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Smoothed particle hydrodynamics

Smoothed Particle Hydrodynamics (SPH) is a computational method used for simulating fluid flows. It has been used in many fields of research, including astrophysics, ballistics, vulcanology and tsunami. It is a Lagrangian method (where the co-ordinates move with the fluid), and the resolution of the method can easily be adjusted with respect to variables such as the density.

Method

The SPH method works by dividing the fluid into a set of discrete "fluid elements". These particles have a spatial distance (known as the "smoothing length", typically represented in equations by h), over which their properties are "smoothed" by a kernel function. This means that any physical quantity of any particle can be obtained by summing the relevant properties of all the particles which lie within two smoothing lengths. For example, the temperature of particle i depends on the temperatures of all the particles within a radial distance 2h of particle i.

The contributions of each particle to a property are weighted according to their distance from the particle of interest. Mathematically, this is governed by the kernel function (symbol W). Kernel functions commonly used include the Gaussian function and the cubic spline. The latter function is exactly zero for particles further away than two smoothing lengths (unlike the Gaussian, where there is a small contribution at any finite distance away). This has the advantage of saving computational effort by not including the relatively minor contributions from distant particles.

The equation for any quantity A of particle i, represented as Ai is given by the equation

A_i(r) = \sum_j m_j \frac{A_j}{\rho_j} W(r_i-r_j,h),

where mj is the mass of particle j, Aj is the value of the quantity A for particle j, ρj is the density associated with particle j, and W is the kernel function mentioned above. For example, the density of particle i (ρi) can be expressed as:

\rho_i(r) = \sum_j m_j \frac{\rho_j}{\rho_j} W(r_i-r_j,h) = \sum_j m_j W(r_i-r_j,h),

where the summation over j includes all particles in the simulation.

Similarly, the spatial derivative of a quantity can be obtained by using integration by parts to shift the del ( \nabla ) operator from the physical quantity to the kernel function,

\nabla A_i(r) = \sum_j m_j \frac{A_j}{\rho_j} \nabla W(r_i-r_j,h).


Although the size of the smoothing length can be fixed in both space and time, this does not take advantage of the full power of SPH. By assigning each particle its own smoothing length and allowing it to vary with time, the resolution of a simulation can be made to automatically adapt itself depending on local conditions. For example, in a very dense region where many particles are close together the smoothing length can be made relatively short, yielding high spatial resolution. Conversely, in low-density regions individual particles are far apart and the resolution is low, optimising the computation for the regions of interest.

Combined with an equation of state and an integrator, this method can simulate hydrodynamic flows efficiently, and since it is a Lagrangian method, its resolution is not limited by grid-cell spacing, unlike Eulerian methods, which are also used to simulate similar problems.

Uses in Astrophysics

The adaptive resolution of smoothed particle hydrodynamics, combined with its ability to simulate phenomena covering many orders of magnitude, make it ideal for computations in theoretical astrophysics.

Simulations of galaxy formation, star formation, stellar collisions, supernovae and meteor impacts are some of the wide variety of astrophysical and cosmological uses of this method.

Generally speaking, SPH is used solely to model hydrodynamics. Incorporating other astrophysical processes which may be important, such as radiative transfer and magnetic fields is an active area of research in the astronomical community, and has had some success.

External Links

[First large simulation of star formation using SPH]

01-04-2007 01:18:14
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