Wet-weather Treatment Upgrade Scenarios with Sensitivity and Uncertainty Analysis at the Eindhoven WWTP

Benedetti, Lorenzo; Nieuwenhuijzen, A. van; Jonge, Joanne De; Amerlinck, Youri; Plano, Salvatore; Weijers, Stefan

doi:10.2175/193864710798170603

Cited by 3 publications

(2 citation statements)

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“…The model originally set up in a previous project (Benedetti et al 2010b;Nopens et al 2010) was used as the starting point for this study. The 2010 model -implemented in WEST (www.mikebydhi.com) -was modified to run long-term simulations by implementing controllers as substitutes for measured inputs of operational variables like airflow and recycle flows, as those data were available only for limited periods of time.…”

Section: Dynamic Model Set-upmentioning

confidence: 99%

The incorporation of variability and uncertainty evaluations in WWTP design by means of stochastic dynamic modeling: the case of the Eindhoven WWTP upgrade

Benedetti¹,

Belia²,

Flameling³

et al. 2013

Water Science and Technology

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This paper illustrates how a dynamic model can be used to evaluate a plant upgrade on the basis of post-upgrade performance data. The case study is that of the Eindhoven wastewater treatment plant upgrade completed in 2006. As a first step, the design process based on a static model was thoroughly analyzed and the choices regarding variability and uncertainty (i.e. safety factors) were made explicit. This involved the interpretation of the design guidelines and other assumptions made by the engineers. As a second step, a (calibrated) dynamic model of the plant was set up, able to reproduce the anticipated variability (duration and frequency). The third step was to define probability density functions for the parameters assumed to be uncertain, and propagate that uncertainty with the dynamic model by means of Monte Carlo simulations. The last step was the statistical evaluation and interpretation of the simulation results. This work should be regarded as a 'learning exercise' increasing the understanding of how and to what extent variability and uncertainty are currently incorporated in design guidelines used in practice and how model-based post-project appraisals could be performed.

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Section: Dynamic Model Set-upmentioning

confidence: 99%

The incorporation of variability and uncertainty evaluations in WWTP design by means of stochastic dynamic modeling: the case of the Eindhoven WWTP upgrade

Benedetti¹,

Belia²,

Flameling³

et al. 2013

Water Science and Technology

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show abstract

“…The details of the WEST (www.mikebydhi.com) model can be found in Benedetti et al, (2010c), Nopens et al, (2010) and Cierkens et al (2012a).…”

Section: The Eindhoven Wwtp and Modelmentioning

confidence: 99%

Translating safety factors to sources of variability and uncertainty; Model-based design evaluation for the Eindhoven WWTP

Belia¹,

Benedetti²,

Weijers³

et al. 2012

proc water environ fed

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Design guideline safety factors (SF) are based on the accumulated experience of the industry and account for the uncertainty and variability inherent in the wastewater treatment process. Models on the other hand, as implemented in most commercial simulators, do not explicitly account for uncertainty. This paper discusses how to deal with variability and uncertainty in an explicit way when using a dynamic model combined with uncertainty analysis to perform a post-project evaluation. Through the use of time series, the response of the design to the variability of key inputs can be captured in the dynamic model. In order to incorporate uncertainty, selected model parameters can be described with probability density functions (PDF). Scenario analysis can be used to simulate discreet operational conditions or events. Uncertainty can then be propagated to the dynamic model outputs with the use of Monte Carlo simulations. To test this approach, the upgrade of the Eindhoven WWTP (Waterboard De Dommel, The Netherlands) was selected as a case study. The project focused on how variability and uncertainty are incorporated in design guidelines and highlighted key issues linked to the inclusion of the sources of uncertainty in the calibrated model.

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Assessing the convergence of LHS Monte Carlo simulations of wastewater treatment models

Benedetti

Claeys²,

Vanrolleghem

2011

Water Science and Technology

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Monte Carlo (MC) simulation appears to be the only currently adopted tool to estimate global sensitivities and uncertainties in wastewater treatment modelling. Such models are highly complex, dynamic and non-linear, requiring long computation times, especially in the scope of MC simulation, due to the large number of simulations usually required. However, no stopping rule to decide on the number of simulations required to achieve a given confidence in the MC simulation results has been adopted so far in the field. In this work, a pragmatic method is proposed to minimize the computation time by using a combination of several criteria. It makes no use of prior knowledge about the model, is very simple, intuitive and can be automated: all convenient features in engineering applications. A case study is used to show an application of the method, and the results indicate that the required number of simulations strongly depends on the model output(s) selected, and on the type and desired accuracy of the analysis conducted. Hence, no prior indication is available regarding the necessary number of MC simulations, but the proposed method is capable of dealing with these variations and stopping the calculations after convergence is reached.

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Wet-weather Treatment Upgrade Scenarios with Sensitivity and Uncertainty Analysis at the Eindhoven WWTP

Cited by 3 publications

References 0 publications

The incorporation of variability and uncertainty evaluations in WWTP design by means of stochastic dynamic modeling: the case of the Eindhoven WWTP upgrade

The incorporation of variability and uncertainty evaluations in WWTP design by means of stochastic dynamic modeling: the case of the Eindhoven WWTP upgrade

Translating safety factors to sources of variability and uncertainty; Model-based design evaluation for the Eindhoven WWTP

Assessing the convergence of LHS Monte Carlo simulations of wastewater treatment models

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