Dynamical Modelling &amp; Estimation in Wastewater Treatment Processes

Dochain, Denis; Vanrolleghem, Peter

doi:10.2166/9781780403045

Cited by 167 publications

(164 citation statements)

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“…All measurements were carried out according to standard methods (APHA, 2005) within one week after the sample collecting. The measured data were evaluated by Student's t-test paired with the F-test to determine the statistical significance of the observed differences between the measured data for DO, ammonia, nitrate and nitrite at the 95% confidence level (Dochain and Vanrolleghem, 2001). After that, the average values were used for model calibration and validation.…”

Section: Sampling and Analysismentioning

confidence: 99%

CFD simulation and optimization of membrane scouring and nitrogen removal for an airlift external circulation membrane bioreactor

Yang

Wei

Zheng

et al. 2016

Bioresource Technology

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Section: Sampling and Analysismentioning

confidence: 99%

CFD simulation and optimization of membrane scouring and nitrogen removal for an airlift external circulation membrane bioreactor

Yang

Wei

Zheng

et al. 2016

Bioresource Technology

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“…Recently, the Good Modeling Practice (GMP) task group from IWA have emphasized that a standardized modeling procedure is needed to distinguish parameter subset that is identifiable with the available data for experience-based approaches 28 . Systematical analysis approaches have attracted much more attention 15,18,[29][30][31][32] , which mainly consist of parameter identification, sensitivity analysis, and error propagation 32 . Conventional parameter subset identifiability analyzing methods are mainly based on the local sensitivity analysis 21,22 .…”

mentioning

confidence: 99%

A Novel Protocol for Model Calibration in Biological Wastewater Treatment

Zhu¹,

Guo²,

Ni³

et al. 2016

Environmental Engineering and Activated Sludge Processes

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Activated sludge models (ASMs) have been widely used for process design, operation and optimization in wastewater treatment plants. However, it is still a challenge to achieve an efficient calibration for reliable application by using the conventional approaches. Hereby, we propose a novel calibration protocol, i.e. Numerical Optimal Approaching Procedure (NOAP), for the systematic calibration of ASMs. The NOAP consists of three key steps in an iterative scheme flow: i) global factors sensitivity analysis for factors fixing; ii) pseudo-global parameter correlation analysis for non-identifiable factors detection; and iii) formation of a parameter subset through an estimation by using genetic algorithm. The validity and applicability are confirmed using experimental data obtained from two independent wastewater treatment systems, including a sequencing batch reactor and a continuous stirred-tank reactor. The results indicate that the NOAP can effectively determine the optimal parameter subset and successfully perform model calibration and validation for these two different systems. The proposed NOAP is expected to use for automatic calibration of ASMs and be applied potentially to other ordinary differential equations models.A ctivated sludge is the most widely used biological technology for treating domestic and industrial wastewater. After its development with 100 years of history, many novel and modified processes have been developed to meet the more and more stringent discharge and emission limits. However, most of operating systems are suffering some drawbacks, such as substantial energy consumption, excessive greenhouse gas emission, and labour-intensive industry. As a powerful tool, Activated Sludge Models (ASMs) have proven to be very useful in process design, operation and optimization 1,2 . To date, ASMs for the simulation of biological nutrients removal processes have been updated from the first version of ASM1 to more complicated extensions, including ASM2, ASM2d, and ASM3 3 , and further to the extended ASM3s 4-10 in order to satisfy various requirements.However, ASMs are large and overparameterized models in terms of having many stoichiometric and kinetic parameters. Some of the model parameters as well as the model structure have to be adjusted, since microbial community structure and dominant species can vary in different wastewater treatment systems with different influent characteristics or operation schemes 6,7,[11][12][13][14] . In addition, the collected data from full-scale plants as well as pilot-or lab-scale reactors can hardly provide reliable estimations of all the parameters simultaneously due to the well-known problem of poorly identifiable parameters [15][16][17][18][19][20] . Thus, the approach to properly select the subsets of parameters for model calibration plays a crucial role on simulation results and model applications [21][22][23][24][25] . Until now, substantial studies have been conducted to develop effective model calibration approaches, which can be distinguished into two m...

