See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/230839606 Assessing the Significance of the Indigo Aerodynamic Agglomeration Technology using Mie/LIF Laser Diagnostics Conference Paper · January 2006 CITATIONS READS 0 57 5 authors, including: Graham J Nathan Richard M. Kelso University of Adelaide University of Adelaide 324 PUBLICATIONS 3,205 CITATIONS 165 PUBLICATIONS 1,800 CITATIONS SEE PROFILE Rodney Truce 3 PUBLICATIONS 0 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Particle-laden turbulent flows View project Understanding Flow Structure View project All content following this page was uploaded by Graham J Nathan on 03 June 2014. The user has requested enhancement of the downloaded file. SEE PROFILE ICESP X – Australia 2006 Paper 9B1 ASSESSING THE SIGNIFICANCE OF THE INDIGO AERODYNAMIC AGGLOMERATION TECHNOLOGY USING MIE/LIF LASER DIAGNOSTICS P KALT†, G NATHAN†, R KELSO†, R TRUCE‡ AND J WILKINS‡ † TEC Group, University of Adelaide, ‡ Indigo Technologies, Pty Ltd. pkalt@mecheng.adelaide.edu.au ABSTRACT A detailed laser diagnostic study has been performed to determine whether aerodynamic mechanisms may be exploited to promote significant agglomeration of fine particles to larger ones, with a view to enhancing the capture of fine and ultra-fine particles in conventional particle collection devices, such as Electrostatic Precipitators. This study was prompted by a series of findings from full-scale trials of a aerodynamic mixing device by Indigo Technologies, which led them to patent technology based on the aerodynamic agglomeration processes. The study assessed the extent to which the patented Indigo Agglomerator technology achieved an increase in the number collisions between PM2.5 droplets and PM 10-50 droplets and, in turn, in the capture of the small by the large droplets using aerodynamic processes. The studies were conducted in the potential core region of a large unconfined jet produced by a wind tunnel contraction. The small water droplets were generated with a TSI atomiser and marked with concentrated Rhodamine 6G dye to allow them to be discriminated from the large droplets. The large droplets were generated by a commercial fine-spray nozzle and were not dyed. Two cameras were used, one to image the fluorescent signal from the fine droplets only, and the other to image the Mie scattered signal from both droplets. The measurements were performed for arrangements with and without the aerodynamic mixing device in place, and with one or both of the droplet streams introduced into the flow. The fluorescent signal from the small droplets is found to decrease significantly, but only for the case where both the large and small droplets are present in the flow along with the aerodynamic device. This clearly shows that the aerodynamic device used in the Indigo Agglomerator technology greatly increases the number of collisions between large and small particles, providing an explanation for the increased capture efficiency found in the industrial-scale Indigo Agglomerator technology. 1 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics INTRODUCTION Ultra-fine particles, smaller than 2.5µm (known as PM2.5 ) are notoriously difficult to remove from particle-laden flows, such as the exhaust gases of industrial power generation utilities. These fine particles pose several risks to wellbeing. Fine particles are able to penetrate deeper into the bronchioles within the lung, creating a serious health risk. Fine particles are able to remain airborne for longer where they may act as nuclei to initiate condensation of atmospheric water vapour. The consequence is disruption of cloud formation, the formation of non-rain yielding clouds mass, and the appearance of brown smog. In fact, since the wavelength of light in the visible spectrum approaches the size of these small particles, the particles strongly attenuate visible light when airbourne, and hence also dominate the opacity of the exhaust stack gases. For these reasons there are already strong incentives to control the emission of PM2.5 particles, and it is anticipated that regulations will be introduced to impose strict controls on the emissions of these ultra-fine particles. Indigo Technologies have developed a patented pre-filter device to enhance the capture of ultrafine particles by the pretreatment of particle-laden flows prior to its entry into conventional particle collection systems. This pre-filter device was developed to pre-agglomerate fine to large particles. In a series of full-scale trials of the device, Indigo deduced that both aerodynamic and electrostatic mechanisms must be significant, since agglomeration was found to occur with the electrical power switched off. This led to a series of investigations being commissioned by Indigo (Nathan and Kelso (2004), Nathan et al (2005), Kalt et al (2005)) to assess the efficacy of aerodynamic agglomeration. The present paper reports on a particular study that seeks to assess the significance of aerodynamic agglomeration in the removal of small particles. To this end, a modified Planar Dropsizing method is employed, using simultaneous Mie and LIF scattering imaging methods. This method assesses directly the number of fine particles that are removed by aerodynamic agglomeration after the particle-laden flow is passed over the Indigo device. The experiment compares the number of fine particles in the flow for all combinations of fine particles only, large particles only, both sizes of particles, and the device inserted or removed from the flow. This allows