Water Online

November 2017

Water Innovations gives Water and Wastewater Engineers and end-users a venue to find project solutions and source valuable product information. We aim to educate the engineering and operations community on important issues and trends.

Issue link: https://wateronline.epubxp.com/i/896704

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Page 23 of 29

in a geometric sense. That is, the volume enclosed by the outer interfaces rather than the interfacial surface area is what determines mixing efficiency. Conversely, the effectiveness of dispersive mixing (micromixing) is dependent on the system's jets' shearing interaction with the sludge. During episodes of high sand influent concentrations, it may be detrimental to have high shear rates because it increases sand particle interactions, making the sludge behave in more of a shear- thickening manner. At an influent concentration of 6 percent or less, the sand is not to be considered of sufficient high concentration to cause the shift from shear thinning to thickening. In this case, the sand has a much higher settling velocity and may accumulate faster at the tank's conical bottom, increasing the concentration there and possibly causing a characteristic change in the recirculation pump suction. The mixing system has to account for sand concentration increasing in the settled sludge at the bottom. In addition, the uniformity of the stress distribution determines the uniformity of the mixing. Without uniform distribution of the shear stresses, it is impossible to guarantee that the same level of mixing is applied to all parts of the tank. Hence, a small number of jet nozzles may not be sufficient to entrain the entire volume of the tank. Turbulence in the region close to the inlet nozzle results in micromixing that cannot be maintained as the flow gets farther from the source in a high-viscosity ambient fluid. Research infers that high jet velocity inlet sources will always revert back to macromixing as the flow gets farther from the source. Thus, the energy cost required to expand micromixing to cover an entire tank would be excessive. In this case study, solids rheology did not exist for the sludge discharged in the holding tank, but volatile solids were known to be less than 80 percent. Therefore, it was less likely that 4 percent solids would behave as a semisolid and more likely that they would behave as a liquid, making the solids more flowable into the pump suction. In general, CFD results typically suggest a reduced solids settling potential, solely due to calculated high viscosities. If the actual viscosities were different, settling may occur. In addition, there is a difference between water and various wastewater sludge characteristics and settleability. Real-world experience suggests that sludge solids in the design range do settle with time, such as in gravity thickeners, hence the need for mixing systems. Therefore, it is recommended not to base non-Newtonian curvilinear flow conclusions solely on a noncalibrated CFD model utilizing empirical viscosity values. For CFD to be cost-effective, it is best used for comparative performance analysis of design alternatives. Based on the author's experience, it is strongly recommended to utilize a conservative design approach rather than optimize it based on the CFD's results. A CFD model can provide simulated data needed to optimize a design. The objective of the CFD modeling in this effort was to compare different design layouts rather than to achieve quantitative results. The multiphase flow in a sludge holding tank was modeled using the Euler-Euler multiphase model. Turbulence effects were ignored as the apparent viscosity of the fluid was expected to be high, and therefore, the turbulent regions were expected to be limited to a small volume of fluid near the design's nozzle jets. Therefore, in this case, laminar viscosity effects were expected to be more important than turbulence effects in the majority of the tank volume. Furthermore, the available turbulence models were not validated for use with non-Newtonian fluids. The secondary phase (sand) was modeled as a granular phase including drag force effects on sand particles. Tracking sand distribution was used as a means for evaluating mixing performance. Cohesive sediments were not accounted for in the model. Settled sand was assumed to leave the tank through the bottom outlet. As shown in Figure 1, three different mixing design configurations were designed by the author and modeled by Naveen Gopinathrao for a 60-ft-diameter sludge tank with 32-ft water depth at center. Design Layouts 1 and 2 are very similar, with the difference being the inner loop's outward nozzles' direction was reversed in Design Layout 2. Design Layout 3 replaces the two nozzle loops with one intermediate one. Micromixing using high-velocity agitation requires a considerable amount of energy due to the high-viscosity sludge. Therefore, the design attempts to achieve macromixing of wateronline.com n Water Innovations BIOSOLIDS Figure 2. Velocity distribution chart for Design Layouts 1, 2, and 3 21 Mixing efficiency is determined by the behavior of the fluid interfaces, and knowledge of the dynamics of the interfaces is crucial for the optimization of mixing efficiency.

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