**3. Experimental analysis of physicochemical processes**

Several analytical and instrumental techniques have been developed for the study of complex hydrodynamic-mediated processes found in particle-laden flow—flocculation, wet agglomeration, sedimentation, floatation, fluidization and crystallization that often occur in a wide range of process conditions. These techniques shown in **Figure 4** are used either in the quantification of the hydrodynamics of the carrier and dispersed phase, or in the determination of the spatial and temporal evolution of the discrete phase properties such as the change in the particle size and distribution. In the case of the hydrodynamic interactions of the carrier and dispersed phase, a number of laser-based fluid flow techniques such as particle image velocimetry (PIV), particle tracking velocimetry (PTV), laser Doppler anaemometry (LDA), laser Doppler velocimetry (LDV), and more recently, radioactive tracking techniques such as positron emission particle tracking (PEPT) and computer-aided radioactive particle tracking (CARPT) have gained wider acceptance in the scientific community and in industry due to

**Figure 4.** Experimental measurement techniques for multiphase particulate flow (reproduced from [18] with permissions © 2012 CRC Press).

their ease of use and non-intrusive nature [20–22]. These techniques provide valuable insight into the salient macroscale fluid flow characteristics such as the instantaneous and time-averaged hydrodynamic behaviour of the continuous phase, as well as the influence of the dispersed phase on the fluid flow. This is achieved by coupling the flow field measurements with the particulate phase properties and motion [21]. The experimental data set is subsequently used in the validation of numerical simulation results [18, 23].

The dominant and widely used macroscale experimental fluid flow characterization techniques are the laser velocimetry and radioactive particle tracking techniques such as the PIV or PTV, LDV or LDA with the PIV reported to be a more efficient technique [24]. These on-line methods facilitate the determination of the properties of multiphase particle-laden flow especially at low concentration. These local methods are quite superior to other similar techniques such as optical fiber probing and light scattering due to their non-intrusive nature with little or no interference on the flow while providing time series and time-averaged fluid flow characteristics with a high spatial resolution [18]. The workings of typical field imaging technique such as PIV consist of the tracer particles, laser source for flow illumination and high capacity cameras—complementary metal-oxide semiconductor (CMOS) or charge-coupled device (CCD) for the fluid flow image recording. The captured images are thereafter post-processed and correlated to obtain the hydrodynamic parameters of interest. **Table 1** provides a list of recent publications on the experimental analysis of physicochemical processes in stirred tanks. These studies demonstrated the importance of robust and reliable experimental data for complex fluid flow analysis and numerical model validation. Recent advances in experimental techniques have led to the emergence of radioactive particle tracing measurement techniques which aim to improve the ease of data collection, data accuracy and reliability.

and the reactor performance under a particular process condition. For instance, the conventional physicochemical simulation tests such as the cylinder, Imhoff cone and jar tests can be combined with parametric analytical techniques such as the Buchner-funnel or pressure filtration test, capillary suction time (CST) test, electrokinetic charge analysis using colloidal titrations (i.e. zeta and streaming potential), laser light scattering or laser diffraction, microscopy, image analysis, photometric dispersion analysis (PDA), fiber optic sensor and HNMR spectroscopy. These techniques have been successfully employed to characterize the physicochemical process in bench, pilot and full-scale studies [38–41]. A careful consideration of the limitations of each of these approaches will ensure proper selection of an

**Table 1.** Selected studies on the experimental analysis of physical and chemical processes in stirred tanks.

appropriate method.

**Reactor configuration** **Stirrer configuration**

impellers

semi-elliptic disc turbine

turbine impeller

Cylindrical tank Hydrofoil

Cylindrical tank Hollow blade

Cylindrical tank Pitched-blade

Cylindrical tank Kenics static

Cylindrical tank Pitched-blade

Cylindrical tank Pitched-blade

Square tank Hydro foil

Cylindrical tank Six-blade

Cylindrical tank Six-blade

Cylindrical tank Rotor-stator

Cylindrical tank Rushton turbine,

mixer

turbine

turbine

impeller

Rushton turbine

pitched-blade turbine

Rushton turbine

mixer

**Experimental technique**

Cylindrical tank Rotating disc 2D PIV Mixing/agglomeration Silver-coated and hollow glass