an unambiguous assessment of whether or not the devices cause agglomeration of small to large particles by aerodynamic means. EXPERIMENTAL METHOD Experimental Setup A uniform flow with low turbulence intensity has been provided by a rectangular-section windtunnel at the University of Adelaide, comprising a fan, flow conditioning section and contraction. This creates a free jet of uniform initial mean velocity and low turbulence intensity whose cross section is 720 × 340mm. The mean velocity of the flow is 6 m/s, which falls just outside the 812 m/s range common in the exhaust ducts of power stations. The mean velocity was unable to be increased further without diluting seeded droplets to an extent that signal quality was compromised. The flow is uniform within the potential core region of this jet, whose cross section is a triangular in both planes, and whose length is about 2m. The jet is directed into a bell-mouth funnel and extraction system used to remove the droplet-containing flow from the lab. The mixing device is placed in the potential core of this jet, where the flow is uniform, as shown in Fig 1. This configuration avoids the need for windows, which would result in optical distortion and signal attenuation. 2 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics Selection of Particles Liquid droplets, instead of solid particles, were chosen because they are more amenable to investigation, making their measurement more cost-effective. Compared with solid particles, liquid droplets are easier to generate, easier to collect, easier to measure and easier to interpret. Droplets are spherical, while many solid particles are irregular in shape. Being spherical is a great advantage in the measurement of particle size since the light-scattering properties of spherical particles are known, while those of non-spherical particles are not. The use of spherical particles allows measurement techniques with high spatial resolution that cannot be used for non-spherical particles. Liquid droplets have higher agglomeration efficiency than do solid particles. The dominant cohesive force for solid particles smaller than about 100µm is the van der Waals force, while for liquids it is the liquid bridge force (Masuda and Gotoh, 1997). In this same range, the liquid bridge force is half an order of magnitude stronger than van der Waals force, making the droplets more likely to adhere. The higher bonding potential of liquids can be used to advantage in the present investigation because it means that it is reasonable to assume that “if it hits, it sticks” – that is every collision will result in agglomeration. This avoids also needing to know the percentage of collisions that lead to adherence – information that, to our knowledge, is not presently available, given the complex dependence of van der Waals force upon particle shape and size. Nevertheless, although the bonding potential of liquids is higher than that of solids, the evidence suggests that the extent of this difference is small in practical applications. Although both Van der Waal’s and Coulombic forces are strongly dependent on physical properties and shape, it is possible to estimate their relative significance. Masuda and Gotoh (1997) have estimated that, for particles of 1µm, Van der Waal’s forces are two and half orders of magnitude stronger than the Coulombic forces associated with electrostatic charging, while for 10µm particles they are an order of magnitude stronger. Hence the van der Waals forces are probably strong enough to provide strong agglomeration forces for the smallest particles anyway, and the additional forces of the liquid bridge are not expected to greatly affect agglomeration – especially of the smallest particles of greatest interest. It is relatively easy to produce a limited range of different sized droplets using commercially available droplet generators. In this experiment, the two size ranges of droplets are produced. The small droplets, which are dyed, are generated using a TSI seeder that produces a droplet of nominal 1µm diameter. This equates to the size where electrostatic precipitators are least efficient. The large droplets are generated using a pressurized spray nozzle, directed upstream within the wind-tunnel, so that the droplets in the size range of 10-20µm are convected to the mixing device with the small droplets, as shown in Fig. 2. Experimental Technique The technique used in this paper is a modified variation on the Laser Sheet Dropsizing technique (LSD), less commonly known as Planar Dropsizing (PDS). LSD involves the simultaneous measurement of the laser-induced fluorescence (LIF), here of a fluorescent dye dissolved within the droplets, and the Mie scattering from the droplets. Key previous investigations of the 3 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics technique include the pioneering work of Jermy and Greenhalgh (2000) and Zimmer et al., (2002). It involves spreading the laser beam into a thin sheet, and imaging a slice of the illuminated flow simultaneously using two cameras as shown in Fig. 4. Mie Scattering. Mie scattering is the dominant mode of light scattering from particles whose diameter is of the same order as the wavelength of light. The signal strength of this type of scattering depends on the cross sectional area of the particle and the direction of the light relative to the sensor. The signal intensity of the Mie signal is proportional to the square of the diameter (d2 ) of the droplet or particle. LIF Signal. In this study, the droplets are