Pressure fluctuation influence

Fig. 4 shows the accumulated standard deviation error, ss, with the measuring time of the pressure fluctuation for a good fluidization case (a) and a locally poor fluidization case (b). Pressure 1 and 2 were measured at the exit and the center air-headers of the FBAC respectively. Pressure 3 and 4 were measured at the entrance air-headers of the FBAC. As shown in Fig. 4 (a) and (b), the accumulated standard deviation error, ss, stayed in a limited range if the bed is in good fluidization state, but ss for the entrance of the FBAC decreased steadily if the bed is in local poor fluidization state. This may be Ifom the decrease of the bubble explosion force and frequency, which have influence on the standard deviation enxir of the pressure fluctuation, at the bed surface due to the bubble break and bypass around the poor fluidization area. Therefore, we can easily detect the local poor fluidization through this simple method. Additionally, as detecting the local poor fluidization, we could also regulate the overall or local airflow rate to clear up the local poor fluidization, as shown in Fig. 5. The accumulated standard deviation error, deviated from a limited range due to poor fluidization, shows to return into a limited value after regulations of local airflow rates.

Reciprocating-piston pumps deliver a constant flow at si fixed backpressure. At high pressures some minor flow variability ziay arise due to the compressibility of the mobile phase. Soms instruments incorporate a flow controller which provides a fixadi backpressure for the pump to work against, independent of the column backpressure. The influence of pressure fluctuations, solvent compressibility, and solvent viscosity on the volumetrie output of the pump are thereby eliminated. Reciprocating-piston pumps can provide continuous solvent delivery, fast solvent change--... 

Fitzgerald et al. (1984) measured pressure fluctuations in an atmospheric fluidized bed combustor and a quarter-scale cold model. The full set of scaling parameters was matched between the beds. The autocorrelation function of the pressure fluctuations was similar for the two beds but not within the 95% confidence levels they had anticipated. The amplitude of the autocorrelation function for the hot combustor was significantly lower than that for the cold model. Also, the experimentally determined time-scaling factor differed from the theoretical value by 24%. They suggested that the differences could be due to electrostatic effects. Particle sphericity and size distribution were not discussed failure to match these could also have influenced the hydrodynamic similarity of the two beds. Bed pressure fluctuations were measured using a single pressure point which, as discussed previously, may not accurately represent the local hydrodynamics within the bed. Similar results were... 

The onset of turbulent fluidisation appears to be almost independent of bed height, or height at the minimum fluidisation velocity, if this condition is sufficiently well defined. It is, however, strongly influenced by the bed diameter which clearly imposes a maximum on the size of the bubble which can form. The critical fluidising velocity tends to become smaller as the column diameter and gas density, and hence pressure, increase. Particle size distribution appears to assert a strong influence on the transition velocity. With particles of wide size distributions, pressure fluctuations in the bed are smaller and the transition velocity tends to be lower. 

Figure 19.3 Influence of equivalence ratio on antinodal RMS pressure fluctuation annular flow arrangement, bulk mean velocity in main flow, Um = 7-5 m/s bulk mean velocity in pilot stream. Up = 8 m/s Re j = UmD/v = 40,000, axial separation between annular ring and step, A = 0.513. 1 — 4 m = 0.62 2 — 0.70 3 — 0.76 dashed line corresponds to flame detachment...

Figure 19.7 Influence of swirl on antin-odal RMS pressure fluctuation flow arrangement with swirl bulk mean axial velocity of main flow in swirler, Um = 17 m/s, Reynolds number in swirler (for isothermal conditions). Res = UmD/v = 56,000 1 — Sw = 0.6 2 — 1.35 3 — 1.8 4 — 2.4 and 5 — 3.75...

The most important characteristics involved in pressure fluctuation are the frequency and the amplitude and must therefore be the major focus of investigation into pressure fluctuation. In addition, it is necessary to understand the distributions of the frequency and the amplitude of fluctuation over the space inside the reactor and the influences of some factors on them. 

In principle, pressure fluctuation signals can be determined directly by suitable probes. However, the device used for the measurement must meet two essential requirements (1) the frequency response of the instrumentation, including the probes and recorder etc., must match the range of signals to be measured, and (2) the influence of the probes on the flow field in the space to be detected must be minimized as possible. Otherwise, reality or even a near reality cannot be achieved. 

