Flow evolution models were developed to evaluate the performance of the new advanced design mixer pump for sludge mixing and removal operations with high-velocity liquid jets in one of the large-scale Savannah River Site waste tanks, Tank 18. This paper describes the computational model, the flow measurements used to provide validation data in the region far from the jet nozzle, the extension of the computational results to real tank conditions through the use of existing sludge suspension data, and finally, the sludge removal results from actual Tank 18 operations.A computational fluid dynamics approach was used to simulate the sludge removal operations. The models employed a three-dimensional representation of the tank with a two-equation turbulence model. Both the computational approach and the models were validated with onsite test data reported here and literature data. The model was then extended to actual conditions in Tank 18 through a velocity criterion to predict the ability of the new pump design to suspend settled sludge. A qualitative comparison with sludge removal operations in Tank 18 showed a reasonably good comparison with final results subject to significant uncertainties in actual sludge properties.
Background: Aerobic capacity is a powerful predictor of cardiovascular disease and all-cause mortality and it declines with advancing age. Since physical activity alters body metabolism, metabolism markers will likely differ between subjects with high versus low aerobic capacities. Methods: Community-based participants without physician-diagnosed heart disease, stroke or cancer underwent same-day multi-modal assessment of cardiovascular function (by echocardiography and magnetic resonance feature tracking of left atrium) and aerobic capacity by peak oxygen uptake (VO2) metrics. Associations between VO2 and cardiovascular and metabolomics profiles were studied in adjusted models including standard covariates. Results: We studied 141 participants, of whom 82 (58.2%) had low VO2 while 59 (41.8%) had high VO2. Compared to participantts with high VO2, participants with low VO2 had more adverse cardiovascular parameters, such as lower ratio of peak velocity flow in early diastole to peak velocity flow in late diastole by atrial contraction of >0.8 (76% vs 35%, adjusted OR 4.1 95%CI (1.7–9.5), p=0.001) and lower LA conduit strain (11.3±4.0 vs 15.6±6.1%, adjusted OR 1.1 95%CI 1.002–1.3), p=0.045). High VO2 was associated with lower accumulation of wide-spectrum acylcarnitines (OR 0.6, 95% CI 0.4–0.9, p=0.013), alanine (OR 0.1, 95%CI 0.01–0.9, p=0.044) and glutamine/glutamate (OR 0.1, 95%CI 0.01–0.5, p=0.007), compared to low VO2. Conclusion: Elderly adults with low VO2 have adverse cardiovascular and metabolic parameters compared to their counterparts with high VO2. Combined cardiac and metabolomics phenotyping may be a promising tool to provide insights into physiological states, useful for tracking future interventions related to physical activity among community cohorts.
Blending times are required for many process industries, and statistical analysis of the measured blending times was used to determine a relationship between CFD (computational fluid dynamics) predictions and experiments. A 95% blending time occurs when tank contents are sufficiently blended to ensure that concentration throughout the tank is within ± 5% of the total change in concentration. To determine 95% blending times, acid and base tracers were added to an eight foot diameter tank, and the pH data were recorded to monitor blending. The data for six pH probes located throughout the tank were normalized to a range of 0 to 1. Then the blending time was established when the pH converged between 0.95 and 1.05 on the normalized graphs. Evaluation of results from 79 different tests concluded that the maximum blending time occurred randomly at any one of the six pH probes. The research then considered the calculated 95% blending times, which had uncertainties up to more than 100% at a 95% confidence level. However, this uncertainty is considered to be an actual variation in blending time, r ather than an experimental error. Not only were there significant variations in the blending times, but there were significant variations in the velocities measured at different points in the blending tank.
Research has been completed in a pilot scale, eight foot diameter tank to investigate blending, using a pump with dual opposing jets. The jets re-circulate fluids in the tank to promote blending when fluids are added to the tank. Different jet diameters and different horizontal and vertical orientations of the jets were investigated. In all, eighty five tests were performed both in a tank without internal obstructions and a tank with vertical obstructions similar to a tube bank in a heat exchanger. These obstructions provided scale models of several miles of two inch diameter, serpentine, vertical cooling coils below the liquid surface for a full scale, 1.3 million gallon, liquid radioactive waste storage tank. Two types of tests were performed. One type of test used a tracer fluid, which was homogeneously blended into solution. Data were statistically evaluated to determine blending times for solutions of different density and viscosity, and the blending times were successfully compared to computational fluid dynamics (CFD) models. The other type of test blended solutions of different viscosity. For example, in one test a half tank of water was added to a half tank of a more viscous, concentrated salt solution. In this case, the fluid mechanics of the blending process was noted to significantly change due to stratification of fluids. CFD models for stratification were not investigated. This paper is the fourth in a series of papers resulting from this research (Leishear,), and this paper documents final test results, statistical analysis of the data, a comparison of experimental results to CFD models, and scale-up of the results to a full scale tank.
This third in a series of four papers (Parts I–IV) presents the equations used for the initial evaluation of a pump’s ability to suspend solids and extends those equations to establish the minimum local velocity required to suspend those solids. This minimum velocity was used in a finite difference model in Part I to predict the ability of a pump to suspend, or slurry, solids that had settled on the bottom of a nuclear waste tank. To slurry waste, the Advanced Design Mixer Pump (ADMP) discharges a fluid jet that impinges on, shears, and then suspends the waste. Prior to the pump’s installation in a waste tank, the local velocity at a point in the flow required to suspend solids was found from available equations, material properties, and empirical data for similar pumps. Also, the computational fluids dynamics (CFD) model was validated in Part II by comparing it to flow rates measured in a full scale test facility where the ADMP was operated. The CFD fluid model could then be used to predict flow rates throughout the actual waste tank where the pump was to be installed, and the ability of the pump to adequately slurry the waste could be shown. All that needed to be done was to compare the local velocity of the fluid required to shear the waste into suspension to the velocities modeled throughout the waste tank. In short, this paper validates the theoretical and experimental basis for the derivation of a minimum velocity required for the flow stream to shear the waste into suspension. The final installment to this series of papers (Part IV) validates the application of the CFD model, by concluding that a nuclear waste tank is effectively cleaned to the wall throughout most of tank, using the ADMP.
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