seeded with Rhodamine 6G, which is a fluorescent dye that absorbs energy at the wavelength of the laser and then fluoresces at a different wavelength. The magnitude of the fluorescent signal depends on the quantity of dye, and hence both on the volume of the particle and the concentration of the dye. As the fluorescence occurs at a different wavelength it is possible to separate the LIF and Mie signals by the use of filters in front of each camera. Accordingly, the LIF signal is proportional to the cube of the diameter (d3) of the dye droplet. Modified LSD Technique In this study, we are limited by the dynamic range of the detectors and the difficulty in generating a large number of dyed large droplets. For this reason the normal LSD technique has been altered in two significant ways. First, rather than comparing the ensemble-averaged Mie and LIF images, a highly accurate spatial matching between the two cameras is performed, so that instantaneous image pairs can be compared. Second, the large droplets generated by the spray nozzle have such a large liquid flow rate that it is not practical to seed these particles with the Rhodamine 6G dye. Not only is it exceedingly messy, but since the LIF intensity varies as the cube of the diameter, one order of magnitude difference in the droplet sizes will result in a 3 order of magnitude difference in the LIF signal. The intensified CCD used to measure LIF doesn't have a large enough dynamic range to account for both the small and large droplets in one measurement. Such a situation will either result in the saturation of the camera array by the large signals from the large droplets, or the loss of the small signal from the small droplets due to inability to discriminate it from the background noise. Hence it is only realistic to seed the dye into the small droplets. However the seeding of only the small droplets is also a useful approach for the present investigation, since the small droplets are of primary interest. The number of small droplets can then be measured by introducing the “LIF is small droplet” assumption. That is, the assumption that the intensity of LIF signal is proportional to the number of small droplets within each measurement volume (measured by each pixel). RESULTS AND DISCUSSION Figure 5 presents the mean Mie and LIF images obtained for the cases a) with, and b) without the mixing device inserted into the flow, for the cases of small drops only, and both large and small droplets. The images were obtained with the light sheet in the transverse plane to the mixing device, and at a distance of 75mm downstream from its trailing edge. Several features are evident in the images. The region of “high” intensity “signal”, corresponding to the presence of drops, is only found in a roughly circularly shaped region. This 4 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics can be seen as the yellow to red of the pseudo-colour scale of these images. The fact that particles are only found in this roughly circular region is a result of the method of introducing the fine droplets through a circular tube, shown in Fig. 2. Also evident in the LIF images is a black circle. This is caused by pre-existing damage to this part of the detector that causes that part of the array to be unresponsive. Hence that part of the image should be ignored. Since only the small droplets contain dye, we first interpret the images under the “LIF is small droplet” assumption, i.e. that the intensity of LIF signal is proportional to the number of small droplets. This proves to be very insightful. We now compare the LIF images with no mixing device for the case with only small droplets and that with both big and small droplets (Fig. 5). It can be seen that the large droplets cause a slight reduction in the LIF signal. This is consistent with some of the small particles having collided with, and becoming adsorbed by (or caused to “agglomerate” to), the larger particles. Nevertheless, this effect is relatively small, so that most of the fine particles are transmitted (without agglomeration) through to the measurement plane. Next we compare the LIF images for the cases with and without the mixing device, and with both sizes of droplets (Fig. 5). It can be seen that the presence of the mixing device dramatically reduces the number of small droplets, as indicated by the LIF signal, when both the large and small droplets are present. This clearly shows that aerodynamic agglomeration is significant for the combination of a fine-scale vortex generator (i.e. the mixing device) and the presence of both the large and small droplets in the flow. Next we assess the amount of agglomeration caused by the mixing device when only small particles are present in the flow. Under this scenario, the “LIF is small droplet” assumption does not apply, since all droplets will have the same amount of dye whether they agglomerate or not. Fortunately, since all droplets are now dyed, the standard LSD method may be applied to determine the Sauter Mean Diameter, <D32 >, as being proportional to the LIF image (d3 ) divided by the Mie image (d2 ). In addition, some droplets are removed by contact with the mixing device. Hence the number of collisions between small particles only can be most effectively assessed by the comparison of the <D32> images of the small particles only, for the cases with and without the mixing device. A comparison of these two images can be found in Fig. 6. That figure also illustrates schematically how the calculation of drop-size is performed. No significant difference in the size of the fine droplets is evident for the cases with and without the mixing device present (the <D32> is almost the same in both cases). This clearly shows that the aerodynamic agglomeration of fine particles requires the combination of appropriate aerodynamic motions, as generated by the mixing device (shown in Fig. 7), and a significant number of the larger droplets. The instantaneous images also show clear evidence of “clustering” of the small droplets, both at fine-scales of turbulent motions, on order of millimetres, and at larger scales of tens of millimetres. Such clustering effects are known to occur in other two-phase flow processes, and may also be significant in the process of aerodynamic agglomeration. 