BNR/ENR treatment plants are impacted by wet weather storm flow events, which can have a significant impact on plant performance. Impacts include redistribution of process biomass, reduced contact time and secondary clarifier solids washout and significant changes in the influent wastewater characteristics. Five generic strategies are implemented in the wastewater treatment industry to deal with wet weather storm flow events:• Diversion and storage of excess storm flow, typically in side-stream equalization tanks. •Modification of the wastewater feed pattern to the BNR/ENR aeration tanks. • Adjustment to the operating mode of the BNR/ENR aeration tanks to better suit the peak flow conditions. • Manipulation of the process biomass storage and inventory. •Diversion of wastewater flow around the BNR/ENR aeration tank/secondary system with/without treatment, before blending back into the mainstream flow.These strategies are typically implemented in some combination on a plant specific basis, dictated by local considerations of:• Retention of solids inventory. •Maintenance of the microbial population in a healthy and viable state. • Achievement of a desired level of treatment. •Prevention of overflows and decants.The paper discusses wet weather treatment using referenced treatment plants and presents a generic decision model for the selection of the appropriate wet weather management strategies.
The development of more stringent effluent nutrient standards requires improved understanding and reliability of unit process performance during typical and stressed conditions. State of the art tools are needed for the evaluation of these units in order to ensure optimum performance during these conditions. Two of the most power tools available today are whole plant simulators such as BioWin™, GPS-X; and Computational Fluid Dynamics (CFD) models. Through the application of two case studies, this paper illustrates the combined use of a whole plant simulator and a secondary clarifier CFD model for the evaluation of wet weather strategies and for the assessment, design and retrofitting of secondary clarifiers.In the first case study, after calibration and validation with stress testing data, a BioWin model was linked to a 2Dc CFD clarifier model for the determination of the wet weather capacity of a Kentucky wastewater treatment plant. The results indicate that clarifier improvements and step feed are needed in order to sustain the extreme wet weather flows for this plant. In the second case study, the calibrated 2Dc model was applied to assess the capacity of existing 39.6 m (130 ft) diameter clarifiers and to the design of a new 48.8 m (160 ft) clarifier. In conjunction with BioWin, the 2Dc CFD model was used to evaluate the impact of using step feed, non-step feed and polymers during a storm event. The results show that the combined used of step-feed and polymers during a wet weather event can improve the performance of the secondary clarifiers by 80%, reducing the effluent suspended solids from approximately 160 mg/L to below 30 mg/L.
Design engineers commonly rely on physical and mathematical approximations or models of real complex phenomena. During the development of these physical or mathematical models, simplifications and assumptions need to be made to develop such tools. It is unrealistic to expect that the modeling process will give an answer that is a perfect match to the real case, and it is, therefore, very important to understand the modeling limitations and uncertainties. In 1996, Kops and Vanrolleghen (1996), indicated that numerous researches had been undertaken with regards to the uncertainty analysis (UA) of the sewer systems and receiving waters; however, there had been very little UA research involving the wastewater treatment plants (WWTPs). This statement has not changed too much since then. One reason that uncertainty analysis has been under utilized in WWTP modeling (with the exception of sensitivity analysis) is that practical ways of assessing uncertainty have not been readily applicable. Several techniques have been described in the literature for many years; however, these techniques traditionally require long simulation times. With new developments in computers and software it seems feasible and appropriate to start conducting UA in wastewater engineering modeling on a routine basis. This paper focuses on the development of UA related to the application of numerical models in wastewater treatment process with the main objective of illustrating the use and application of this technique to understand the limitations of the modeling process itself. The paper applies a Computational Fluid Dynamics (CFD) model for the design and upgrade of settling tanks and illustrates through examples the use of historical data and Monte Carlo type simulations to assess the parametric uncertainties associated with the settling and flocculation properties, which are the type of uncertainty that most strongly affects the output of the CFD clarifier model.
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