The structure of the experimental SCISR is the same as that shown in Fig. 10.2 for convenience of operation it is without cover. The propellers are driven by two motors of stable speeds and with a stepless-speed-adjustable device. Highly accurate micro pressure probes of Model XCQ-062 made by the Kulite Corporation are used for measuring the pressure fluctuation. The outside diameter of the probes is 1.6 mm, which is very small in comparison with the dimensions of the reactor so that their influence on the flow field can be negligible. In addition, the inherent frequency of the probes is 330 kHz, much higher than those to be measured, and thus complete fluctuation signals can be detected without any loss. 

The pressure fluctuation must affect the condition of the micromixing in the device and thus promote process kinetics. The results to be introduced in the next chapter will provide the experimental evidence for this topic. Unfortunately, a quantitative description for such influences cannot as yet be made because of the complexity of the problems involved, and further investigations are certainly needed in order to make the relationships clear, particularly the influence of pressure fluctuation on micromixing. 

QUALITATIVE ANALYSIS FOR THE INFLUENCES OF PRESSURE FLUCTUATION AND MICROMIXING... 

Influences of micromixing and pressure fluctuation What are the mechanisms of their effects How can direct experimental evidence be obtained for these effects How can these influences be quantitatively described How can their individual contributions to the global influence be determined ... 

The main function of the septum, or screen, is to support the filter aid, which, as we have seen, actually does the filtering. A heavy dense septum is therefore not necessary except where there may be cake instability due to pressure fluctuations or other outside influences. If the cake is discharged dry and is thick or heavy, a strong septum should be used. 

Possible influences of nonequilibrium cross-diffusion effects on the mixing process were investigated by means of direct numerical simulations (DNS) of mass fraction fluctuations in stationary isotropic turbulence for binary mixtures under supercritical conditions (26,27). The authors have shown that after some time, the initially perfectly mixed species become segregated owing to the presence of temperature and pressure fluctuations and the resulting Soret mass cross-diffusion fluxes Jj and /f, induced by temperature and pressure gradients. Based on DNS results (26,27), we propose a phenomenological model that predicts the rate of production of the concentration variance as... 

Let us assume that at some initial time t = 0 relative to the adiabatic atmosphere. Then, from (16.A. 14) we see that if Q = 0, the condition of T = 0 is preserved for t > 0 even though there may be motion of air. Also, the equation of motion (16.A.11) reduces to the usual form of the Navier-Stokes equation for the dynamics of an incompressible fluid under the influence of a motion-induced pressure fluctuation p with no contribution from buoyancy forces since T = 0. Therefore, for an atmosphere with no sources of heat and initially having an adiabatic lapse rate, the temperature profile is unaltered if the atmosphere is set in motion. As a result, the adiabatic condition can be envisioned as one in which a large number of parcels are rising and falling, a sort of convective equilibrium. Thus, we have been able to derive the relation for the adiabatic lapse rate here from the full equation of continuity, motion, and energy, in contrast with the derivation presented in Section 16.1.1, which is based on thermodynamic arguments. 

The reactor vessel is usually a stirred tank. The monomer phase is subjected either to turbulent pressure fluctuations or to viscous shear forces, which break it into small droplets that assume a spherical shape under the influence of interfacial tension. These droplets undergo constant collisions (collision rate >1 s ), with some of the collisions resulting in coalescence. Eventually, a dynamic equilibrium is established, leading to a stationary mean particle size. Individual drops do not retain their unique identity, but undergo continuous breakup and coalescence instead. In some cases, an appropriate dispersant can be used to induce the formation of a protective Aim on the droplet surface. As a result, pairs of clusters of drops that tend to coalesce are broken up by the action of the stirrer before the critical coalescence period elapses. A stable state is ultimately reached in which individual drops maintain their identities over prolonged periods of time [247]. 

B. The vapor pressure of a substance determines its potential maximum air concentration and influences the degree of inhalation exposure or airborne contamination. Vapor pressures fluctuate greatly with temperature. 

Qu et al. [2] observed in their experiment that hydrodynamic instabilities influence inlet and outlet pressures and can induce a degree an uncertainty in the measurement of pressiu-e drop. They recorded temporal pressure signals and made the following observations even with a small heat flux supplied to the parallel channels, the case of pressure drop oscillations presents pressure fluctuations with quite constant frequency, whereas in the case of instability in the parallel chaimels, the fluctuaticHis are small and random. 

Figure 21.14. A schematic depicting how fluctuations in the capillary pressure, APc and the disjoining pressure, AHmax influence the local barrier height relative to the imposed capillary pressure along the film (a) a typical spatial fluctuation (b) a local depletion zone due to monolayer density fluctuations...

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