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Scalar covariance derivation

As discussed in Chapter 5, the complexity of the chemical source term restricts the applicability of closures based on second- and higher-order moments of the scalars. Nevertheless, it is instructive to derive the scalar covariance equation for two scalars molecular-diffusion coefficients ra and I, respectively. Starting from (1.28), p. 16, the transport equation for ((,) can be found following the same steps that were used for the Reynolds stresses. This process yields34... [Pg.109]

The derivation of the transport equation for g xg,p is analogous to that used to derive the transport equation for the scalar covariance. The resultant expression is... [Pg.111]

In the absence of mean scalar gradients, the scalar covariances and joint dissipation rates will decay towards zero. For this case, it is convenient to work with the governing equations for g p and p p directly. These expressions can be derived from (3.179) and (3.180) ... [Pg.117]

Gap is the corresponding scalar-covariance source term, and Tap is the scalar-covariance transfer spectrum. In the following, we will relate the SR model for the scalar variance to (A.2) however, analogous expressions can be derived for the scalar covariance from (A.4) by following the same procedure. [Pg.383]

In Section 3.3, the general transport equations for the means, (3.88), and covariances, (3.136), of 0 are derived. These equations contain a number of unclosed terms that must be modeled. For high-Reynolds-number flows, we have seen that simple models are available for the turbulent transport terms (e.g., the gradient-diffusion model for the scalar fluxes). Invoking these models,134 the transport equations become... [Pg.238]

A key assumption in deriving the SR model (as well as earlier spectral models see Batchelor (1959), Saffman (1963), Kraichnan (1968), and Kraichnan (1974)) is that the transfer spectrum is a linear operator with respect to the scalar spectrum (e.g., a linear convection-diffusion model) which has a characteristic time constant that depends only on the velocity spectrum. The linearity assumption (which is consistent with the linear form of (A.l)) ensures not only that the scalar transfer spectra are conservative, but also that if Scap = Scr in (A.4), then Eap ic, t) = Eyy k, t) for all t when it is true for t = 0. In the SR model, the linearity assumption implies that the forward and backscatter rate constants (defined below) have the same form for both the variance and covariance spectra, and that for the covariance spectrum the rate constants depend on the molecular diffusivities only through Scap (i.e., not independently on Sc or Sep). [Pg.383]

Placement of indices as superscripts or subscripts follows the conventions of tensor analysis. Contravariant variables, which transform like coordinates, are indexed by superscripts, and coavariant quantities, which transform like derivatives, are indexed by subscripts. Cartesian and generalized velocities and 2 thus contravariant, while Cartesian and generalized forces, which transform like derivatives of a scalar potential energy, are covariant. [Pg.69]

By definition, the second order velocity structure function is the covariance of the difference in velocity between two points in space. A consequence of isotropy is that the structure function can be expressed in terms of a single scalar function. According to the similarity hypotheses of Kolmogorov, the scalar function can be expressed as Bdd x) = Sv Sv is a derived velocity scale sometimes... [Pg.117]

Requiring these order parameters to transform in a Lorentz-covariant way, we are led to a particular basis of 4 x 4 matrices , which was recently derived in detail (Capelle and Gross 1999a). The resulting order parameters represent a Lorentz scalar (one component), a four vector (four components), a pseudo scalar (one component), an axial four vector (four components), and an antisymmetric tensor of rank two (six independent components). This set of 4 x 4 matrices is different from the usual Dirac y matrices. The latter only lead to a Lorentz scalar, a four vector, etc., when combined with one creation and one annihilation operator, whereas the order parameter consists of two annihilation operators. [Pg.172]


See other pages where Scalar covariance derivation is mentioned: [Pg.88]    [Pg.98]    [Pg.99]    [Pg.151]    [Pg.191]    [Pg.303]    [Pg.307]    [Pg.576]    [Pg.599]    [Pg.63]    [Pg.840]   
See also in sourсe #XX -- [ Pg.90 ]

See also in sourсe #XX -- [ Pg.90 ]




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Scalar covariance

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