- Email: [email protected]
Numerical simulation of silica particle trajectory in flow field and silica particle spheroidizing in oxygen–acetylene flame spheroidization process
Powder Technology 286 (2015) 451–458
Contents lists available at ScienceDirect
Powder Technology journal homepage: www.elsevier.com/locate/powtec
Numerical simulation of silica particle trajectory in flow field and silica particle spheroidizing in oxygen–acetylene flame spheroidization process Zhengjia Ji a, Hongyun Jin a,b,⁎, Yaoqing Wu a, Yunlong Li a, Min Liu a, Chunhui Xu a, Pan Hou a, Jie Dong a, Shuen Hou a,b,⁎ a b
Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, PR China
a r t i c l e
i n f o
Article history: Received 23 October 2014 Received in revised form 20 July 2015 Accepted 24 July 2015 Available online 7 August 2015 Keywords: CFD simulation Oxygen–acetylene flame spheroidization process Spherical silica Particle trajectory
a b s t r a c t A numerical simulation was developed for particle trajectory in flow field and spheroidizing of silica particle in oxygen–acetylene flame spheroidization process. Gas flow field and silica particle behavior in oxygen–acetylene flame spheroidization process was simulated using a Computational Fluid Dynamics (CFD) package FLUENT. A model was proposed for optimizing spheroidization process of silica particle. Oxygen gas and acetylene gas were used as the continuous phase. Silica particle was used as the dispersed phase. The three-dimensional, steady and isothermal flow field was showed for illustrating the continuous phase and the dispersed phase. Conservation equations of mass and momentum for each phase were solved using the finite volume numerical technique. Various gas conditions were discussed systematically. The injected silica particle trajectories were simulated by using dispersed particle surface trajectory. The trajectories and spheroidizations of different size particles were analyzed. The results of numerical simulation reveal that the flame length was reasonable and overall temperature was highest when acetylene gas flow rate was 10 L · min−1, oxygen gas flow rate was 20 L · min−1 and powder carrying gas flow rate was 5 L · min−1 and 40 μm silica particles were difficult to finish spheroidizing within 5 × 10−4 s. The comparison shows that temperature distribution, velocity distribution, particle trajectories, and deformation which were predicted by simulation, were in good agreement with the corresponding experimental results. © 2015 Elsevier B.V. All rights reserved.
1. Introduction With the rapid development of aerospace and information industry, spherical silica particle has attracted more and more attention [1–5]. Because it has the advantages of good fluidity, low thermal expansion and low stress concentration. The spherical silica particle was indispensable, especially in the large-scale integration (LSI) circuits packaging field. The flame spheroidizing process also was widely found in many industrial applications such as spraying industry, metal industry and ceramic industry. Therefore, it was very worthy and necessary to study spheroidizing process of raw silica material to improve the spheroidization rate and flame furnace design. In order to obtain perfect spherical silica particle, particle character and experimental operating condition were investigated [6–8]. In previous study, the researchers tried many experimental methods, which include the direct current arc plasma method, the ratio frequency ⁎ Corresponding authors at: Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China. E-mail address: [email protected] (H. Jin).
http://dx.doi.org/10.1016/j.powtec.2015.07.040 0032-5910/© 2015 Elsevier B.V. All rights reserved.
plasma process, the high-temperature fused quartz jet route and so on [9–12]. The literatures demonstrated changes in the particle morphology, structure and crystallinity during the spheroidization process [13–15]. For economic cost and high spheroidization efficiency, a new oxygen–acetylene flame spheroidization process has been developed [2]. Although the experimental researches for oxygen–acetylene flame spheroidization process have been conducted excessively, the process fundamentals were not yet fully understood due to difficulty of observing in the limited furnace zones, because of its extremely hightemperature and high-speed gas in the furnace. According to literatures, researchers did a lot of investigations on spheroidizing process of silica particle [16–21]. Some investigations of different heat source and spheroidizing process have been performed. Moreover, some empirical formulas have been built in experimental study. However, the process cannot easily realize enlargement of the furnace and optimization of the parameters due to high cost. Previous studies indicate that flame flow field, temperature field characteristics and feed particle size were the major influencing factors of spheroidization rate. Therefore, the computational method was capable of predicting detailed evolution of gas dynamics and particle dynamics would be very useful.
