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Base flow

Three examples of simple multivariable control problems are shown in Fig. 8-40. The in-line blending system blends pure components A and B to produce a product stream with flow rate w and mass fraction of A, x. Adjusting either inlet flow rate or Wg affects both of the controlled variables andi. For the pH neutrahzation process in Figure 8-40(Z ), liquid level h and the pH of the exit stream are to be controlled by adjusting the acid and base flow rates and w>b. Each of the manipulated variables affects both of the controlled variables. Thus, both the blending system and the pH neutralization process are said to exhibit strong process interacHons. In contrast, the process interactions for the gas-liquid separator in Fig. 8-40(c) are not as strong because one manipulated variable, liquid flow rate L, has only a small and indirec t effect on one controlled variable, pressure P. [Pg.736]

Note that rotational viscometers give true shear rates and if this is to be used with Newtonian based flow curves then, from above, a correction factor of (4n/3 + 1) needs to be applied to the true shear rate. [Pg.372]

Rezkallah KS (1996) Weber number based flow-pattern maps for liquid-gas flows at microgravity. Int J Multiphase Flow 22 1265-1270... [Pg.255]

Table 2 Fate and effects of metals in a stream receiving a point-source of metals (upper part of the table) or diffuse input via urban runoff (lower part of the table). Summary of the expected influence of four different hydrological situations base-flow in a rainy period a flood after a rainy period low-flow after a long period of low rainfall (water scarcity) and a flood produced after this drought. Metal concentration (M) metal retention efficiency (measured on the basis of the nutrient spiraling concept) exposure (dose and duration) bioaccumulation (in fluvial biofilms) and metal sensitivity (of biofihns)... Table 2 Fate and effects of metals in a stream receiving a point-source of metals (upper part of the table) or diffuse input via urban runoff (lower part of the table). Summary of the expected influence of four different hydrological situations base-flow in a rainy period a flood after a rainy period low-flow after a long period of low rainfall (water scarcity) and a flood produced after this drought. Metal concentration (M) metal retention efficiency (measured on the basis of the nutrient spiraling concept) exposure (dose and duration) bioaccumulation (in fluvial biofilms) and metal sensitivity (of biofihns)...
The first case is based on a hypothetical stream receiving a metal-poUuted source (for instance the outlet of a metal factory). In this case, metal concentration is expected to be driven by dilution, being higher under low-flow than under base-flow conditions and minimum during floods. Metal accumulation is expected to be maximum under low-flow conditions and proportional to the duration of this water scarcity situation. Chronic exposure will lead to community adaptation, which is often related to changes in species composition. Metals will therefore be bioaccumulated in fluvial biofihns and transferred to higher trophic levels in the fluvial food web. [Pg.50]

The second case (Table 2) illustrates a hypothetic urban stream receiving both metals and nutrients mainly via urban runoff. Since urban runoff is directly linked with rainfall episodes, metal inputs and exposure will be variable under base-flow during a rainy period and very low under a situation of water scarcity (low rain and low-flow). In this case, a sudden flow increase after strong rains may cause contrasting effects on water metal transport depending on the previous situation. If previous rains have already washed the metals retained in land and sediments, the... [Pg.50]

Proportional control can be based on the temperature of the third stage. Here FO is the base flow rate, KC is the proportional controller gain, and TSET is the temperature set point. Note that in order to guard against the unrealistic condition of negative flow, a limiter condition on F should be inserted into the DYNAMIC region. This can be accomplished with ISIM by the following statement... [Pg.349]

As a first step towards the analytical study of the dynamics of the mixed PTV-SHV regime in the vicinity of the SHV base flow, we consider a non-autonomous perturbation of system (4.4.3) as follows ... [Pg.427]

With the feed at its boiling point and constant molar overflow the base flows can be calculated as follows ... [Pg.541]

M.A. Gonzalez-Martinez, S. Morais, R. Puchades, A. Maquieira, A. Abad, and A. Montoya, Monoclonal antibody-based flow-through immunosensor for analysis of carbaryl. Anal. Chem. 69, 2812—2818 (1997). [Pg.77]

In real life, the parcels or blobs are also subjected to the turbulent fluctuations not resolved in the simulation. Depending on the type of simulation (DNS, LES, or RANS), the wide range of eddies of the turbulent-fluid-flow field is not necessarily calculated completely. Parcels released in a LES flow field feel both the resolved part of the fluid motion and the unresolved SGS part that, at best, is known in statistical terms only. It is desirable that the forces exerted by the fluid flow on the particles are dominated by the known, resolved part of the flow field. This issue is discussed in greater detail in the next section in the context of tracking real particles. With a RANS simulation, the turbulent velocity fluctuations remaining unresolved completely, the effect of the turbulence on the tracks is to be mimicked by some stochastic model. As a result, particle tracking in a RANS context produces less realistic results than in an LES-based flow field. [Pg.166]

