Stokesian Dynamics
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Stokesian dynamics is a solution technique for the
Langevin equation In physics, a Langevin equation (named after Paul Langevin) is a stochastic differential equation describing how a system evolves when subjected to a combination of deterministic and fluctuating ("random") forces. The dependent variables in a Lange ...
, which is the relevant form of
Newton's 2nd law Newton's laws of motion are three physical laws that describe the relationship between the motion of an object and the forces acting on it. These laws, which provide the basis for Newtonian mechanics, can be paraphrased as follows: # A body re ...
for a Brownian particle. The method treats the suspended particles in a discrete sense while the continuum approximation remains valid for the surrounding fluid, i.e., the suspended particles are generally assumed to be significantly larger than the molecules of the solvent. The particles then interact through hydrodynamic forces transmitted via the continuum fluid, and when the particle
Reynolds number In fluid dynamics, the Reynolds number () is a dimensionless quantity that helps predict fluid flow patterns in different situations by measuring the ratio between Inertia, inertial and viscous forces. At low Reynolds numbers, flows tend to ...
is small, these forces are determined through the linear Stokes equations (hence the name of the method). In addition, the method can also resolve non-hydrodynamic forces, such as Brownian forces, arising from the fluctuating motion of the fluid, and interparticle or external forces. Stokesian Dynamics can thus be applied to a variety of problems, including sedimentation, diffusion and rheology, and it aims to provide the same level of understanding for multiphase particulate systems as molecular dynamics does for statistical properties of matter. For N rigid particles of radius a suspended in an incompressible Newtonian fluid of viscosity \eta and density \rho, the motion of the fluid is governed by the Navier–Stokes equations, while the motion of the particles is described by the coupled equation of motion: :\mathbf\frac = \mathbf^\mathrm + \mathbf^\mathrm + \mathbf^\mathrm. In the above equation \mathbf is the particle translational/rotational velocity vector of dimension 6N. \mathbf^\mathrm is the hydrodynamic force, i.e., force exerted by the fluid on the particle due to relative motion between them. \mathbf^\mathrm is the
stochastic Stochastic (; ) is the property of being well-described by a random probability distribution. ''Stochasticity'' and ''randomness'' are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; i ...
Brownian force due to thermal motion of fluid particles. \mathbf^\mathrm is the deterministic nonhydrodynamic force, which may be almost any form of interparticle or external force, e.g. electrostatic repulsion between like charged particles. Brownian dynamics is one of the popular techniques of solving the
Langevin equation In physics, a Langevin equation (named after Paul Langevin) is a stochastic differential equation describing how a system evolves when subjected to a combination of deterministic and fluctuating ("random") forces. The dependent variables in a Lange ...
, but the hydrodynamic interaction in Brownian dynamics is highly simplified and normally includes only the isolated body resistance. On the other hand, Stokesian dynamics includes the many body hydrodynamic interactions. Hydrodynamic interaction is very important for non-equilibrium suspensions, like a sheared suspension, where it plays a vital role in its microstructure and hence its properties. Stokesian dynamics is used primarily for non-equilibrium suspensions where it has been shown to provide results which agree with experiments.


Hydrodynamic interaction

When the motion on the particle scale is such that the particle Reynolds number is small, the hydrodynamic force exerted on the particles in a suspension undergoing a bulk linear shear flow is: :\mathbf^\mathrm = -\mathbf_\mathrm(\mathbf-\mathbf^) + \mathbf^\mathrm:\mathbf^. Here, \mathbf^ is the velocity of the bulk shear flow evaluated at the particle center, \mathbf^ is the symmetric part of the velocity-gradient tensor; \mathbf_\mathrm and \mathbf_\mathrm are the configuration-dependent resistance matrices that give the hydrodynamic force/torque on the particles due to their motion relative to the fluid (\mathbf_\mathrm) and due to the imposed shear flow (\mathbf_\mathrm). Note that the subscripts on the matrices indicate the coupling between kinematic (\mathbf) and dynamic (\mathbf) quantities. One of the key features of Stokesian dynamics is its handling of the hydrodynamic interactions, which is fairly accurate without being computationally inhibitive (like boundary integral methods) for a large number of particles. Classical Stokesian dynamics requires O(N^) operations where ''N'' is the number of particles in the system (usually a periodic box). Recent advances have reduced the computational cost to about O(N^ \, \log N).


Brownian force

The stochastic or Brownian force \mathbf^\mathrm arises from the thermal fluctuations in the fluid and is characterized by: : \left\langle\mathbf^\mathrm\right\rangle = 0 : \left\langle\mathbf^\mathrm(0)\mathbf^\mathrm(t)\right\rangle = 2kT\mathbf_\mathrm\delta(t) The angle brackets denote an ensemble average, k is the Boltzmann constant, T is the absolute temperature and \delta(t) is the delta function. The amplitude of the correlation between the Brownian forces at time 0 and at time t results from the fluctuation-dissipation theorem for the N-body system.


See also

* Immersed boundary methods * Stochastic Eulerian Lagrangian methods


References

{{reflist Statistical mechanics Equations Fluid mechanics