Typical Simulation Conditions

Most of the simulation results that are reported in the literature and all those considered here are for zero shear rate friction Reynolds numbers, Re o, 125, 180, 

Effects of Flow, Rheological, and Numerical Parameters on DNS of Turbulent Channel Flow of Dilute Polymer Solutions 

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After rigorous code evaluation, parametric simulations are then performed to look at the coupled transport and reaction phenomena in SOFCs. The typical simulation conditions from the literature are adopted and summarized in Table 6.2. 

Tests have been conducted with Monsanto high barrier nitrile resins using the common food simulating solvents (Table X) plus some typical beverages. Conditioning times and temperatures were based on applicable FDA regulations and guidelines (16). 

A typical simulation result is shown in Fig. 3. Under the given conditions, the concentration of fuel gas in bulk phase at the exit (Fig. 3a) is zero and the concentration of evaporative fuel gas at solid phase (Fig. 3b) at the exit did not reach the equilibrium concentration of activated carbon during adsorption. These results indicate that the canister of ORVR system is properly designed to adsorb the evaporative fuel gas. The temperature changes in canister (Fig. 3 c) during the operation remains in the acceptable range. The test results for different weather conditions showed that the canister design in this study can fulfill the required performance. 

Fig. 28. Size distributions from a typical simulation produced by the VILM model. After six cycles a steady size is reached. Smaller sizes are obtained after five cycles as compared to the final distribution. The conditions for the simulation are /, . = = 100 Pa s, = 0.2,...

The maximum value of the diffusivity occurs when zJzi — 0.5 and has a magnitude 0.21w.Zj. For typical meteorological conditions this corresponds to a diffusivity of 0(100 m sec" ) and a characteristic diffusion time defined by of 0(5zi/w ). Yamada (1977), for example, has observed dififusivities of 0(100 m sec" ) when simulating the Wangara day 34 field experiment. Above the surface layer the observational evidence is inadequate to verify more than an order of magnitude estimate of the diffusivity. Clearly there is a need for more field data to establish the shape of the profile in the upper portions of the mixed layer. 

Two sets of typical operating conditions are used for the simulations presented. These are shown in Table IV and will be referred to as standard type I or II conditions. Type I corresponds to operation at moderate to high temperatures, pressures, and flow rates with relatively low inlet CO and H2 concentrations and small amounts of inlet CH4, C02, and HzO either from recycle or from the upstream process. Type II is based on conditions for the industrial use of methanation in synthetic natural gas production. Note that the inlet methane concentration is much higher than in type I. 

Simulations show that the radial and axial temperature and bulk concentration profiles are effectively not influenced by these modeling differences. Figure 9 shows the radial concentration profiles at = 0.38 and at the reactor outlet. Even with very high Peclet numbers, the differences between the radial concentration profile across the relatively small bed and the assumed uniform profile are minimal. Under typical operating conditions with small Peclet numbers, there is no benefit to increasing the number of radial collocation points, especially in light of the increased dimensionality of the resulting system. 

Another approach has been to model sequential reactions by using multiple advection-dispersion equations [207]. The use of multiple ADEs provides a more realistic model where each reactant can degrade, sorb, and disperse. Simulations using this type of model reveal that breakthrough of degradation products could occur despite complete removal of the parent compound, TCE [207]. Additional simulations were used to explore the effect of slow sorption (i.e., nonequilibrium sorption), and the results suggest that it is reasonable to assume that an FePRB will reach steady-state conditions under typical field conditions. 

The effectiveness factors based upon the generalized modulus concept were calculated in each axial increment used in the numerical integration of (19/ 20 and 21). The saving in computer time, as compared with solving the differential equations for mass transfer inside the particle in each increment, is enormous, in particular since the particle shape is an additional complication. The simulation results based upon the complete model (equations 19-27) cure represented in Figures 5 and 6 for typical operating conditions. 

Table I shows the flexibility of the computational system. Six types of frequently encountered problems are classified according to their respective boundary conditions. In each classification, one or more run options can be selected. For example, Class 1 are typical simulation problems where the reactor outlet pressure and feed conversion are specified and the inlet pressure and radiant temperature are calculated. Alternatively, the effect of fouling can be determined by calculating a coking factor from a known pressure drop. The following examples illustrate applications of the system in problems under Classes 1, 5 and 6 respectively.

Typical simulation results are shown in Fig. 8.10. At time equals zero, the fresh feed flowrate FoC is reduced by 25 percent from its base-case value. The process responds to this change by gradually cutting back on the other feed streams and the product leaving the unit. The new steady-state conditions are attained in a little over 1 hour. The control structure also successfully handled the other disturbances. 

Typical operating conditions were 140 K with about 3 W of additional heat added to the cold end. A few experiments were performed with the cold end inserted into a room temperature gelatin to simulate biological heat loads. Catheter tip temperatures of 160 to 175 K were achieved and ice balls with diameters of about 26 mm and a mass of 11 g were created. 

These results have demonstrated that snow photochemistry involves several complex chemical processes. Such a system can only be accounted for with a comprehensive reaction mechanism. Therefore, we used available experimental and field data to assemble a comprehensive reaction mechanism for surface snow. In addition, rate constants for the reactions involved for typical polar conditions in summer at snow temperatures of -20 °C are presented together with typical initial concentrations of the stable compounds involved in the mechanism. First simulations are performed for typical summer conditions in Greenland and results of these calculations are presented. 

Fig. 9 (A) A typical simulation results for spreading 3-D dewetting simulation with (B) initial condition for 100% layer loading and (C) relaxed film with a rough, dewetted surface. Black indicates a bare surface and white indicates peaks.

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