Second, due to the difficulty of accessing multiphase flows with laser-based flow diagnostics, there is very little experimental data available for validating multiphase turbulence models to the same degree as done in single-phase turbulent flows. For example, thanks to detailed experimental measurements of turbulence statistics, there are many cases for which the single-phase k- model is known to yield poor predictions. Nevertheless, in many CFD codes a multiphase k-e model is used to supply multiphase turbulence statistics that cannot be measured experimentally. Thus, even if a particular multiphase turbulent flow could be adequately described using an effective viscosity, in most cases it is impossible to know whether the multiphase turbulence model predicts reasonable values for... [Pg.291]

Different concentrations of BG bacterial spores (103 107 spores per mL) were introduced into the electric field sensor chip-based flow cell and an appropriate... [Pg.432]

Artificial Neural Networks Applied to Potentiometric Acid-Base Flow Injection Titrations. [Pg.389]

Fig. 10.12 Chemiluminescence image of four spotted probes on a macroporous silicon-based flow-through chip after hybridization. Fig. 10.12 Chemiluminescence image of four spotted probes on a macroporous silicon-based flow-through chip after hybridization.
The difficulties of intensity-based flow cytometry are illustrated by the present difficulties of cell-by-cell measurements of intracellular calcium. This can be accomplished using the calcium probe Indo-l,(34 38) but requires an ultraviolet (UV) laser source which is not routinely available in flow cytometry (Indo-1 is an emission wavelength ratiometric probe). Flow cytometers routinely have argon ion laser sources with outputs of 488 or 514 nm. Measurement of intracellular ions other than Ca2+ is nearly impossible. (The SNAFL and SNARF probes should allow pH measurement from the wavelength-ratiometric data.(15))... [Pg.12]

Another way to produce biphenyl derivates using flow was described by Leeke et al. [34] where they performed a Pd catalyzed Suzuki-Miyaura synthesis in the presence of a base. First experiments were carried out in toluene/methanol solvent. A reaction mixture was passed through the encapsulated Pd filled column bed length 14.5 cm (some cases 10 cm) x 25.4 mm id. 45 g of PdEnCat. Base concentration, temperature and flow rate were optimized and at optimum parameters (0.05 M base concentration, 100°C and 9.9 mL/min) the conversion was 74%. Then the reaction was performed under supercritical conditions using supercritical CO2 at high pressure and temperature. After optimizing the concentration of base, flow rate, pressure and temperature, the highest conversion rate (81%) was observed at 166 bar and 100°C where the reactant mixture was monophasic in the supercritical state. This system is able to produce 0.06 g/min of the desired product. [Pg.409]

Fibre optic-based flow-through optical biosensors The dramatic advances in fibre optic development in die last decade have promoted construction of sensors where radiation, whether emitted, transmitted or reflected, is conducted fi-om the sample to the detection system. The wide variety of available optical waveguide types (solid rods, hollow cylinders, micro-planar geometries) has been used with varying success in sensor development. [Pg.85]

Fibre optic-based flow-through sensors... [Pg.176]


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Base case design flow diagrams

Base case design process flow diagram

Channel-based flow fields

Column-Base Level Control Via Feed Flow Manipulation

Control based on RQ and heat flow rate measurements

Converters Based on Periodic Reversal of the Flow Direction

Direct-flow-based contacting

Dispersion-based flow control

Drainage system base flow

Droplet based microfluidics capillary flows

Electric field, separations based cross-flow

Extraction Process Based on Slug Flow

Fibre optic-based flow-through optical biosensors

Fibre optic-based flow-through sensors

Flow cytometry, laser-based

Flow gravity based separation

Flow gravity-based separator

Flow-Based Particle Trapping and Manipulation

Flow-based method

Flow-through sensors for multideterminations based on integrated retention and detection

Heat-flow based systems

Laminar Flow-Based Fuel Cells

Models Based on the Core-Annular Flow Structure

Optical flow-through sensors based on a non-regenerable immobilized reagent

Piezoelectric flow-through sensors based on a non-regenerable immobilized reagent

Pressure flow pattern-based

RANS based models of reactive flow processes

Recycle-flow Coanda-effect Mixing Based on Taylor Dispersion

Recycle-flow Mixing Based on Eddy Formation

Sensors flow-cell-based

Stopped-flow acid-base catalysis

Surface tension gradient based flow

Wettability Based Flow Splitters

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