452
Z. Ji et al. / Powder Technology 286 (2015) 451–458
Table 1 Gas flow rate set in the simulation. Gas number
Acetylene gas flow rate/L · min−1
Oxygen gas flow rate/L · min−1
Powder carrying gas flow rate/L · min−1
1# 2# 3#
5 10 20
10 20 40
2.5 5 10
In recent years, FLUENT fluid software has been applied as a useful tool in more and more fields for offering a new method [22–28]. Weihong Yang et al. [29] simulate flame obtained by combustion of liquified propane gas with highly preheated air using a regenerative burner. The results of the numerical calculation showed that the flame spread is very well predicted. Mingheng Li et al. [30] obtained statistical distribution of particle velocity, temperature, impinging angle and position on the substrate as well as particle residence time in a high velocity oxygen–fuel thermal spray coating process by FLUENT. Lu Xin et al. [31] performed the numerical simulation of the argon flow field of inductively coupled plasma spheroidization system by using FLUENT fluid software. They predicted particle collection rate of TiAl alloy powders in spheroidization system. Rory F. D. Monaghan et al. [32] validated a steady-state 3D CFD simulation of the combustor using standard numerical techniques. They used SIMPLE coupling and second-order upwind discretization of the momentum equation. The solution was generally found to give better results. While many studies on the numerical simulation have been undertaken, literatures on the simulation
about melt and spheroidization of silica particles in the furnace have not been reported. In a word, so far no references introduce the numerical simulation of oxygen–acetylene flame spheroidizing process for spherical silica particle in detail by FLUENT. The purpose of this study was to develop two models that can predict silica particle spheroidization inside the gas flame furnace at various operating conditions and particle sizes. In this work, the use of numerical simulation method was discussed also as a predictive tool, and 3D modeling of oxygen–acetylene flame spheroidization system was performed by using FLUENT fluid software. First, temperature field and flow field of the furnace were simulated under different gas condition. Then, the different size silica particle trajectories were simulated in the furnace. Finally, the heat transfer, melt and spheroidization of silica particles were simulated. The flow behavior in oxygen–acetylene flame spheroidization furnace under varying gas conditions was investigated in detail by using the finite volume method on basis of the ANSYS FLUENT software. The effect of spheroidizing of silica powder in oxygen– acetylene flame spheroidization system was predicted. 2. Experimental and numerical modeling 2.1. Experimental setup The silica raw material was natural vein quartz crystal dealt with chemo-mechanical disposal. The purity was 99.9% and the content of the radioactive microelement U was 2.5 × 10−9 g/g. The size distribution of particles was 1–40 μm. The as-mechanical–chemical treated of
Fig. 1. Schematic diagram and mesh model of spheroidization furnace. 1: silica inlet; 2: gas inlet; 3: transverse section mesh; 4: bottom.
