Single-shot planar temperature imaging of radiatively heated fluidized particles

Kimberley C.Y. Kueh; Timothy C.W. Lau; Graham J. Nathan; Zeyad T. Alwahabi

doi:10.1364/OE.25.028764

1. Introduction

The heating of particles suspended in a flow is a phenomenon that occurs in a wide range of industrial processes, such as in combustion environments, mineral processing plants and, more recently, in the particle receivers under development for high temperature concentrated solar thermal (CST) systems [1,2]. However, the heat transfer in these non iso-thermal particle-laden flows remains poorly understood because of its complexity, which arises from the coupled and non-linear mechanisms of particle-fluid interactions, inter-particle collisions, particle clustering and radiation attenuation [3,4]. This lack of detailed understanding limits current capacity to optimize particle-laden systems, improve process efficiencies and develop new technologies. Therefore, a reliable, non-intrusive, in situ and spatially resolved technique to measure particle temperatures is necessary for the study of heat transfer within turbulent particle-laden flows. Good temporal resolution is also needed to allow multiple fluctuating qualities to be measured. The overall objective of the present investigation is to contribute to meeting this need.

A range of alternative laser diagnostic measurement techniques meet the criteria by making use of various sophisticated instruments and different optical components to provide in situ and high-speed measurements with high resolution that allow multiple fluctuating quantities to be measured [5]. Among the laser diagnostic techniques most commonly used for temperature measurement of the gas phase, the coherent anti-Stokes Raman spectroscopy (CARS) technique is well-established for accurate point-resolved measurements, and recently planar measurements, even in harsh environments. However, it is not yet to be developed for measurements in the presence of particles [6]. Alternatively, Rayleigh scattering technique is well-established for planar measurements of the gas phase, but are not suited to the measurement of flowing particle temperature [7]. They are also challenging to implement in the presence of particles because of the strong interference from spurious light scattering. Another laser-based method is the laser-induced fluorescence (LIF) thermometry. This utilizes tracers added to the gas flow and is a robust technique typically used to study the relationship between mixture formation and temperature [8]. However, LIF investigations are suited to the measurement of gas or liquid phase, rather than to particles and must also address the effect of halation around the particles.

In contrast, laser-induced phosphorescence (LIP) is a technique that mitigates the effects of these occurrences by using the temperature-dependent properties of thermophosphors (TPs) to determine the temperature of the particles. This technique makes use of phosphorescent emissions of TPs governed by the temperature-dependent Boltzmann distribution where the emission spectra shifts with respect to wavelength, the extent of the shifting of which varies with the type of TP used [9]. For the present investigation, the spectral intensity ratio method of LIP is used. Here, the intensity ratio, I_r, is calculated by:

I_{r} = \frac{I_{1} - B_{1}}{I_{2} - B_{2}} \times \frac{I_{2, r e f}}{I_{1, r e f}}

where I is the phosphorescent emission intensity, B is the background signal, the subscripts 1 and 2 is the signal taken at the 2 selected wavelength region and ref denotes a reference case [8]. One advantage of this technique is that a range of TPs exist, each with its own properties such as decay lifetime, emission intensity, operating temperature, and effect of oxygen quenching as documented by many studies [10–12]. This offer the potential to optimize the measurement for any given experimental condition by the selection of an appropriate TP. However, applications of LIP to date have mostly been directed to measurement of the gas-phase temperature using the TP as a tracer, rather than as a measurement of the particle phase itself [13–15]. These measurements have found that volume-averaged measurement of the gas-phase temperature is most effective with relatively high volumetric loadings of the TP. Importantly, this avoids the need to resolve the temperature of individual particles. The resulting accuracy of this type of measurement has been reported to be high. For instance, Abram et.al [14]. reported a temperature precision of 4K (5.3%) at low temperature ranges (~363K), and up to 3K (1.4%) at higher temperatures (~500K) using 2µm Eu:BAM particles, while Lawrence et.al [16]. reported measurement errors up to 3.1% for 2.9µm Eu:BAM particles and 10.1% for 10.2µm Dy:YAG particles. However, these approaches of using tracer particles in LIP to measure the flow temperature relies on the assumption that the temperature of the gas phase and the particle phase are in equilibrium locally. Hence it can only be applied where heating rates are relatively low and cannot be used to measure heat transfer between particles and the flow. Additionally, despite the high accuracy of the technique, little progress has been made on its application to single-shot particle temperature measurement.

