Continuum fluid field

The continuum fluid field is calculated from the continuity and Navier— Stokes equations based on the local mean variables over a computational ceU, which can be written as (Zhou et al., 2010a) ... 

When the length scale approaches molecular dimensions, the inner spinning" of molecules will contribute to the lubrication performance. It should be borne in mind that it is not considered in the conventional theory of lubrication. The continuum fluid theories with microstructure were studied in the early 1960s by Stokes [22]. Two concepts were introduced couple stress and microstructure. The notion of couple stress stems from the assumption that the mechanical interaction between two parts of one body is composed of a force distribution and a moment distribution. And the microstructure is a kinematic one. The velocity field is no longer sufficient to determine the kinematic parameters the spin tensor and vorticity will appear. One simplified model of polar fluids is the micropolar theory, which assumes that the fluid particles are rigid and randomly ordered in viscous media. Thus, the viscous action, the effect of couple stress, and... 

Basically, two fundamental approaches are used (I) continuum or field dynamics and (2) kinetic theory and nonequilibrium statistical mechanics. The study of fluids tends to be quite complex. 

The fundamental theory of fluid mechanics is expressed in the mathematical language of continuum tensor field calculus. An exhaustive treatment of this subject is found in the treatise by Truesdell and Toupin (1960). Two fundamental classes of equations are required (1) the generic equations of balance and (2) the constitutive relations. 

The equations of motion for granular flows have been derived by adopting the kinetic theory of dense gases. This approach involves a statistical-mechanical treatment of transport phenomena rather than the kinematic treatment more commonly employed to derive these relationships for fluids. The motivation for going to the formal approach (i.e., dense gas theory) is that the stress field consists of static, translational, and collisional components and the net effect of these can be better handled by statistical mechanics because of its capability for keeping track of collisional trajectories. However, when the static and collisional contributions are removed, the equations of motion derived from dense gas theory should (and do) reduce to the same form as the continuity and momentum equations derived using the traditional continuum fluid dynamics approach. In fact, the difference between the derivation of the granular flow equations by the kinetic approach described above and the conventional approach via the Navier Stokes equations is that, in the latter, the material properties, such as viscosity, are determined by experiment while in the former the fluid properties are mathematically deduced by statistical mechanics of interparticle collision. 

While the detailed analysis of the Kerr profiles in pure liquids leads to the conclusion that four distinct responses underlie the overall rise and decay of the field-induced polarization anisotropy A n(t), naturally in a real liquid these responses are coupled together. For clarity of discussion we will continue to describe them separately, since the timescale separation assumption in Eq. (3) proved quite valid. Summarized as follows in terms of r (t), which are associated with the instantaneous electronic and noninstantaneous, field-driven nuclear responses linked to intra- and intermolecular motions, the responses are labeled r (electronic) and r2> r, r (nuclear). The underlying assumption of a harmonic potential v j, and a continuum fluid [g(r) = 1] might clearly lead to some over simplifications but if molecules reside at or near the bottom of the potential well, the situation is not unreasonable. The results are very instructive for modeling short-time behavior for molecular solvents at room temperature, which is the next, vastly more complex step (see references on simulations and the next chapter). 

The addition of a point force into the continuum fluid equations introduces a singularity into the flow field, which causes both mathematical and numerical difficulties. On the other hand, the flow field around a finite-sized particle can be... 

Continuum theory has also been applied to analyse tire dynamics of flow of nematics [77, 80, 81 and 82]. The equations provide tire time-dependent velocity, director and pressure fields. These can be detennined from equations for tire fluid acceleration (in tenns of tire total stress tensor split into reversible and viscous parts), tire rate of change of director in tenns of tire velocity gradients and tire molecular field and tire incompressibility condition [20]. 

At Che opposite limit, where Che density Is high enough for mean free paths to be short con ared with pore diameters, the problem can be treated by continuum mechanics. In the simplest ease of a straight tube of circular cross-section, the fluid velocity field can easily be obtained by Integrating Che Nsvler-Stokes equations If an appropriate boundary condition at Che... 

In continuum boundary conditions the protein or other macromolecule is treated as a macroscopic body surrounded by a featureless continuum representing the solvent. The internal forces of the protein are described by using the standard force field including the Coulombic interactions in Eq. (6), whereas the forces due to the presence of the continuum solvent are described by solvation tenns derived from macroscopic electrostatics and fluid dynamics. 

We begin our discus.sion with the top-down approach. Let F be a two or three dimensional region filled with a fluid, and let v x,t) be the velocity of a particle of fluid moving through the point x = ( r, y, z) at time t. Note that v x, t) is a vector-valued field on F, and is to be identified with a macroscopic fluid cell. The fact that we can make this so-called continuum assumption - namely that we can simultaneously speak of a velocity of a particle of fluid and think of a particle of fluid as a macroscopic cell - is not at all obvious, of course, and deserves some attention. 

