Contour data

Smokeview visualizes FDS computed data hy animating time dependent particle flow, 2D slice contours and surface boundary contours. Data at a particular time may also be visualized using 2D or 3D contour plots or vector plots. 

The isotherm or contour data can also be viewed as a three-dimensional display, and this is shown in Figure 2.3. This representation of Equation 2.7 is that of one-quarter of the outside of a smooth, inverted bowl. 

FIGURE 28.2 MBIP for extracting PDF parameters from clinical E-wave contours. The Levenberg-Marquardt algorithm is applied to user-selected E-wave contour data as input to yield best-fit PDF parameters as output and a measure of goodness of fit denotes the unknown parameter value until the final fitting step. 

With 3D-CTVicwer the export of slice-contours from parts inside the data volume is possible via the DXF-format. From these contours a two-dimensional comparison to the CAD geometry is possible if the coordinate system and the absolute scaling between both methods are well known. 

The squares visible in figure 5 represent the position of hard particles at the moment of recording. Therefore the time distance between two video records is about 1,3 ms at a record rate of 750 Hz. With these data it is possible to calculate particle velocity. Figure 8 shows the particle movement in the molten bath caused by flow processes. The particles are captured at the contour of the molten bath and transported into the liquid phase. 

A two-dimensional slice may be taken either parallel to one of the principal co-ordinate planes (X-Y, X-Z and Y-Z) selected from a menu, or in any arbitrary orientation defined on screen by the user. Once a slice through the data has been taken, and displayed on the screen, a number of tools are available to assist the operator with making measurements of indications. These tools allow measurement of distance between two points, calculation of 6dB or maximum amplitude length of a flaw, plotting of a 6dB contour, and textual aimotation of the view. Figure 11 shows 6dB sizing and annotation applied to a lack of fusion example. 

Figure Cl.3.6. Contour plot of the H6(4,3,2) potential for Ar—HF, which was fitted principally to data from far-...

Many functions, such as electron density, spin density, or the electrostatic potential of a molecule, have three coordinate dimensions and one data dimension. These functions are often plotted as the surface associated with a particular data value, called an isosurface plot (Figure 13.5). This is the three-dimensional analog of a contour plot. 

Wave functions can be visualized as the total electron density, orbital densities, electrostatic potential, atomic densities, or the Laplacian of the electron density. The program computes the data from the basis functions and molecular orbital coefficients. Thus, it does not need a large amount of disk space to store data, but the computation can be time-consuming. Molden can also compute electrostatic charges from the wave function. Several visualization modes are available, including contour plots, three-dimensional isosurfaces, and data slices. 

This state of affairs is summarized in Fig. 9.4a, which plots contours for different values of [77] in terms of compatible combinations of mj /nij and a/b. For the aqueous serum albumin described in Example 9.1 as an illustration, any solvation-ellipticity combination which corresponds roughly to [77] = 5 is possible for this system. Data from some other source are needed to pin down a more specific characterization. 

We shall see in Sec. 9.10 that sedimentation and diffusion data yield experimental friction factors which may also be described-by the ratio of the experimental f to fQ, the friction factor of a sphere of the same mass-as contours in solvation-ellipticity plots. The two different kinds of contours differ in detailed shape, as illustrated in Fig. 9.4b, so the location at which they cross provides the desired characterization. For the hypothetical system shown in Fig. 9.4b, the axial ratio is about 2.5 and the protein is hydrated to the extent of about 1.0 g water (g polymer)". ... 

All that can be concluded from the data given in the preceding example is that the particle is not an unsolvated sphere. However, when an appropriate display of contours is examined for f/fo (e.g.. Ref. 2), the latter is found to be consistent with an unsolvated particle of axial ratio about 4 1 or with a spherical particle hydrated to the extent of about 0.48 g water (g polymer). Of course, there are a number of combinations of these variables which are also possible, and some additional experimental data—such as the intrinsic viscosity—are needed to select that combination which is consistent with all experimental observations. 

Different processes like eddy turbulence, bottom current, stagnation of flows, and storm-water events can be simulated, using either laminar or turbulent flow model for simulation. All processes are displayed in real-time graphical mode (history, contour graph, surface, etc.) you can also record them to data files. Thanks to innovative sparse matrix technology, calculation process is fast and stable a large number of layers in vertical and horizontal directions can be used, as well as a small time step. You can hunt for these on the Web. 

Figure 9.2-2 shows a data input screen in which general characteristics are input by radio buttons and numerical data is typed. The program calculates distances to specified in.sic concentrations and other requested consequence levels automatically. Results are available in a variety of formats including cloud footprints, sideview, cross section, pool evaporation rate, concentration vs distance and heat flux contours. Figure 9.2-3 shows the calculated results as a toxic plume. superimposed on the map with and without oligomerization. 

Heat-flux data obtained from calorimeters present in the fire-affected area revealed maximum heat fluxes of 160-300 kW/m. Figure 5.1 shows the calorimeter positions, the final contours of the flash fire, and heat-flux data from calorimeters positioned near or in the flames. No data are available on flame propagation during the vapor-bum tests. 

Figure 5.1. Final contours in Coyote test no. 5, calorimeter positions and calorimeter heat-flux data (Goldwire et al., 1983).

An example of the results obtained in the form of a chromatoelectropherogram can be seen in Figure 9.6. The contour type data display showed the three variables that were studied, namely chromatographic elution time, electrophoretic migration time, and relative absorbance intensity. Peptides were cleanly resolved by using this two-dimensional method. Neither method alone could have separated the analytes under the same conditions. The most notable feature of this early system was that (presumably) all of the sample components from the first dimension were analyzed by the second dimension, which made this a truly comprehensive multidimensional technique. 

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