Spreading factor values

Factorial design methods cannot always be applied to QSAR-type studies. For example, i may not be practically possible to make any compounds at all with certain combination of factor values (in contrast to the situation where the factojs are physical properties sucl as temperature or pH, which can be easily varied). Under these circumstances, one woul( like to know which compounds from those that are available should be chosen to give well-balanced set with a wide spread of values in the variable space. D-optimal design i one technique that can be used for such a selection. This technique chooses subsets o... 

Fig. 12 shows the spread factors simulated on meshes with different resolutions along with the measurement value of Wachters and Westerling (1966). The spread factor is defined as the radius of the droplet on the solid surface divided by the initial radius of the droplet. Although the convergence is not perfect, the agreement between the experiment and the simulations is relatively good for all resolutions. Consistent with the results of Fig. 11, the effect of the mesh resolution on spread factor becomes notable after 8 ms since the moment of impact, and the coarser resolution tends to yield a slower rebounding process. 

If the model is used then this situation can be improved considerably. In Fig. 20.14 some of the most important cell operating conditions are taken into account when inferring the gap from k-factor. This means that the spread of possible k-factor values that can be associated with that gap is reduced and the alarm point can be reduced from KA to KA and yet still guarantee that the minimum gap constraint will not be violated. Notice that despite the use of the model there is still a range of gaps which could be prevalent when the alarm triggers. This spread is due to modelling errors and variables not used by the model. 

The spreading factor C is the variance of the chromatograms of the monodisperse polymer species, i.e. of the instrumental spreading fimction G(V,Vr), If O g varies linearly vd.th the retention volume of the monodisperse polymer, then<0 > is numerically equal to the interpolated value 0 (v) of the function (T (Vr) for the polydisperse sample at its mean elution volume. 

The critical pressure P = PoAso/q2 is more difficult to evaluate. In the earlier literature there is a large spread of values [17]. The recent MC simulations of Orkoulas and Panagiotopoulos [52] yield P c = 8 x 10-5 near the lower limit of earlier estimates, along with a critical compressibility factor of Zc — PJ(pcTc) = 0.024 which is one order of magnitude lower than observed for nonionic fluids (e.g., Zc = 3/8 = 0.375 for the van der Waals fluid). 

The diameter of any stain is always larger than that of the impinging droplet, the relationship between the two diameters is referred to as the spread factor. The spread factor is an empirical value which must be a determined anew for each formulation and each target surface. The droplet size data in the present study were derived using an assumed spread factor on fir foliage of 2.5. Recent measurements (8) using a mono-disperse droplet generator have shown the true factor to be 2.66. 

The literature data on the tortuosity factor r show a large spread, with values ranging from 1.5 to 11. Model predictions lead to values of 1/e s (8), of 2 (parallel-path pore model)(9), of 3 (parallel-cross-linked pore model)(IQ), or 4 as recently calculated by Beeckman and Froment (11) for a random pore model. Therefore, it was decided to determine r experimentally through the measurement of the effective diffusivity by means of a dynamic gas chromatographic technique using a column of 163.5 cm length,... 

A surface heat transfer coefficient h can be defined as the quantity of heat flowing per unit time normal to the surface across unit area of the interface with unit temperature difference across the interface. When there is no resistance to heat flow across the interface, h is infinite. The heat transfer coefficient can be compared with the conductivity the conductivity relates the heat flux to the temperature gradient the surface heat transfer coefficient relates the heat flux to a temperature difference across an unknowm distance. Some theoretical work has been done on this subject [8], but since it is rarely possible to achieve in practice the boundary conditions assumed in the mathematical formulation, it is better to regard it as an empirical factor to be determined experimentally. Some typical values are given in Table 2. Cuthbert [9] has suggested that values greater than about 6000 W/m K can be regarded as infinite. The spread of values in the Table is caused by mold pressure and by different fluid velocities. Heat loss by natural convection also depends on whether the sample is vertical or horizontal. Hall et al. [10] have discussed the effect of a finite heat transfer coefficient on thermal conductivity measurement. 

Equations 4.34 and 4.35 do not depend on the mobility or diffusion properties of ions other than via g in Equation 4.34 that can be mitigated by raising like at short fres- As the dispersion field in FAIMS is not low, scales with K super-linearly and, by Equations 4.32 and 4.33, sensitivity stiU decreases and resolution improves for species with higher K. However, the linear part of the dependence of Djx on K is cancelled per Equations 4.34 and 4.35 and the discrirnination is much less than that in flow-driven FAIMS. This may be seen by comparing Figure 4.9 versus Figure 4.2 for same ions and otherwise identical conditions. For example, the spread of values in the exponent of s(t s) at Wc = 750 kHz drops from 5.4 to 1.5 times, and the spread of Rq factors in the formula for R(t es) (Table 4.1) decreases... 

The discharge voltage strongly depends on the structural and technological features of the battery, on temperature, and on numerous other factors. The spread in values of the discharge voltage is greater than that of OCV values. 

FIGURE 1.79. Simulated Nyquist plots exhibiting the effect of a distribution in layer thickness L on the impedance response recorded at low frequency. The S denotes a numerical spread factor. We assume a log-normal distribution of the layer thickness with a variance = Si rj) and a mean value rj = logL. The spread factors are - 0.01, S2 = 0.03, S3 = 0.07, and S4 = 0.10. 

The different regimes of interest are illustrated in Figure 8 (drawn afla Ref. 30) for spherical particles. The cross-section has been normalized to its value at K=0. The oscillations only occur when the particle radius, a, is well-defined, and become damped as the radius takes on a spread of values(26). Figure 8a shows the Guinier region at low K. From equation 26, the intercept at K=0 is equal to C (ft,P - pn ) (Np fV). Thus, the initial portion cf the scattering curve gives information about the i cle size and volume fraction, provided die scatto ing contrast and instrumentation factors are known. 

The final distribution of herbicide over the treatment area is determined by surface wetting, which can be assessed from the value of the contact angle, though its measurement is complicated by hysteresis. Surface wetting is influenced also by (1) the spread factor, which depends on the ratio between the diameter of the wetted area and the diameter of the drop, and (2) the spreading coefiicient(s), which reflects the tension when a solid-liquid and a liquid-air interface are replaced by a solid-air interface. 

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