Z. Ji et al. / Powder Technology 286 (2015) 451–458 Table 2 The fixed parameters of silica particle. Density Molecular Standard state Pure solvent Melting Viscosity kg/m3 weight enthalpy J/kg · mol melting heat J/kg point K kg/m · s Value 2650.7 60.1
4.51 × 108
1.28 × 105
1983
0.43
453
Where, the 1st, 2nd, 3rd, 4th and 5th terms on right hand side of Eq.(4) were shear force, pressure force, solid pressure force, gravity force and drag force terms respectively. (c) Energy equations: ∂p ∂ α g ρg hg þ ∇ α g ρg hg ug ¼ ∇ λg ∇T þ þ ug ∇p þ τ : ∇ug þ SE ∂t ∂t
ð5Þ
silica powders were added into spheroidization furnace by powder feeder. Silica powder was fed to the flame jet through powder feeder coaxially fixed to the furnace axis. The initial speed of silica powder was varied by adjusting the flow of carry gas-oxygen. The flame temperature could be adjusted by changing the design of flame jet and proportion of oxygen. The powders were heated and accelerated by oxygen– acetylene flame jet. Then the powders were melted and spheroidized under the effect of surface tension. After removal from high temperature region, the spheroidized powders were cooled and condensed rapidly to spherical solid. The silica powder was characterized by a scanning electron microscope (Quanta200, FEI). Silica spheroidizing experiments were performed at an oxygen and acetylene gas flow rate as 2# in Table 1. 2.2. Numerical modeling of spheroidization furnace establishment 3D modeling of oxygen–acetylene flame spheroidization system was established by using GAMBIT (FLUENT pre-processor). The schematic of flame furnace and unstructured tetrahedral mesh was shown in Fig. 1. The mesh was read into FLUENT software, and the relevant parameters are set. 2.2.1. Governing equations A set of governing equations were solved by implementing the commercial FLUENT software package FLUENT 6.13. The governing equations of mass, momentum and energy are as follows (α, ρ and u are the void fraction, density and velocity respectively for gas (subscript “g”) or particle (subscript “s”), such as C2H2, O2, CO2, H2O and SiO2) [23]: (a) Continuity equations: Conservation equation of mass for gas phase is ∂ α g ρg þ ∇ α g ρg ug ¼ 0: ∂t
ð1Þ
Conservation equation of mass for solids phases is ∂ ðα s ρs Þ þ ∇ ðα s ρs us Þ ¼ 0: ∂t
ð2Þ
(b) Momentum equations: Conservation equation of momentum for gas phase is n X ∂ K gs ug −us : α g ρg ug þ ∇ α g ρg ug ug ¼ ∇ τ g −α g ∇P þ α g ρg g þ ∂t i¼1
ð3Þ Where, the 1st, 2nd, 3rd and 4th terms on right hand side of Eq.(3) were shear force, pressure force, gravity force and drag force terms respectively. Conservation equation of momentum for solids phases is ∂ ðα s ρs us Þ þ ∇ ðα s ρs us us Þ ¼ ∇ τs −α s ∇P−∇P i þ α s ρs g−K gs ug −us ∂t n X þ K sz ðus −uz Þ: z¼1;z≠i
ð4Þ
Where, h was the specific enthalpy, λg was the thermal conductivity of the gas and SE was a source term that denotes the rate of heat liberated due to chemical reaction and heat absorption due to radiation. τ : ∇ug was always negative and which was called the viscous dissipation.
2.2.2. Boundary conditions The boundary conditions were imposed for the model which was same for all the simulation cases. The gas flow rate should be coordinated with the input power to stabilize the flame. According to experiment, under the condition of the acetylene gas flow rate of 10 L · min, oxygen gas flow rate of 20 L · min and powder carrying gas flow rate of 5 L · min, a stable flame was acquired. Three different sets of gas flow rate were considered in simulation, as shown in Table 1. For dispersed phase silica particle, the wall of spheroidization furnace were set as reflect wall boundary, meaning that an inviscid wall was formed when particles impacted the boundary, and the velocity and direction of jet could be decided by the momentum of particles. The bottom of the spheroidization furnace was defined as trap boundary, and particles would be captured when it touched the boundary. 2.2.3. Material characteristics The physical parameters of oxygen and acetylene were given in the material database in FLUENT. The silica powder particle was considered as dispersed phase. The physical and chemical properties of the silica powder particle used are given in Tables 2 and 3 and the diameter of silica particle range from 1 μm to 100 μm. 2.2.4. Solver and numerical method The standard κ-ɛ turbulent model and PISO pressure–velocity coupling algorithm were applied to the numerical simulation of the acetylene–oxygen flow field. As the volume fraction of particles was rather small compared with that of the gas, the interaction between the particles and the flow field could be ignored in the calculation of the particle trajectory. To build up the numerical model and calculate the results, some assumptions were made as follow: (a) The flow was steady in spheroidization furnace. (b) Joule heating was generated by the combustion reaction of acetylene and oxygen. (c) The viscous dissipation and the pressure work in the energy equation were negligible. (d) The inject silica particles had the same size and shape, had no loss of mass, and their density did not change.