In addition to a laser diagnostic method, a systematic study of the accuracy of a particle temperature measurement technique requires a well-controlled heat source that is capable of achieving high enough heating rates of the particle relative to the flow for the two phases to have a significant temperature differential. This is necessary to measure heat transfer in a particle-laden flow. The preferred method of achieving well-defined, high heating rates of particles is via a radiative heat source because this can be used to heat only the particles via careful choice of wavelength to avoid absorption lines of the gas phase. Previously, radiative heat sources to achieve this have employed various types of lamps such as deuterium, xenon, and tungsten [17,18]. However, these sources cannot be used to generate a true point source, but rather generate “hot-spots” in which certain heating regions have higher heat fluxes than others. It is also difficult to achieve sufficiently high heating rates for the particle temperature to differ significantly from that of the fluid. An alternative solid-state system that achieves uniform, high fluxes with known optical direction has recently been demonstrated by Alwahabi et.al [19]. This Solid-State Solar Thermal Simulator (SSSTS) is capable of delivering continuous, well-defined heat flux of up to 36.6 MW/m² and operates at a peak wavelength of approximately 910nm, which is absorbed by particles but not by the air.

This investigation is to demonstrate a direct, in situ, non-intrusive, planar measurement of particle temperature in a turbulent flow under well-characterized heating with high-flux radiation. In particular, we aim to determine the resolution and accuracy of a temporally and spatially-resolved, single-shot application of LIP for the measurement of the temperature of micron-sized particles suspended in an unsteady flow heated with a high flux source of laser irradiation.

2. Experimental

2.1 Particle heating by radiation

The particles were heated with the well-defined and high heat flux heat source Solid-state Solar Thermal Simulator (SSSTS) reported by Alwahabi et.al [19]. This provides 3kW of continuous radiation at fluxes, Ф, of up to 36.6 MW/m² for which the heating profile, region, and flux are well-characterized and easily controlled. The 910nm wavelength of the SSSTS was chosen to minimize heating of the carrier gas, which in the current experiment was dry air. The SSSTS beam converges from a diameter of 46mm at the fiber-optic head (FOH) to a waist of 10.5 ± 0.1mm diameter over the distance of 520mm-540mm from the FOH.

2.2 Optical arrangement

The optical arrangement is presented in Fig. 1. Here, the third harmonic of an Nd:YAG laser (Quantel Q-smart 850) operated at 5.27 ± 0.47mJ and 355nm (shown in purple in Fig. 1) was used to excite the ZnO:Zn TPs suspended within in a fluidized bed (FB). Three cylindrical lenses (L₁, L₂ and L₃) were used in series to manipulate the excitation laser beam and generate a laser sheet of 300µm thickness at the measurement test section. The subsequent phosphorescent emissions (shown as dotted lines in Fig. 1) from the ZnO:Zn TPs were then recorded with an ICCD camera (PI-Max/PI-Max2, Princeton Instruments) through a 40mm spacer (sp) and an f/2.8 Tamron imaging lens (ImL). The imaging area was 15 mm × 10.8 mm, viewing the y and z plane of Fig. 1. An image splitter, IS (Opto-Split II, Cairns Research), with an in-built conventional dichroic mirror with a 50:50 ratio was used to transmit two images onto a single ICCD camera, as shown in Fig. 2. The use of a single ICCD camera offers the advantage over the more commonly used 2-camera system for LIP of minimizing errors during image processing because both images are collected simultaneously. Two high transmission (> 93%) interference filters at 392 ± 9nm (FF01-392/18-25, Semrock) and 440 ± 20nm (FF01-440/40-25, Semrock) were selected specifically to detect ZnO:Zn phosphorescent emissions. These two bands were selected because they provide the highest sensitivity to the particle temperatures below 625°C [12]. The camera gain, gate width and gate delay were set to 5, 26ns and 51ns respectively, to maximize the phosphorescence signal. The mirror (labelled as M4 in Fig. 1) was also carefully aligned to be 45° with respect to the ICCD camera to minimize relative distortion of recorded images.