Hydrodynamic Characterization of Physicochemical Process in Stirred Tanks and Agglomeration Reactors

Cylindrical tank Rushton turbine PIV Mixing Polymeric and glass particles

Cylindrical tank Rushton turbine CARPT Mixing Radioactive particles [29] Cylindrical tank Rushton turbine LDA Mixing Hollow glass spheres [30]

> PIV, image analysis

**Technical application Tracer particles**

PEPT Mixing Radioactive particles [26]

TRPIV, PIV Mixing Neutrally buoyant glass beads

FPIV Mixing Soda-lime glass beads [28]

PEPT Mixing Radioactive particles [31]

PEPT Mixing Radioactive particles [32]

PIV Mixing Silica glass spheres [23]

3V3 Mixing Opt image polycrystalline

PEPT Mixing Monosized silica gel particles

PEPT, LDA Mixing Ion-exchange resin particles

PIV Mixing Polyamide particles [37]

spheres [1]

http://dx.doi.org/ 10.5772/intechopen.77014

63

[27]

[24]

Mixing/agglomeration In situ agglomerated flocs [33]

[35]

[36]

particles [34]

In order to correlate the hydrodynamic and process conditions with the suspension or dispersion properties especially the change in the species concentration—spatial and temporal evolution of the particle size distribution, a number of laboratory measurement techniques are widely adopted [25]. The choice will depend to a large extent on the concentration and size distribution of the disperse phase and the nature of the flow. Regardless of the chosen analytical approach, such a correlation will facilitate an assessment of the treatment process Hydrodynamic Characterization of Physicochemical Process in Stirred Tanks and Agglomeration Reactors http://dx.doi.org/ 10.5772/intechopen.77014 63


their ease of use and non-intrusive nature [20–22]. These techniques provide valuable insight into the salient macroscale fluid flow characteristics such as the instantaneous and time-averaged hydrodynamic behaviour of the continuous phase, as well as the influence of the dispersed phase on the fluid flow. This is achieved by coupling the flow field measurements with the particulate phase properties and motion [21]. The experimental data set is subsequently

**Figure 4.** Experimental measurement techniques for multiphase particulate flow (reproduced from [18] with permissions

The dominant and widely used macroscale experimental fluid flow characterization techniques are the laser velocimetry and radioactive particle tracking techniques such as the PIV or PTV, LDV or LDA with the PIV reported to be a more efficient technique [24]. These on-line methods facilitate the determination of the properties of multiphase particle-laden flow especially at low concentration. These local methods are quite superior to other similar techniques such as optical fiber probing and light scattering due to their non-intrusive nature with little or no interference on the flow while providing time series and time-averaged fluid flow characteristics with a high spatial resolution [18]. The workings of typical field imaging technique such as PIV consist of the tracer particles, laser source for flow illumination and high capacity cameras—complementary metal-oxide semiconductor (CMOS) or charge-coupled device (CCD) for the fluid flow image recording. The captured images are thereafter post-processed and correlated to obtain the hydrodynamic parameters of interest. **Table 1** provides a list of recent publications on the experimental analysis of physicochemical processes in stirred tanks. These studies demonstrated the importance of robust and reliable experimental data for complex fluid flow analysis and numerical model validation. Recent advances in experimental techniques have led to the emergence of radioactive particle tracing measurement techniques which aim to improve the ease of data collection, data accuracy and reliability.

In order to correlate the hydrodynamic and process conditions with the suspension or dispersion properties especially the change in the species concentration—spatial and temporal evolution of the particle size distribution, a number of laboratory measurement techniques are widely adopted [25]. The choice will depend to a large extent on the concentration and size distribution of the disperse phase and the nature of the flow. Regardless of the chosen analytical approach, such a correlation will facilitate an assessment of the treatment process

used in the validation of numerical simulation results [18, 23].

62 Laboratory Unit Operations and Experimental Methods in Chemical Engineering

© 2012 CRC Press).