Table 3 The variable parameters of silica particle. Temperature 273.15–1983.15 K 1983.15–5000 K Specific heat (J/kg · K) 694 Thermal conductivity (W/m · K) 7.6 Surface tension (N/m) 0
Y = 1045 + 9.95 × 10−2T Y = −0.1141 + 6 × 10−5T Y = 0.2449 + 2.5 × 10−5T
454
Z. Ji et al. / Powder Technology 286 (2015) 451–458
Fig. 2. Temperature distribution of the 1#(a), 2#(b) and 3#(c) in Table 1.
(e) The motion of the particles in the flow field was influenced only by flow drag force and gravity, other forces ignored. (f) After passing through the flow field, the all particles would go out through bottom of furnace.
using GAMBIT software. Due to the surface symmetric character of the single-particle, such model was simplified in order to reduce the computational time. Base on literatures, melting point, specific heat capacity, coefficient of thermal conductivity, surface tension and viscosity have been set (Tables 2 and 3). Finally, solidification and melting model have been selected in the FLUENT software.
2.3. Particle melting model
3. Results and discussion
To research heat transferring and spheroidization mechanism of the silica particle, 3D numerical modeling of single-particle melting was established. The model simulates process of silica particle melting and spheroidizing in the surrounding of 2500 K. The mesh was constructed
3.1. Simulation of flow field in spheroidization furnace The information of the flow field velocity and temperature distribution inside the furnace was of great importance for the particle behavior
Fig. 3. Velocity distribution of the 1#(a), 2#(b) and 3#(c) in Table 1.
Z. Ji et al. / Powder Technology 286 (2015) 451–458
455
Table 4 Selection of simulation parameters. Model
Settings
Solver Time Space Injection type Number of particle streams Particle type Diameter distribution X-velocity (m/s) Y-velocity (m/s) Z-velocity (m/s) Diameter (μm) Temperature (K) Total flow rate (kg/s) Turbulent dispersion
Pressure Steady 3D Group 300 Inert Linear 11.6 0 0 1–100 300 0.001 Close
and the spheroidizing quality control. The flow field velocity and temperature distribution in the furnace could be adjusted by changing the gas flow rate. Different gas flow rates were employed in this study (Table 1). Fig. 2 showed the temperature distribution of the flow field with different gas flow rates in Table 1. The combustion reaction of acetylene took place small zone of the furnace front where the reaction heat generated high temperature. The high temperature regions of flame extend axially with burning of acetylene in jet. The temperature gradually decreased by heat conduction and radial convection from center of high temperature toward the furnace wall of low temperature. As seen in Fig. 2(a), the length of the flame was 0.4 m and the highest temperature reached 5250 K. In Fig. 2(b), the highest temperature was 5590 K and the length of the flame was 0.2 m. What is more, the highest temperature was 3800 K and the length of the flame was 0.15 m in Fig. 2(c). From Fig. 2, it can be seen that increasing of the gas flow rate decreased the length of flame. Compared with Fig. 2(a) and (c), (b) flame was perfect for temperature distribution and flame length. It was considered that the temperature distribution and length of flame were reasonable in spheroidizing process. On one hand, if there were higher temperature and longer flame length in furnace, smaller silica powders would evaporate during this spheroidizing process. On the other hand, if there were lower temperature and shorter flame length in furnace, bigger silica powders would not melt during this spheroidizing process. This means that the gas flow rate enhanced the controllability of the temperature field of the spheroidization furnace. Fig. 3 showed the velocity distribution of the flow field with different gas flow rates in Table 1. The highest velocity of 1#, 2# and 3# was 80.5 m/s, 150 m/s and 272 m/s, respectively. The difference of the
Fig. 5. Curves of vertical displacement and average residence time for particles with various sizes.