Fig. 1 Optical arrangement. Note that the temperature-controllable oven replaces the fluidized bed during calibration. Purple line: 355nm Nd:YAG laser beam path; Red line: 910nm Solid-State Solar Thermal Simulator (SSSTS) beam path; Blue dashed line: optical collection path of phosphorescence emission. BD: Beam Dump; BS: Beam Splitter; ImL: Imaging Lens; L: Lens; M: Mirror; P: Polariser; PM: Power Meter; sp: spacer; WP: Waveplate.

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Fig. 2 Image collection via an image splitter. The phosphorescence signal from the excited particles in the fluidized bed were reflected by a mirror (M₄) and passed through the imaging lens (ImL) and spacer (Sp) before entering the image splitter (IS). A beam splitter (BS) within was used to separate the signal to a 50:50 ratio and allowed to pass through different filters, F₁ (392 ± 9nm) and F₂ (440 ± 20nm), the collection wavelengths of which are shaded in blue in the insets. Images over the z and y planes were then collected with an ICCD camera. Temperature is determined from the ratio of the filtered images.

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The thermophosphor particles chosen here are made from ZnO:Zn and obtained from Phosphor Technology with a size distribution of 1µm-50µm. It was found during the course of the investigation that the sole use of ZnO:Zn TPs led to significant particle agglomeration, consistent with the findings of Abram et.al [14]. Other previous investigations [20,21] have also shown that particles in a fluidized bed of the diameter and sphericity used here have a natural tendency to agglomerate. To minimise these effects, 100µm-200µm sized CaSO₄·2H₂O particles were mixed with the TPs with a volumetric ratio of 20:80. These CaSO₄·2H₂O particles were chosen not only for their size, but also because they do not emit any phosphorescent signals when excited at the excitation wavelength of 355nm (thereby avoiding interference with signals emitted by the ZnO:Zn particles). The mixture of CaSO₄·2H₂O and ZnO:Zn particles was placed in an optically-accessible fluidized bed. The fluidized bed has four 32mm diameter apertures positioned diametrically opposed from each other, with two transmitting the Nd:YAG laser and SSSTS beams through the axis of the reactor and two providing access for the imaging measurements. The path of the Nd:YAG laser was propagated along the y-axis of the system, as shown in Fig. 1, and was offset from the SSSTS beam (shown in red in Fig. 1) path by 7° such that they intercepted at the 10.5mm waist of the SSSTS beam and at the centre of the fluidized bed. A flow controller (Alicat Scientific, MC 20slpm) was used to deliver dry air at a constant volumetric flow rate of 6.5L/min. Dry air was used as an added precaution to avoid the contribution to particle agglomeration that can arise due to humidity. A UV beam splitter (BS) was placed 300mm from the front of the Fibre-optic Head (FOH) of the SSTS laser to split the beam at intensity ratio of 92:8. The low-power beam was directed to a water-cooled power meter (Gentec model HP100A-4KW-HE, labelled as PM₂ in Fig. 1), while the high power beam was passed pass through the working section of the fluidized bed chamber before impinging onto a separate, but similar, water-cooled power meter (labelled as PM₁ in Fig. 1). The power meter readings were recorded at fixed sampling rate of 10Hz. The particle mass loading within the system was estimated by calculating the radiation attenuation by the particles, ${\dot{Q}}_{a t t}$ . This value was calculated by taking the difference between the two power meter readings at every time-step after correcting for differences in beam power due to the beam splitter, i.e. ${\dot{Q}}_{a t t} = {\dot{Q}}_{i n} - {\dot{Q}}_{o u t}$ , where ${\dot{Q}}_{i n}$ is the power recorded by PM₁ multiplied by 100/92, and ${\dot{Q}}_{o u t}$ is the power recorded by PM₂, multiplied by 100/8.