5 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics CONCLUSIONS The investigation has demonstrated unambiguously that the process of aerodynamic agglomeration between relatively large and small particles can be significant in turbulent shear flows of suitable scale and intensity. More specifically, it shows that, under conditions that closely resemble those in the flue gases from a coal-fired power station, Indigo’s agglomeration device causes a substantial increase in the number of collisions between droplets of nominal size ~1µm and 10-20µm. A significant reduction in the number of fine particles was caused by the combined introduction of the large particles and the mixing device. This was demonstrated by a direct comparison of the amount of agglomeration for other combinations of droplets, (i.e. with large and small particles in a free stream flow, small particles only with mixing device, etc). Hence it is demonstrated that that the phenomenon of aerodynamic agglomeration is significant and that it is measurable. The present LSD arrangement is only able to provide a relative (i.e. comparative) measurement of collection efficiency since it cannot measure of the size distribution of the combined flow of large and small drops. This limitation arises because of the relatively poor dynamic range of LSD – that is it can only perform measurements of droplets size when the largest and smallest particles are relatively similar in size. A measure of the actual collection efficiency would require knowledge of the number density of large and small droplets before and after the collector. ACKNOWLEDGEMENTS The TEC Laser Diagnostics laboratory is supported by the Australian Research Council. REFERENCES Eaton, J.K. and Fessler, J.R. (1994). Preferential Concentration of Particles by Turbulence, Int. J. Multiphase Flow, 20, 169-209. Jermy M.C. and Greenhalgh D.A. (2000). Planar dropsizing by elastic and fluorescence scattering in sprays too dense for phase Doppler measurement, Appl. Phys. B, 71, 703–710. Kalt, P.A.M., Nathan, G.J. and Kelso, R.M. (2005). Planar Laser measurements of the aerodynamic agglomeration caused by Indigo's Emitter, Report to: Indigo Technologies, Consulting Report MECHTEST MT0659-3, Dept. Mech. Eng., University of Adelaide. Longmire, E.K. and Eaton, J.K. (1992). Structure of a particle-laden round jet . J. Fluid Mech, 236, 217 – 257. Nathan, G.J., and Kelso, R.M. (2004). Scaling and sensitivity analyses of the mechanism of aerodynamic agglomeration in particle filters, Report to: Indigo Technologies, Consulting Report MECHTEST MT0659-1, University of Adelaide. Nathan, G.J., Scarsella, A. and Kelso, R.M. (2004). An Assessment of the Dominant Flow Features of Indigo's Bi-Polar Agglomerators and their role in Aerodynamic Agglomeration, Report to: Indigo Technologies, Consulting Report MECHTEST MT0659-2, University of Adelaide. 6 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics Okuyama,K. (1997). Agglomeration in Gaseous State, Powder Technology Handbook, ed Gotoh, K., Masuda, H. and Higashitani, K., Marcel Dekker publishers, pp 155-164. Qamar, N., Nathan, G.J., Alwahabi, Z.T. and King, K.D. (2004). The Effect of Global Mixing on Soot Volume Fraction: Measurements in Simple Jet, Precessing Jet and Bluff Body Flames, Proc. Combustion Institute, 30, (1), 1493-1500. Zimmer, L., Ikeda,Y., Domann, R. and Hardalupas, Y., (2002). Simultaneous LIF and Mie scattering measurements for branch-like spray cluster in industrial oil burner, AIAA Paper, 020340. Figure 1: Wind tunnel arrangement 7 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics Figure 2: Delivery of small and large droplets within the wind-tunnel. Figure 3: Size distribution of droplets produced by the TSI atomiser (small droplets) and the spray nozzle (large droplets) 8 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics Figure 4: The optical arrangement of the imaging method. Imaging plane is downstream of the mixing device. Cameras are orthogonal to the imaging plane. Figure 5: The mean LIF, and Mie images for the cases: a) without; and b) with the mixing device. Results for each droplet case (small only & both droplets sizes) are shown. The imaged area is 56 × 56mm, 75mm downstream from trailing edge of the mixing device (if present). 9 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics Figure 6: The ratio of mean LIF to mean Mie images to provide drop size for the small particles only, and for cases: a) with the emitter; and b) without the emitter. Figure 7: A selection of (Mie) images of the instantaneous distribution of small droplets only, performed in the transverse plane with and without the mixing device in the flow. Viewing area: 56mm × 56mm. 10 ICESP X – June 2006 Assessing Agglomeration Using Mie/LIF Diagnostics View publication stats