TESTING A 25°C ■ 30°C■ 35°C■ 104 B 103 10-1 D 25°C ■ 30°C■ 35°C■ 104 100 Shear rate (1/s) C 101 102
0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
103 10-1 100 Shear rate (1/s) 101 102
0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
500 kg hr-1 750 kg hr-1 1000 kg hr-1
■ ■ ■
57
-0.015
-0.01
-0.005
0
0.005 Distance from pipe centreline (m)
500 kg hr-1 750 kg hr-1 1000 kg hr-1
■ ■ ■
0.01
0.015
-0.015
-0.01
-0.005
0
0.005 Distance from pipe centreline (m)
Figure 3: Experimental data: a) Hand dish wash – rheology; b) Hand dish wash – ERR velocity profiles; c) Shampoo – rheology; d) Shampoo – ERR velocity profiles9
algorithm, developed by Wang et al.4 ,
reconstructs both the linear and circular sensor tomograms. These tomograms may then be segmented into zones of interest to develop a number of radial velocity measurement positions in the pipe cross-section. A heat pulse is generated, within the sensor,
to deliver a minor increase in temperature to provide a small change in electrical conductivity which is tracked throughout the sensor. The use of a heat pulse provides uniform heating of the pipe cross-section; is 95 % efficient; is automated; does not require the physical inclusion of a tracer and provides negligible degradation of thermosensitive products.5 For a zone of the tomogram, the obtained
conductivity is averaged, normalised and subsequently the cross-correlation algorithm, developed by Papoulis6
, is employed to tag
the fluid motion across and within multiple measurement arrays. As the distance between the measurement arrays is fixed and known, the extracted time delay may then be converted into both two- and three-dimensional velocity profiles. However, due to the axisymmetric nature of velocity profiles in laminar flow, only the two-dimensional velocity profile is required in the determination of rheology7
, reducing
computational requirements. The rheological properties of a fluid strongly
influence the shape of the velocity profiles in laminar pipe flow due to a shear rate response
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of the fluid. The raw velocity measurements may alone act as a fingerprinting tool to predict rheological parameters; this can be used to infer rheological behaviour exhibited by complex fluids systems, i.e. shear-banding, wall depletion and shear-induced phase migration. The velocity profile may then be coupled with the measurement of differential pressure to obtain the linear shear stress profile in steady state, incompressible laminar flow. The rheological properties of a fluid can be
extracted from the velocity profile in a number of ways. If the rheological behaviour can be described by conventional rheological models i.e. the power law model, a parametric fitting of the velocity profile can be applied to determine the desired rheological properties.2 This approach is suited to extracting the
rheological parameters of fluids which adhere to simple models. A number of industrial fluids do not adhere to such models, however, and thus the approach is difficult to implement. Artificial intelligence algorithms offer an alternative means.
Experimental set-up To validate this novel technique, a number of industrial fluids were investigated at the pilot plant of a multinational manufacturer of homecare and personal care products. Stream’s industrial ERR sensor (Figure 2) was used within this study. An ERR sensor, of diameter 25.4 mm, was
installed within a simple recirculation pipeline. The flow loop contained a 200-litre jacketed vessel, agitated by an anchor impeller and a controlled centrifugal pump. The differential pressure measurement was obtained from a PMD55 sensor, supplied by Endress + Hauser, across a distance of 1 m, and was logged alongside parameters of flow rate and pressure. The jacket of the vessel was used to elevate
the fluid temperature to 25°C, monitored by a temperature probe at the vessel outlet, before the fluid was circulated at selected three flow rates of 500 kg hr-1, 750 kg hr-1 hr-1
and 1,000 kg . Upon completion, the fluid temperature
was increased to 30°C and the experimental protocol was repeated; this was once again repeated at 35°C. Three ERR measurements were performed for each experimental condition. To provide a comparison to off-line measurements, a Haake Rheostress1
0.01
0.015
rotational
rheometer from Thermo Fischer Scientific, equipped with a smooth-walled, 1° stainless steel cone and plate geometry, was used. Due to the thermosensitive nature of some of the products being tested, a Peltier plate was used to hold each sample at 25±0.1°C, 30± 0.1°C and 35± 0.1°C. To assess the impact which the time-shear history received during processing had upon the structure, samples were collected and off-line measurements performed at each experimental flow rate.
November 2021 PERSONAL CARE
Viscosity (mPas)
Viscosity (mPas)
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