Four K-type thermocouples were also placed within the experimental facility - one protruding into the fluidized bed upstream from the heating zone, one about 50mm downstream from the heating zone within the fluidized bed to provide a measure of the overall rise in the gas-phase temperature, one on the outer surface of the fluidized bed reactor and one on the metal enclosure encapsulating the system for safety. The temperatures of all four thermocouples were monitored with an analogue-to-digital converter and recorded to a computer. Table 1 presents the summary of the experimental parameters in the present investigation.

Table 1. Summary of experimental parameter ranges.

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2.3 Temperature calibration

The calibration investigation was performed with a similar experimental arrangement to that described in Section 2.2, except that the fluidized bed in Fig. 1 was replaced by a temperature-controlled oven (MTI Corporation, OTF-1200X-S). A copper plate of 30mm diameter was coated with ZnO:Zn TPs and placed in the oven. The heated plate was then placed within the Nd:YAG laser path such that the excitation laser beam was orthogonal to the plate. The excitation laser beam size and energy was kept constant during calibration. Additionally, a separate K-type thermocouple was attached to the surface of the TP-coated plate to measure in situ the temperature of the TP.

2.4 Image processing

Images were collected through an image splitter, which combines side-by-side onto a single ICCD array image collected through a filter at bandwidth 440 ± 20nm and the other at 392 ± 9nm. Each of the two images records an area of 15mm × 10.5mm and each is collected simultaneously. This avoids the potential for errors associated with different time-delays and/or angular distortion that are typical of using traditional two-camera systems. The resultant spatial resolution for each image was 51 pixels/mm. In-house Matlab codes were then used to divide the original image into two sub-images. The steps performed to obtain particle temperature from the raw images, as illustrated in Fig. 3, are outlined below:

Fig. 3 Image processing procedure of two images obtained from two filters, F₁ (392 ± 9nm) and F₂ (440 ± 20nm): (1) threshold background noise and incoherent signals which, (2) calculate intensity ratio from 2 filtered images, (3) derive temperature from the calibration.

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1. Each instantaneous image was thresholded by the average pixel count of the background image to remove electrical noise, as presented in Eq. (1). The background image here refers to the image recorded using the same experimental setup but without the presence of particles. The signal-to-noise ratio (SNR) for the images taken with the 392 ± 9nm filter varied from 13 at Ф = 0 W/m² to 5.6 at Ф = 21.1 MW/m². Conversely, the SNR for the images taken with the 440 ± 20nm filter was between 5.4 at Ф = 0 W/m² and 11 at Ф = 21.1 MW/m². This is due to a shift in the phosphorescent emission spectra as the particle temperature increases due to increasing heat flux. It can be seen from Fig. 3 that the final image of temperature yields measurement of significantly fewer particles than do the raw images. This is because data from particles with a non-physical diameter have been rejected. More specifically, particles that are not in the focusing plane appear artificially larger than the actual particle agglomerate size, leading to intensity ratio images that are not reflective of the true particle temperatures. To estimate the true diameter of particle agglomerates, independent images of particles in the fluidized bed were recorded with a NIKON D5500 camera (f/3.1) without excitation at room temperature. It was found that ~80% of the particles comprise agglomerates of diameter in the range 100µm-250µm. Hence particle agglomerates with an imaged diameter > 300µm were assumed to be out of the image plane and were eliminated. Additionally, the inferred temperature images of particle agglomerates showed that the measured temperature is significantly greater at the outer edges of some particle agglomerates. This is due to weak signals in these areas, leading to high errors due to a low signal to noise ratio. To account for this, the weighted centroid of each particle agglomerate was found and used to reject the signal from the pixels at the outside of the particles.
2. The two sub-images were super-positioned to overlap each other to within plus/minus 0.1 pixels. This was achieved by utilizing the same image processing method as for the superposition the sub-images with a gridded target, which enables the average offset between the two sub-images to be calculated. Arrays of intensity ratios, I_r, were then calculated by dividing the two sub-images on a pixel-by-pixel basis. A previous investigation of the influence of excitation (355nm) laser fluence on intensity ratio showed that the intensity ratio varied by approximately 25% between laser fluence values of 2.6mJ/cm² and 5.17mJ/cm². This stems from a slight dependence of phosphorescent emission spectra on the laser fluence. To correct for this, the intensity ratios were normalized by the equivalent intensity ratio obtained at room temperature to correct for this influence following Abram et.al [22];
3. Particle temperatures were then inferred from I_r and from the calibration data.

