Maximum deviations, size

During the calibration the geometric distortions in the images are reduced from a maximum of more than 11 pixels to less than 0.3 pixels (pixel size about 0.28mm 0.28mm). The whole calibration results in a maximum deviation of the projected calibration marks from the measured calibration marks in the image of less than 0.4 pixel (2D-error). 

Eq. (3.466) has correlated several experimental data giving a maximum deviation of 0.04, for low particle sizes (< 0.4 mm diameter). This correlation is valid only in the creeping flow regime, i.e. Re(m < 10, for relatively small particles. The minimum predicted value of porosity is 0.37. Thus, the lower values predicted by the Broadhurst-Becker equation should not be used. This is the case of large particles, where the Wen-Yu correlations should be used. 

The design and rating of a fired heater is a moderately complex operation. Here only the completely mixed model will be treated. For this reason and because of other generalizations, the method to be described affords only an approximation of equipment size and performance. Just what the accuracy is, it is hard to say. Even the relatively elaborate method of Lobo and Evans (1939) is able to predict actual performance only within a maximum deviation of 16%. 

The maximum deviation from this dashed line in Figure 62 is only about 1% and can not explain the observed 10% variation of the Sommerfeld constant. Therefore, taking into account Eq. (9), it was concluded that the local lattice distortions due to the different size of the Y and Lu ions in the YxLui xNi2B2C compounds mainly reduce the electron-phonon interaction (Rosner et al., 2000). The dependence of Xph on the Y concentration resulting from Eq. (9) and N( p) is... 

The chronology of the experimental data is from first to last. The parameters have a mean of 0.7470872, maximum deviation from the mean of 0.0370847, and standard deviation of 0.0216772. There is no systematic trend in the deviation which is as it should be if we have treated the problem properly. The standard deviation is only 2.9% of the mean. We consider this to be a very satisfactory resolution of a difficult experimental problem. The small size and near-spherical nature of the crystal permitted a spherical sample absorption correction to be applied, for which fir was taken to be <0.5. 

Figure 6-2b shows the theoretical distribution for 10 equal-sized uncertainties. Again we see that the most frequent occurrence is zero deviation from the mean. At the other extreme, a maximum deviation of 10 C/ occurs only about once in 500 measurements. 

Solids cone, in feed (kg/cu.m) Flow rate (cu.m/s) Median size of solids in feed (gm) Standard deviation of feed (-) Maximum particle size in feed (pm) =r of data points to use ... 

Another way to reduce the dimensionality of the data set descriptors X is the so called Principal Component Analysis (PCA) technique 0olliffe, 1986). It seeks to find out a new set of variables named Principal Components (PC) showing the data in order of decreasing variance with the aim to state the main information in the variables by the principal components of X. The primary Principal Component (PCI) describes the maximum deviation in the whole data set. The subsecjuent principal component (PC2) describes the maximum remaining variance, and so forth, with each axis linearly independent, to the preceding axis. Some of the last compwnents may be discarded to decrease the size of the model and stay away from over-fitting. 

The standard deviation both of the cumulative distribution and of the density distribution decreases to values of zero for minimum and maximum particle size classes without respect to any reproducibility. 

Figure 17.12 shows the results for the jet from the parabolic inlet velocity profile upon first reaching the end of the computational domain at f = 30. The local mean radius exhibits a more stable behavior compared to the constant profile with amplitudes of similar size, but less frequency for the oscillations, pm and the maximum deviation are both set in relation to the nozzle radius Rq and therefore display a downward slope caused by the decreasing size of the cone-shaped jet toward the tip. The surface area expansion F and /niax display a huge... 

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