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.

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.

A Methodology for Global Sensitivity Analysis of Activated Sludge Models: Case Study with Activated Sludge Model No. 3 ( ASM 3)

2019 ◽  
Vol 91 (9) ◽  
pp. 865-876
Author(s):  
Dhan Lord B. Fortela ◽  
Kyle Farmer ◽  
Alex Zappi ◽  
Wayne W. Sharp ◽  
Emmanuel Revellame ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Activated Sludge ◽  
Global Sensitivity Analysis ◽  
Activated Sludge Model ◽  
Global Sensitivity ◽  
Activated Sludge Models

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.

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