Since particle temperatures may vary in space and time, it is necessary to assess whether the rate of change in temperatures are sufficiently low for local thermodynamic equilibrium to be established. That is, it is necessary to assess whether the temperature of each agglomerate can be determined accurately without considering spatial and/or temporal thermal gradients. This is assessed by comparing the rate of cooling via convection and heating or cooling via radiation relative to the internal transfer via conduction over the particle volume. The Biot number was used to ascertain the degree of thermal equilibrium for the case of convective cooling. Here, the Biot number, Bi [23], is defined as:

B i = \frac{h (\forall_{p} / A_{p})}{k_{p}},

where

A_{p} = 4 π r^{2}

is the surface area of the particle being heated,

h = \frac{N u k_{g}}{D_{p}}

is the convective heat transfer coefficient,

N u = 2 + (0.4 \times R e^{0.5} + 0.06 \times R e^{\frac{2}{3}}) \times P r^{0.4} {(\frac{μ_{a}}{μ})}^{0.4}

is the Nusselt number,

R e = \frac{ρ V_{p} D_{p}}{μ}

is the Reynolds number, V_p = 0.6m/s is the slip velocity,

\forall_{p}

is the particle volume, k_p is the thermal conductivity of the particle, and k_g is the thermal conductivity of the gas. For cases where Bi « 1, the rate of conductive heating within the particle volume is significantly greater than that of convective cooling, implying that the particle has approached thermal equilibrium. The converse is true for Bi » 1. By analogy, a dimensionless cooling parameter,

β_{c}

, was obtained by modifying Eq. (2) to include cooling by convection and radiation, defined as:

β_{c} = \frac{ε σ (T_{1}^{4} - T_{a}^{4}) (\forall_{p} / A_{p}) F_{12} + h (T_{1} - T_{a}) (\forall_{p} / A_{p})}{k_{p} (T_{1} - T_{a})},

where ε = 0.9 is the emissivity, F₁₂ = 1 is the view factor of the particle to the surrounding gas and

σ = 5.67 \times 10^{- 8}

m²K⁻⁴ is the Stefan-Boltzmann constant. There, the value of k_p varies with respect to temperature from 27 W/mK at 22°C to 6 W/mK at 700°C [24]. Similarly, to assess equilibrium with regard to radiant heating, we modified Eq. (2) to obtain the heating parameter,

β_{h}

, which is the ratio of radiative heat absorption by the particle from the heating laser to the internal heat conduction is defined as:

β_{h} = \frac{Q_{r a d} F_{13} α}{k \frac{d T}{d D_{p}}},

where F₁₃ = 0.5 is the view factor and α = 0.15 is the absorptivity of ZnO particles. The values of the dimensionless parameters, Bi,

β_{c}

and

β_{h}

together with Nu and h were evaluated for T₁ = 300°C, T_a = 22°C and radiative flux, Ф, of 21.1 MW/m². These are presented in Table 2 for a range of particle diameters. As can be seen, both Bi and

β_{c}

« 1, which implies that cooling effects are insignificant.

β_{h}

is also « 1. This suggests that the particles approach thermal equilibrium, with any gradients that may be present (e.g. for the largest particles) being small.