velocity magnitude among 1#, 2#, and 3# mainly depended upon gas flow rate. It was noted that the flow rate of oxygen gas and acetylene gas decreases rapidly after entering the spheroidization furnace. As seen in Fig. 3(a), velocity of gas declined rapidly to 2.68 m/s after passing a distance of 0.35 m in 1#. Also, decrease of the flow rate was fastest in 3#. It was thus clear that the increase of total gas flow rate caused the rise of the velocity in entire spheroidization system, while the flow direction has no obvious change. In addition, according to the ideal gas law, expanding gas will caused rise of gas velocity at high temperature in the combustion region. Meanwhile, total gas flow rate would control burning of acetylene and particle residence time in high temperature region. It was important that reasonable velocity have been chosen. 3.2. Influence of particle size on particle trajectory In the study, discrete phase model was opened after calculating gas flow field. Due to the increasing particle velocity with an increasing flow velocity, it was pivotal and important to preferably choose a gas flow rate. A jet flow composed of 300 silica powder particles was defined in the flow field with a gas flow rate of 2#, which of temperature distribution was showed in Fig. 2(b). The particle of different sizes might have different dynamic behavior during flight due to different momentum, so various sizes were studied. The particles were injected into the flow field from powder feed inlet, and their initial
Fig. 4. Trajectories of particles with different sizes in spheroidization furnace. (a) 1 μm; (b) 5 μm; (c) 10 μm; (d) 40 μm and (e) 100 μm.
456
Z. Ji et al. / Powder Technology 286 (2015) 451–458
Fig. 6. Curves of time and particle temperature for particles with various sizes.
speed was supposed to be the same as powder carrying gas. The parameter setting was given in Table 4. Fig. 4 presented the trajectory of the particles with the size of 1 μm, 5 μm, 10 μm, 40 μm and 100 μm in the spheroidization furnace. After falling into spheroidization furnace, the velocity of all particles decreased rapidly. The velocity magnitude of 1 μm particles was about 4.2 m/s, decline to 2.6 m/s for 5 μm particles, 1.8 m/s for 10 μm particles and 1.5 m/s for 40 μm particles at outlet of the furnace. But, the velocity of 100 μm particles was 2.0 m/s. Meanwhile, the particle velocity direction changed due to various particle sizes. In the Fig. 4(a), for the 1 μm particles, they moved along the initial direction, and trajectory of particles were affected by eddy current. From the Fig. 4(a), (b) and (c), it was illustrated that the range of the particle trajectory became more and more wide with the particle size increasing because of particle momentum. On one hand, smaller particles possess lower momentum, and their velocity magnitude and direction tend to change under the drag force of gas flow. On the other hand, bigger particles possess higher momentum, so particles tend to take
place longer radial displacement. From the Fig. 4(d) and (e), it was found that the range of the particle trajectory became more and more narrow with the particle size increasing, because the particle gravity was dominant. The gravity direction was vertically downward. What was more obvious, the velocity direction of 100 μm particles became vertical downward and fly almost vertically to the furnace outlet. We can draw a conclusion, small particle trajectory was mainly controlled by gas flow field and big particle trajectory was mainly controlled by gravity. Fig. 5 showed the curves of vertical displacement and average residence time for particles with different sizes. It was obvious that it takes longer time for smaller particles to get through the spheroidization furnace, especially in the region 0.6–1.6 m. Furthermore, it was seen that particle residence time was very short in the region 0–0.6 m, which means that the particle residence time was very short in high temperature region of furnace. The residence time of 100 μm particles was mere 0.4 s and the residence time of small particles was about 1.0 s. Because there was no obvious difference between 1 μm, 5 μm and 10 μm particles, three curves overlap in the Fig. 5. However, the temperature of smaller particles changes faster than that of larger particles (Fig. 6). As shown in Fig. 2(b), the highest temperature reached 5000 K in small region. As shown Fig. 6, 1 μm particle easily reached high temperature 4000 K. Because that the boiling point of silica was 2503 K, the particles that were smaller than 1 μm easily evaporated. So, the small particles would vapor if they stay in high temperature region for a long time. 3.3. Particle spheroidization model In order to study melting and spheroidizing of silica particle during flight inside the furnace, spheroidization process of different size particles was simulated in this section. Fig. 7 showed particle phase contours of volume fraction in horizontal plane (YZ plane) at 5 × 10−4 s. Computational domain was reasonably adjusted depending on particle size. It was seen that silica phase was perfect round in the Fig. 7(a) and (b). The silica phase was irregular in the Fig. 7(d). It was thus concluded that spheroidization process of bigger particles need more time than
Fig. 7. Particle phase contours of volume fraction in horizontal plane (YZ plane) at 5 × 10−4 s. (a):1 μm; (b):5 μm; (c):10 μm and (d):40 μm.