Similar convection-diffusion equations to the Navier-Stokes equation can be formulated for enthalpy or species concentration. In all of these formulations there is always a superposition of diffusive and convective transport of a field quantity, supplemented by source terms describing creation or destruction of the transported quantity. There are two fundamental assumptions on which the Navier-Stokes and other convection-diffusion equations are based. The first and most fundamental is the continuum hypothesis it is assumed that the fluid can be described by a scalar or vector field, such as density or velocity. In fact, the field quantities have to be regarded as local averages over a large number of particles contained in a volume element embracing the point of interest. The second hypothesis relates to the local statistical distribution of the particles in phase space the standard convection-diffusion equations rely on the assumption of local thermal equilibrium. For gas flow, this means that a Maxwell-Boltzmann distribution is assumed for the velocity of the particles in the frame-of-reference co-moving with the fluid. Especially the second assumption may break dovm when gas flow at high temperature or low pressure in micro channels is considered, as will be discussed below. 

A partial differential equation is then developed for the number density of particles in the phase space (analogous to the classical Liouville equation that expresses the conservation of probability in the phase space of a mechanical system) (32>. In other words, if the particle states (i.e. points in the particle phase space) are regarded at any moment as a continuum filling a suitable portion of the phase space, flowing with a velocity field specified by the function u , then one may ask for the density of this fluid streaming through the phase space, i.e. the number density function n(z,t) of particles in the phase space defined as the number of particles in the system at time t with phase coordinates in the range z (dz/2). 

In the two-fluid formulation, the motion or velocity field of each of the two continuous phases is described by its own momentum balances or NS equations (see, e.g., Rietema and Van den Akker, 1983 or Van den Akker, 1986). In both momentum balances, a phase interaction force between the two continuous phases occurs predominantly, of course with opposite sign. Two-fluid models therefore belong to the class of two-way coupling approaches. The continuum formulation of the phase interaction force should reflect the same effects as experienced by the individual particles and discussed above in the context of the Lagrangian description of dispersed two-phase flow. 

An alternative and complementary use of CFD in fixed bed simulation has been to solve the actual flow field between the particles (Fig. lb). This approach does not simplify the geometrical complexities of the packing, or replace them by the pseudo-continuum that is used in the first approach. The governing equations for the interstitial fluid flow itself are solved directly. The contrast is thus between the interstitial flow field type of simulation and the superficial flow... 

We focus our attention on a packet of fluid, or a fluid particle, whose size is small compared to the length scales over which the macroscopic velocity varies in a particular flow situation, yet large compared to molecular scales. Consider air at room temperature and atmospheric pressure. Using the ideal-gas equation of state, it is easily determined that there are approximately 2.5 x 107 molecules in a cube that measures one micrometer on each side. For an ordinary fluid mechanics problem, velocity fields rarely need to be resolved to dimensions as small as a micrometer. Yet, there are an enormous number of molecules within such a small volume. This means that representing the fluid velocity as continuum field using an average of the molecular velocities is an excellent approximation. 

Initial supercritical fluid work was on C02 (21-23) and indicated weak interactions between the fluid and solute. Additional work has appeared on Xe, SF6, C2H, and NH3 (24,25). For all fluids, spectral shifts were observed with fluid density. Yonker, Smith and co-workers (24-26,28) compared their results to the McRae continuum model for dipolar solvation (56,57), which is based on Onsanger reaction field theory (58). Over a limited density range, there was agreement between the experimental data and the model (24-26,28), but conditions existed where the predicted linear relationship was not followed (28). At low fluid densities, this deviation was attributed (qualitatively) to fluid clustering around the solute (28). 

Soft biological structures exhibit finite strains and nonlinear anisotropic material response. The hydrated tissue can be viewed as a fluid-saturated porous medium or a continuum mixture of incompressible solid (s), mobile incompressible fluid (f), and three (or an arbitrary number) mobile charged species a, (3 = p,m, b). A mixed Electro-Mechano-Chemical-Porous-Media-Transport or EMCPMT theory (previously denoted as the LMPHETS theory) is presented with (a) primary fields (continuous at material interfaces) displacements, Ui and generalized potentials, ifi ( , r/ = /, e, to, b) and (b) secondary fields (discontinuous) pore fluid pressure, pf electrical potential, /7e and species concentration (molarity), ca = dna/dVf or apparent concentration, ca = nca and c = Jnca = dna/dVo. The porosity, n = 1 — J-1(l — no) and no = no(Xi) = dVj/dVo for a fluid-saturated solid. Fixed charge density (FCD) in the solid is defined as cF = dnF/dV , cF = ncF, and cF = cF (Xf = JncF = dnF/d o. 

Several hybrid simulations on crystal growth can be found in recent literature. Examples include dendritic solidification by coupling finite-different discretization of a phase field model to a MC simulation (Plapp and Karma, 2000), coupling a finite difference for the melt with a cellular automata for the solidification (Grujicic et al., 2001), a DSMC model for the fluid phase with a Metropolis-based MC for the surface to address cluster deposition onto substrates (Hongo et al., 2002 Mizuseki et al., 2002), a step model for the surface processes coupled with a CFD simulation of flow (Kwon and Derby, 2001) (two continuum but different feature scale models), an adaptive FEM CVD model coupled with a feature scale model (Merchant et al., 2000), and one-way coupled growth models in plasma systems (Hoekstra et al., 1997). Some specific applications are discussed in more detail below. 

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