Table 2. Characteristic heat transfer parameters estimated for various particle agglomerate sizes assuming T₁ = 300°C, T_a = 22°C and radiative flux, Ф = 21.1 MW/m².

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3. Results and discussion

3.1 Temperature calibration

To calibrate the temperature of the ZnO:Zn particle agglomerates as a function of phosphorescence emission, 45 sets of measurements were systematically collected at temperatures ranging from 22°C to 425°C. For each temperature, the TP-coated plate was allowed to reach thermal equilibrium before 100 images were taken. The average intensity ratio was then calculated from the 100 instantaneous measurements for each temperature. The relationship between the intensity ratio and temperature was then used to infer particle temperature from the second set of experiments undertaken within the fluidized bed. The accuracy of the calibration was found to be within ± 1% after comparing the intensity ratio of the 100 instantaneous measurements at the same temperature.

3.2 Moving particle temperature measurement

During each measurement, suspended particles were subjected to simultaneous excitation by the Nd:YAG laser and radiative heating by the SSSTS. Measurements of particle temperature were taken with 14 different values of heat flux with the SSSTS laser in the range of 2.4 MW/m² ≤ Ф ≤ 21.1 MW/m². For each of these measurements, the first 50 (≈30s) and last 100 (≈60s) of the 800 total shots were recorded with the SSSTS deliberately switched off. Figure 4 presents examples of particle images, in which columns A and B are individual particle agglomerate images taken with the FF01-440/40-25 and FF01-392/18-25 filters respectively, while column C shows the resultant inferred particle temperature, T_p, based on the calibration curve. Additionally, rows (1) to (5) present heat fluxes for the selected cases of 0 MW/m² (i.e. the case with no radiative heating), 3.34 MW/m², 6.93 MW/m², 12.4 MW/m², and 21.1 MW/m². As it can be seen, the particle intensity increases with the heat flux for the images in column A (440nm ± 20) and decreases for images in column B (392 ± 9nm). This shows that the emission spectra of the TPs shifts towards longer wavelengths as the heat flux is increased, consistent with the measurements of Särner et.al [12].

Fig. 4 Typical examples of image trios of particle agglomerates, comprising raw image pairs 440 ± 20nm (column A) and at 392 ± 9nm (column B), together with the resulting temperature, T_p (column C), recorded for five values of radiative heat flux, Ф: (1) 0 MW/m², (2) 3.34 MW/m², (3) 6.93 MW/m², (4) 12.4 MW/m², and (5) 21.1 MW/m².

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It can also be seen that most of the images of particles in Fig. 4 are non-spherical. This apparent non-sphericity was true for most particles. It is possible that this non-sphericity is genuine and is attributed to the agglomeration process, although a possible contributor is the artefacts that can arise, even for spherical particles, due to their interaction with a light sheet of finite thickness. Figure 5 presents examples of non-spherical images of particles, together with a plausible explanation of the type of shape that could be expected from the position of a spherical particle within a light sheet. In this figure, the direction of the excitation (355nm) laser sheet is from left to right and the camera is facing into the page at a direction orthogonal to the laser sheet. For the case in which the particle is entirely within the laser sheet (a), only half the particle facing the excitation beam is excited, so that the phosphorescence originates only from half of the particle. However, for the case where the particle is partly out of the laser sheet, the particle image can be either half-annular in shape (b) or a truncated circle (c), depending on whether the particle is out of the light sheet in the out-of-plane directions, respectively. This complicates the interpretation, because it is difficult to distinguish between small particles and particles that are simply not fully in the laser sheet. However, this challenge can be reduced in future applications through the use of mono-dispersed (and de-agglomerated) particles, for which the size is known.

Fig. 5 Examples of particle appearances with respect to their locations in the excitation laser sheet, y.