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“…However, such manual parameter fitting can be technically tedious and time-consuming, does not provide a unique optimal set of parameters, is not scientifically robust, and does not quantify parameter uncertainty (Dochain et al 2001, Donoso-Bravo et al 2011. The selection of minerals to include in a model is typically based on prior experience (Musvoto et al 2000a), and/or on equilibrium predictors (e.g.…”

Section: Minerals Precipitation Modelling Approachmentioning

confidence: 99%

“…Further, chemical equilibrium predictors do not capture kinetic effects (Wiechers et al 1975). An alternative method is based on statistical model analysis, whereby a precipitating mineral is included in a model if its kinetic parameter value is significantly different from zero , Dochain et al 2001, Donoso-Bravo et al 2011. A combination of prior knowledge, equilibrium predictors and robust statistical approaches could then provide improved estimates of mineral formation.…”

Section: Minerals Precipitation Modelling Approachmentioning

confidence: 99%

“…The identification of model parameters needs to be addressed since systematic and robust approaches are well-established in dynamic modelling of domestic wastewater processes , Dochain et al 2001, Donoso-Bravo et al 2011. This could also be useful for the identification of minerals to be included in a model, because minerals could be included or excluded based on whether their relative kinetics significantly affect overall model predictions, ie.…”

Section: Model Parameter Determinationmentioning

confidence: 99%

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Dynamic modelling of minerals precipitation in wastewater treatment

Mbamba¹

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In wastewater treatment, there is an increasing focus on nutrient and energy recovery and a reduction in energy consumption to counter climate change. Because of this, integrated mathematical modelling platforms are required to support plant-wide developments making use of emerging, resilient and environmental-friendly technologies. A reliable model description of a wastewater treatment plant should include both biology and physico-chemistry. However, existing standard models used across the wastewater sector have a biological focus with over-simplified descriptions of important physicochemistry, especially with minerals precipitation which is a very important class of physicochemical reactions.As part of development of a more widely applicable physicochemical framework, this thesis sought to identify a suitable minerals precipitation modelling approach that could give reasonable results in mainstream use with wastewater treatment. This research aim was approached in three steps. Firstly a review of available modelling approaches suggested a simple equilibrium kinetic-based modelling approach could be feasible. This approach was then validated in a simple system of calcite in synthetic solutions using pH titration experiments with the reliable Constant Composition Method (CCM).Further statistical analysis focused on clarifying key environmental factors that influence calcite precipitation to determine whether these are necessary to include in a model. Secondly, the proposed model approach was further tested on different types of wastewater and for multiple parallel precipitation reactions. Experiments included dynamic titration or aeration with synthetic wastewater and real wastewater. Thirdly, the general physicochemical modelling approach was implemented in a plant-wide platform together with standard biological models, namely activated sludge model No 2 (ASM2d) and Anaerobic Digestion Model No. 1 (ADM1). The plant-wide model evaluation compared simulations with real data from a full-scale wastewater treatment plant, and used steadystate, dynamic and scenario analyses to test the model performance.Experimental evidence for calcite precipitating in synthetic aqueous solutions, suggested that minerals precipitation kinetics could be reliably described with a 1 st order dependency on mineral Further testing for multi-species systems in real wastewater indicated that precipitation was dominated by the mineral struvite, forming together with varied and minor amounts of calcium phosphate and some calcium carbonate. Kinetic rate coefficients (kcryst), which were statistically fitted, were generally in the range 0.35-11.6 h -1 with 95% confidence intervals of 10-80% relative.The results confirmed that the baseline model approach provided a statistically good fit of measured pH, dissolved calcium, magnesium, total inorganic carbon and phosphate. With this application, the precipitation modelling approach offered the advantage of only requiring a minimal number of empirical fitted parameters (kcryst values), res...

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Dynamical Modelling & Estimation in Wastewater Treatment Processes

Cited by 167 publications

References 0 publications

CFD simulation and optimization of membrane scouring and nitrogen removal for an airlift external circulation membrane bioreactor

CFD simulation and optimization of membrane scouring and nitrogen removal for an airlift external circulation membrane bioreactor

A Novel Protocol for Model Calibration in Biological Wastewater Treatment

Dynamic modelling of minerals precipitation in wastewater treatment

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