**Table 1.** Selected studies on the experimental analysis of physical and chemical processes in stirred tanks.

and the reactor performance under a particular process condition. For instance, the conventional physicochemical simulation tests such as the cylinder, Imhoff cone and jar tests can be combined with parametric analytical techniques such as the Buchner-funnel or pressure filtration test, capillary suction time (CST) test, electrokinetic charge analysis using colloidal titrations (i.e. zeta and streaming potential), laser light scattering or laser diffraction, microscopy, image analysis, photometric dispersion analysis (PDA), fiber optic sensor and HNMR spectroscopy. These techniques have been successfully employed to characterize the physicochemical process in bench, pilot and full-scale studies [38–41]. A careful consideration of the limitations of each of these approaches will ensure proper selection of an appropriate method.

In most of the physicochemical processes involving particulate flow either as a colloidal dispersion or granular suspension, the species attributes—mean size, particle concentration and distribution and fractal properties of the resulting agglomerates—are the primary parameters of interest [21]. In this case, an appropriate physicochemical simulation such as a jar or cylinder test is often followed by a parametric analysis to characterize the process performance as a function of species attributes. Several other parameters may be of interest depending on the type of reactor and the required solid-liquid separation method. Such parameters may include aggregate mean size, shape and distribution, aggregate volume concentration, aggregate strength, sludge volume index, silting index, residual supernatant turbidity, absorbance or optical density, electrical conductivity, viscosity, zeta or streaming potential, specific resistance to filtration, capillary suction time, and so on [38, 39]. In the case of chemical optimization, a parametric dose-response curve will give reasonably accurate information on the required chemical dose for a particular process condition [42–45]. **Table 2** and **Figure 5** show a typical correlation of the agglomerate test properties with the process condition—shear rate. However, regardless of the choice of parametric test, an examination of the supernatant, sediment, filtrate and residue will yield some valuable information on the reactor performance under specific process conditions. Such assessment is carried out either by direct *in situ* measurements such as in particle counting, *ex situ* analysis in which the samples are extracted for measurements or by other indirect parametric indicators. A detailed discussion on the practical applications of different dispersed phase measurement techniques is available elsewhere [40, 41].

Considering the wide range of options available to select from, optimizing a given physicochemical condition for a particular process reactor under laboratory conditions is a daunting task. Therefore, in optimizing the design and process parameters for a particular reactor, a statistical correlation of these parameters from a data set is often required, depending on the available time and complexity of the problem, to obtain accurate information on the optimum design and process conditions. A number of statistical methods such as the design of experiment and response surface methodology can be applied to a large set of experimental data to obtain the desired optimization points. This will facilitate an understanding of the influence of different process conditions on the reactor performance which will assist in the selection of optimized operating conditions.

**4. Modeling physicochemical processes in stirred tank reactor**

experimental data.

165 rpm.

The use of computational fluid dynamics (CFD) as a research tool to investigate complex fluidparticle interactions has been growing in popularity both in academia and in the industry [46]. CFD provides a powerful alternative and a more robust platform for engineers in the design of equipment and processes involving fluid flow and heat transfer when compared to the classical experimental approach. Nowadays, numerical simulations complement the experimental and analytical techniques and are increasingly being performed in many fluid engineering applications ranging from chemical and mineral processing to civil and environmental process engineering [46]. However, it is worth pointing out that the continual development of reliable empirical, mathematical and computational models relies on a robust and detailed

**Figure 5.** A parametric correlation of agglomerate properties with the process condition—shear rate (a) 145 rpm and (b)

Hydrodynamic Characterization of Physicochemical Process in Stirred Tanks and Agglomeration Reactors

http://dx.doi.org/ 10.5772/intechopen.77014

65

**Tables 3** and **4** provide a list of recent experimentally validated numerical studies focusing on the physicochemical analysis of fluid-particle reactors. The former is focused on the analysis of the mixing phenomena in stirred tanks while the latter deals with the technical application of mixing


**Table 2.** Agglomerate characteristics test properties as a function of the reactor agitation speed in a wet agglomeration process.

Hydrodynamic Characterization of Physicochemical Process in Stirred Tanks and Agglomeration Reactors http://dx.doi.org/ 10.5772/intechopen.77014 65

**Figure 5.** A parametric correlation of agglomerate properties with the process condition—shear rate (a) 145 rpm and (b) 165 rpm.
