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In civil engineering (specifically hydraulic engineering), a hydrodynamic separator (HDS) is a stormwater management device that uses cyclonic separation to control water pollution. They are designed as flow-through structures with a settling or separation unit to remove sediment and other pollutants. [ 1 ]
A spiral separator may process a couple tons per hour of ore, per flight, and multiple flights may be stacked in the same space as one, to improve capacity. [2] Many things can be done to improve the separation efficiency, including: changing the rate of material feed; changing the grain size of the material; changing the slurry mass percentage [3]
Dimensionless numbers (or characteristic numbers) have an important role in analyzing the behavior of fluids and their flow as well as in other transport phenomena. [1] They include the Reynolds and the Mach numbers, which describe as ratios the relative magnitude of fluid and physical system characteristics, such as density, viscosity, speed of sound, and flow speed.
In a centrifugal oil and water separator, the force of gravity is one-thousand [citation needed] times greater that of the coalescing plate pack separator or the petrol interceptor, so the separation is much greater. Not only is the force of separation greater, but there are fewer working parts so maintenance is much easier and cheaper. [5]
ANUGA Hydro [3] is a free and open source software tool for hydrodynamic modelling, suitable for predicting the consequences of hydrological disasters such as riverine flooding, storm surges and tsunamis.
Fluid flow in an external gear pump. A hydraulic pump is a mechanical source of power that converts mechanical power into hydraulic energy (hydrostatic energy i.e. flow, pressure).
A water tunnel is an experimental facility used for testing the hydrodynamic behavior of submerged bodies in flowing water. It functions similar to a recirculating wind tunnel , but uses water as the working fluid, and related phenomena are investigated, such as measuring the forces on scale models of submarines or lift and drag on hydrofoils .
The computational cost of SPH simulations per number of particles is significantly less than the cost of grid-based simulations per number of cells when the metric of interest is related to fluid density (e.g., the probability density function of density fluctuations). [6] This is the case because in SPH the resolution is put where the matter is.