CFD analysis of sludge accumulation and hydraulic performance of a waste stabilization pond

Alvarado, Andrés; Sánchez, Esteban Morcillo; Durazno, Galo; Vesvikar, Mehul; Nopens, Ingmar

doi:10.2166/wst.2012.450

Cited by 35 publications

(37 citation statements)

References 19 publications

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“…Alvarado et al (2012) determined that sludge accumulation and settling of sludge within waste stabilization ponds increases as water moves away from the inlet and the velocity decreases. Karteris et al (2005) created a temperature model within a covered anaerobic pond under unsteady state conditions.…”

Section: Modelingmentioning

confidence: 99%

Oxidation pond for municipal wastewater treatment

et al. 2015

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This literature review examines process, design, and cost issues related to using oxidation ponds for wastewater treatment. Many of the topics have applications at either full scale or in isolation for laboratory analysis. Oxidation ponds have many advantages. The oxidation pond treatment process is natural, because it uses microorganisms such as bacteria and algae. This makes the method of treatment cost-effective in terms of its construction, maintenance, and energy requirements. Oxidation ponds are also productive, because it generates effluent that can be used for other applications. Finally, oxidation ponds can be considered a sustainable method for treatment of wastewater.

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Section: Modelingmentioning

confidence: 99%

Oxidation pond for municipal wastewater treatment

et al. 2015

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“…These high loadings were associated with the sludge accumulation, which was also the reason of unavailable data at the bottom of location 1 and 2 in FPs. According to the study of Alvarado et al [39] in this pond system, the sludge volume of the FPs reached up to 34% of the pond volume, which substantially reduced its active volume.…”

Section: Spatiotemporal Influences On the Oxygen Dynamicmentioning

confidence: 79%

“…This difference can be caused by the fact that the central area of the FPs had less sludge accumulation and flow turbulence, which promoted high density of algae located at this region [39]. On the other hand, the bathymetries in the study of Alvarado et al [16] on these MPs showed only a slight sludge layer growth in the maturation ponds that can be assumed negligible regarding the pond hydraulics.…”

Section: Spatiotemporal Influences On the Oxygen Dynamicmentioning

confidence: 89%

“…This approach of artificially assigning values to parameters can lead to biased results, which significantly deviates from real outputs [38]. Indeed, several simplifying assumptions along with geometric approximations caused the disagreements between computational fluid dynamics (CFD) model outputs and experimental results in the research of Alvarado, Sanchez, Durazno, Vesvikar and Nopens [39]. Finally, the large number of experimental data needed for the validation of mechanistic model is another major constraint.…”

Section: Model Evaluationmentioning

confidence: 99%

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A Closer Look on Spatiotemporal Variations of Dissolved Oxygen in Waste Stabilization Ponds Using Mixed Models

Pham

Echelpoel

et al. 2018

Water

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Dissolved oxygen is an essential controlling factor in the performance of facultative and maturation ponds since both take many advantages of algal photosynthetic oxygenation. The rate of this photosynthesis strongly depends on the time during the day and the location in a pond system, whose roles have been overlooked in previous guidelines of pond operation and maintenance (O&M). To elucidate these influences, a linear mixed effect model (LMM) was built on the data collected from three intensive sampling campaigns in a waste stabilization pond in Cuenca, Ecuador. Within two parallel lines of facultative and maturation ponds, nine locations were sampled at two depths in each pond. In general, the output of the mixed model indicated high spatial autocorrelations of data and wide spatiotemporal variations of the oxygen level among and within the ponds. Particularly, different ponds showed different patterns of oxygen dynamics, which were associated with many factors including flow behavior, sludge accumulation, algal distribution, influent fluctuation, and pond function. Moreover, a substantial temporal change in the oxygen level between day and night, from zero to above 20 mg O 2 ·L −1 , was observed. Algal photosynthetic activity appeared to be the main reason for these variations in the model, as it was facilitated by intensive solar radiation at high altitude. Since these diurnal and spatial patterns can supply a large amount of useful information on pond performance, insightful recommendations on dissolved oxygen (DO) monitoring and regulations were delivered. More importantly, as a mixed model showed high predictive performance, i.e., high goodness-of-fit (R 2 of 0.94), low values of mean absolute error, we recommended this advanced statistical technique as an effective tool for dealing with high autocorrelation of data in pond systems.

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“…7.1 (and Table 7.1) are not effectively modelled using a lumped parameter approach, since there will be substantial variation in state variables across space. Particular examples where distributed parameter modelling is important include anaerobic biofilm reactors (including granular reactors), which can be modelled both in the micron scale through a biofilm model , as well as through an advective-diffusive (possibly plug-flow reactor) on the reactor scale (Batstone et al 2005), plug-flow semi-solid reactors (Dvorak 2012;Frear and Dvorak 2013), leach bed (including engineered landfill reactors) (Nopharatana et al 2003), and anaerobic digestion and stabilization lagoons (Alvarado et al 2012a;Alvarado et al 2012b). Even systems, which can be effectively represented by a single compartment from a biological perspective, may need a distributed parameter model for specific aspects, particularly those related to shear, mixing, or other operational considerations (BoyleGotla et al 2014).…”

Section: Complex (Distributed Parameter) Systemsmentioning

confidence: 99%

Modelling Anaerobic Digestion Processes

Batstone¹,

Rodríguez²

2015

Anaerobic Biotechnology

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Anaerobic process modelling is rapidly expanding as new processes and reactor designs are developed, and a better understanding of the underlying processes is established. At the same time, new applications and demands on the art have been developed, particularly the generation of bioenergy and fuels, as well as plant-wide modelling of wastewater processes, and the integration of activated sludge and anaerobic models. This has required a rethink of what should go in the model, with a focus on the biochemical pathways (resulting in e.g., the IWA Anaerobic Digestion Model No. 1 -ADM1) shifting towards a better description of associated processes, such as chemistry, gas transfer, and organic solubilization, as well as new topics such as integration with hydrodynamics. In this chapter, we take a very broad view of anaerobic process modelling, including new applications, model development fit for applications, determining biochemical structure and potential new structures, as well as the identification and characterization of processes fit for modelling. While based on fundamentals, this leads to a practical view of how to best apply this diverse range of techniques to best solve real problems in anaerobic process modelling. A general approach to the problem of parameter and input characterization applicable to the broad range of processes and problems generally modelled is also included.

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CFD analysis of sludge accumulation and hydraulic performance of a waste stabilization pond

Cited by 35 publications

References 19 publications

Oxidation pond for municipal wastewater treatment

Oxidation pond for municipal wastewater treatment

A Closer Look on Spatiotemporal Variations of Dissolved Oxygen in Waste Stabilization Ponds Using Mixed Models

Modelling Anaerobic Digestion Processes

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