Slurry transport through pipelines ensures a dust-free environment, requires substantially less space, enables full automation, and requires less operating staff. On the other hand, it requires higher operating pressures and considerable high-quality pumping equipment and control systems. For competitiveness,the power consumption for the slurry transport should be reduced. Here, a numerical technique was developed for the reduction of the power consumption during slurry transport in horizontal long pipelines. Four main flow regimes characterise the horizontal slurry flow, i.e. the flow with a stationary bed, the flow with a moving bed and saltation (with or without suspension), heterogeneous mixture with all solids in suspension, and pseudo-homogeneous mixtures with all solids in suspension. Heterogeneous suspension occurs when the turbulence level is too low to prevent any particle deposition. In the saltation regimes, the solids concentration is strongly nonuniform. The critical velocity is defined as the minimum velocity in which solids form a bed at the bottom of the pipe from fully suspended flow. This velocity, which is also referred to as the minimum-carrying or limiting-deposition velocity, is exactly predicted by the developed method. It also is the velocity that corresponds to the minimum pressure drop, and therefore the most important transition velocity in slurry transport. Lower transport velocities are uneconomical due to increased pressure drop, and cause danger of pipeline plugging and of excessive corrosion in the lower part of the pipeline. The model was developed following the criteria that as few as possible input parameters should be used, and that each input should be highly cross-related to the output parameter. Neural training of the support vector machine was performed using data for different solid concentrations, particle diameters, densities, and viscosities. The accurate prediction of the critical velocity will substantially reduce power consumption since keeping the slurry velocity just above the critical velocity enables keeping it in the vicinity of minimum pressure drop.
Minimize power consumption in slurry transport. Accurately predict critical velocity
Hydrocarbon Processing ; 87 , 12 ; 112-118
2008
7 Seiten, 7 Bilder, 5 Tabellen, 24 Quellen
Article (Journal)
English
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