expert System

2012 ◽  
Vol 263-266 ◽  
pp. 1647-1651
Author(s):  
Miao Yu ◽  
Feng Pan ◽  
Xiao Feng Lian ◽  
Xiao Ting Li
Keyword(s):  
Parameter Estimation ◽  
Fault Diagnosis ◽  
Expert System ◽  
Activated Sludge ◽  
Sewage Treatment ◽  
Actual Process ◽  
Uncertainty Reasoning ◽  
Diagnosis System ◽  
Activated Sludge Model ◽  
Fault Diagnosis System

For urban sewage treatment process of A2/O, a fault diagnosis method based on parameter estimation of Activated Sludge Model No.2(ASM2) model and expert system is proposed. Firstly, the A2/O process is simulated based on Activated Sludge Model No.2(ASM2) model, according to which, the estimated value of component parameters of biochemical reaction process is obtained, and when it’s compared with the normal value of corresponding parameters, the faults can be detected. Furthermore, an expert system that can draw fault diagnosis results is designed by means of uncertainty reasoning for expert knowledge. Finally, a fault diagnosis system for A2/O process is developed. For a sewage treatment plant of Kunming, experiment result has shown that the fault diagnosis system for A2/O process can make effective diagnosis of the actual process issues, and it has certain engineering practicability.

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