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3.3 Temperature distribution within a particle

Figure 6 presents a histogram of T_p/T_p,mean, where T_p,mean is the mean temperature of each individual particle, so that the ratio is normalized for each particle. The data is presented on a pixel-by-pixel basis calculated from all particles within the series of 650 captured ICCD images for the case in which Ф = 12.4 MW/m², together with temperature distribution of 2 individual particle agglomerates within the inset of the figure. It can be seen that the extreme range of measured temperature is ± 6% relative to the modal (i.e. most commonly occurring) temperature while the RMS of the temperature is ± 4%. Given that both $β_{c}$ and $β_{h}$ number of the particle agglomerates are <1 [see Table 1], it can be deduced that temperature gradient within any single particle is negligible. This deduction is further supported by observation of the distribution of the scatter in individual particles [Fig. 4], which appears to be random, rather than systematic. Therefore, the T_p variation observed in Fig. 4 can be attributed to noise from the two ICCD images, rather than to any actual temperature variations within the particles. On this basis, the influence of noise can be overcame by averaging from a sufficiently large number of pixels and the resolution of the present images can be deduced to be sufficient for the peak of the measured temperature to be reliably.

Fig. 6 Lumped probability distribution of the normalised temperatures within each particle, T_p, as calculated from all particles in the 650 images when heated at 12.4 MW/m², while the insets present the temperature distributions within individual particles.

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3.4 Heated particle temperatures

Figure 7 presents the mean of all particle temperatures, $\bar{T_{p, m}}$ , calculated from each series of 650 captured images as a function of radiative heat flux, Ф. The error bars here shows the maximum-minimum range of $\bar{T_{p, m}}$ at any given flux, which is attributed to fluctuations in particle mass loading in the fluidized bed flow between measurement shots. Despite some scatter, it can be seen that $\bar{T_{p, m}}$ scales linearly with Ф.

Fig. 7 Mean particle temperature, $\bar{T_{p, m}}$ , at various heat flux, Ф.

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Figure 8 presents the radial distribution of $\bar{T_{p, m}}$ each calculated from the relevant series of 650 images for which the radiative heat source was switched on, together with their standard deviations. It can be seen that in addition to the primary influence of heat flux on T_p, the distance of the particles from the source of radiation has a secondary influence. That is, particles closest to the heat source have a higher T_p than those further away, consistent with the expected role of attenuation. It can also be seen that particle temperature rises of between 40°C and 280°C were measured for Ф = 2.4 MW/m² and 21.1 MW/m², respectively. Given that temperature gradients within individual particles were negligible, this large scatter in T_p is attributed to the unsteadiness of particle mass loading within the fluidized bed, consistent with the fluctuations in the measured values by the power meter.

Fig. 8 Particle temperature, T_p, averaged from all particles over 650 images with respect to heating beam direction, y. Error bars represent the minimum-maximum particle temperatures while heat flux was kept constant: square: Ф = 0 MW/m²; triangle: Ф = 3.34 MW/m²; circle: Ф = 12.4 MW/m²; diamond: Ф = 21.1 MW/m².

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The local heating rate of the particles within the irradiated zone was calculated based on the residence-time, τ, of the particles within the heating zone. Several 2D, long exposure images were taken with the ICCD camera aligned normal to the laser sheet. The distance of each particle was recorded then divided by the 3ms exposure time to obtain an average velocity of 0.21m/s. On this basis, given the path length through the heating zone of 10.5mm, the average residence time was 0.035s, while the maximum value was 0.05s. Dividing the maximum temperature rise, ΔT_max, by the τ yields an averaged local heating of 23,000°C/s.

4. Conclusion

A temporally and spatially-resolved, single-shot temperature measurement of individual micron-sized particle agglomerates transported in an unsteady flow has been demonstrated. Measurements were performed for particle agglomerates of diameters 20µm ≤ D_p ≤ 300µm under $β_{c}$ and $β_{h}$ < 1), so that any gradients within the particle can be neglected to first order. This is consistent with the measured variation in pixel-to-pixel temperature being both randomly distributed spatially and within ± 4% for irradiated heat flux, Ф = 12.4 MW/m². Hence, this variation can be explained by the noise from the image intensifier of the ICCD camera, so that the average can be expected to provide a good measure of the particle temperature. Additionally, a spatial resolution of 51 pixels/mm was achieved, with the signal-to-noise ratio being approximately 11. This gives confidence that the mean temperature of the particle is reliable.

