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Table 2-5 Summary of Approaches to Turbulence Modelinga Model Boussinesq approximation One equation with one adjustable parameter Averaged over time and all length scales Prandtl mixing length One equation with two adjustable parameters Averaged over time and all length scales Physical Basis of the Model One length scale Based on analogy to laminar transport and apparent viscosity One length scale Based on analogy to mean free path in the kinetic theory of gases Drawbacks Oversimpli cation of the physics The apparent viscosity is a function of the ow eld and of position Oversimpli cation of the physics The assumption of a linear velocity pro le does not match physical reality; however, the results are surprisingly good for the log-law region of a pipe Five model constants have been determined for simpli ed ows Two-equation models cannot accurately model the effects of anisotropy on the large scale, although the form of the model may be useful for the locally isotropic range of turbulence k model tends to be overly diffusive

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Use the delta function to do the d4x integral and expand the resulting factor cxp(k$(y)) to give the desired result. Taking G / S J ( z ) of this result by the same procedure leads to the expression for b 2 2 [ J ] / b J ( y ) 6 J ( z ) .

(2.170)

[a,b] [1,0] [1,0] [1,0] [1,0] [1,0] [1,0] [1,0] [1,0] [1,0] [1,0] 1 1 1 2 14 1 0 1 2 2

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using different properties of the interfering signal; for example, for a GMSK-modulated interferer it is possible to use its constant envelope property or the fact that the same information is carried in the real and imaginary part of the signal [12, 13]. Basically, BIC techniques have a lower complexity than JD-based methods, making them more cost ef cient and therefore attractive for rst-generation SAIC terminals. The cost for this lower complexity is a reduction in the potential performance gain, compared with methods based on JD. The SAIC results presented in this section are based on two different low complexity BIC solutions: the rst one is Mono Interference Cancellation (MIC) [13]; the other is called GMSK-IC (Interference Cancellation). Both the solutions have previously been used to generate input to the feasibility study ongoing in TSG GERAN [14, 15]. Identi cation of SAIC capability is another important issue currently being debated. The network is likely to require the knowledge of which mobiles are SAIC-capable, and potentially to what degree (e.g. GMSK only, GMSK and 8-PSK, etc). Such information may be bene cial for the network to control the C/I conditions different terminals are subject to: for instance, through tighter effective reuses for SAIC MS, or by means of SAIC-optimised Power Control, or even SAIC-tuned DFCA algorithms (see 9). Several possibilities exist: special signalling could be de ned (one way to do this is to have explicit classmark information) or the network could be required to identify SAIC-capable terminals in an unassisted way.

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Figure 21-22 Spherical bearing (cross-sectional view.) (Courtesy of NTN Bearing Corp.)

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