Mean particle temperatures in the range 100°C ≤ $\bar{T_{p, m}}$ ≤ 300°C were measured for the suspended particles irradiated with heat flux between 2.4 MW/m² ≤ Ф ≤ 21.1 MW/m². A maximum temperature rise of 350°C was recorded with a heat flux of 21.1 MW/m². For these conditions, the corresponding heating rate was estimated to be up to 23,000°C/s, given a maximum residence time of the particles in the heating region of 0.05s. The dependence of particle temperatures with respect to their distance from the heat source, residence time and heat flux was found to be consistent with expected trends, providing further confidence in the reliability of the method.

Funding

Australian Research Council: Discovery grant 150102230; Linkage Grant LE130100127.

Acknowledgment

The authors would also like to thank Mr. Jeffrey Hiorns and Mr. Jason Peak, from the mechanical workshop at the School of Chemical Engineering, for their outstanding technical support.

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Experimental Parameters
355nm laser fluence	5.27 ± 0.47mJ
Particle diameters	50 – 250 µm
Fluidized bed air flow rate	6.5 L/min
Measurement volume	10.5mm $\times$ 10.5mm $\times$ 300µm
Spatial resolution	51 pixel/mm
Calibration temperature range	22 - 423°C
SSSTS heat flux	0 – 21.1 MW/m²

Particle diameter, D_p	Re	Nu	h	*$B i$*	*$β_{c}$*	$β_{h}$
µm			W/m²K
50	0.636	2.32	$1777$	$5.7 \times 10^{- 4}$	$5.6 \times 10^{- 4}$	$2.7 \times 10^{- 3}$
100	1.273	2.46	$942.3$	$5.8 \times 10^{- 4}$	$7.3 \times 10^{- 4}$	$3.5 \times 10^{- 3}$
200	2.545	2.67	$510.1$	$6.2 \times 10^{- 4}$	$9.2 \times 10^{- 4}$	$7.1 \times 10^{- 3}$
300	3.718	2.83	$360.3$	$6.5 \times 10^{- 4}$	$1.1 \times 10^{- 3}$	$1.1 \times 10^{- 2}$

Experimental Parameters
355nm laser fluence	5.27 ± 0.47mJ
Particle diameters	50 – 250 µm
Fluidized bed air flow rate	6.5 L/min
Measurement volume	10.5mm $\times$ 10.5mm $\times$ 300µm
Spatial resolution	51 pixel/mm
Calibration temperature range	22 - 423°C
SSSTS heat flux	0 – 21.1 MW/m²

Particle diameter, D_p	Re	Nu	h	*$B i$*	*$β_{c}$*	$β_{h}$
µm			W/m²K
50	0.636	2.32	$1777$	$5.7 \times 10^{- 4}$	$5.6 \times 10^{- 4}$	$2.7 \times 10^{- 3}$
100	1.273	2.46	$942.3$	$5.8 \times 10^{- 4}$	$7.3 \times 10^{- 4}$	$3.5 \times 10^{- 3}$
200	2.545	2.67	$510.1$	$6.2 \times 10^{- 4}$	$9.2 \times 10^{- 4}$	$7.1 \times 10^{- 3}$
300	3.718	2.83	$360.3$	$6.5 \times 10^{- 4}$	$1.1 \times 10^{- 3}$	$1.1 \times 10^{- 2}$

Single-shot planar temperature imaging of radiatively heated fluidized particles

Abstract

1. Introduction

2. Experimental

2.1 Particle heating by radiation

2.2 Optical arrangement

2.3 Temperature calibration

2.4 Image processing

3. Results and discussion

3.1 Temperature calibration

3.2 Moving particle temperature measurement

3.3 Temperature distribution within a particle

3.4 Heated particle temperatures

4. Conclusion

Funding

Acknowledgment

References and links

Cited By

Figures (8)

Tables (2)

Equations (4)

Optics Express