Z. Ji et al. / Powder Technology 286 (2015) 451–458
457
Fig. 8. SEM photos of spherical powders of different particle size distribution: (a) and (b) wide particle size distribution; (c) and (d) narrow particle size distribution.
smaller ones, which agreed with experimental results. Fig. 8 showed SEM photos of spherical silica powders of various particle size distribution after spheroidization. From the Fig. 8(a) and (b), there are various particles with size ranging from 5 to 40 μm. The larger particles are poorly spheroidized, while the smallers are completely spheroidized. In other words, the larger the particle size was, the more difficult spheroidization was. In the experiment, 10 μm particles spheroidized for almost 100% at the proper condition as shown in Fig. 8(c) and (d). The particles are amorphous silica. Through CFD simulation of silica particle trajectory and particle spheroidization, the results showed that 1 μm and 5 μm silica particles can complete spheroidization. Because the time period in high temperature (the magnitude 10−3 s) was longer than the time period of melting and spheroidizing of silica particle (the magnitude 10−4 s). The particles that were smaller than 40 μm easily become perfect spherical particle. The above-mentioned results have been verified by the experimental results, which proves that the finite volume model of oxygen– acetylene flame spheroidization system established in this paper was reasonable. 4. Conclusion The FLUENT software was used for numerical simulation of silica particle spheroidization in oxygen–acetylene flame spheroidization system. The oxygen–acetylene flow field, the particle trajectories of silica powder and particle temperature model were calculated. The flow field properties in the furnace were very important to determine the spheroidization rate. The temperature distribution and velocity distribution of the flow field with different gas flow rates have been obtain by FLUENT software. When acetylene gas flow rate was 10 L · min−1, oxygen gas flow rate was 20 L · min−1 and powder carrying gas flow rate was 5 L · min− 1, the flame length was reasonable and overall temperature was highest. With the increasing of the oxygen gas and acetylene gas flow rate, the gas velocity magnitude increased and the
gas velocity direction has no obvious changed. The different size silica particles fly inside the furnace with different trajectories and the particle trajectories were affected by gas flow drag force, eddy current and gravity. Compared simulative date with experimental date, the results indicated the numerical simulation of the spheroidization furnace gas flow field and injected silica powder particle trajectories in oxygen– acetylene flame spheroidization process was reliable. The study can be used to further optimize spheroidizing processes under real operating conditions and to accurately predict particle trajectories. The simulation results can be applied to metallurgy, ceramics and other industry fields. Acknowledgments The work was carried out under the financial of China (No: NSFC51102218), Natural Science Foundation of Hubei Province (No:2013CFB412),Wuhan Scientific and technological project (No: 201210321099) and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (No: CUG120402, CUG120118). References [1] T. Jesionowski, Preparation of spherical silica in emulsion systems using the co-precipitation technique, Mater. Chem. Phys. 113 (2009) 839–849. [2] H. Jin, L. Xu, S. Hou, Preparation of spherical silica powder by oxygen–acetylene flame spheroidization process, J. Mater. Process. Technol. 210 (2010) 81–84. [3] S. Mishra, R. Mitra, M. Vijayakumar, Structure-property correlation in cellular silica processed through hydrophobized fused silica powder for aerospace application, J. Alloys Compd. 504 (2010) 76–82. [4] C. Larson, J.R. Smith, G.J. Armstrong, Current research on surface finishing and coatings for aerospace bodies and structures — a review, Trans. Inst. Met. Finish. 91 (2013) 120–132. [5] T. Li, J. Zhang, H. Wang, Z. Hu, Y. Yu, High-performance light-emitting diodes encapsulated with silica-filled epoxy materials, ACS Appl. Mater. Interfaces 5 (2013) 8968–8981. [6] S.L. Chen, G.M. Yuan, C.T. Hu, Preparation and size determination of monodisperse silica microspheres for particle size certified reference materials, Powder Technol. 207 (2011) 232–237.
458
Z. Ji et al. / Powder Technology 286 (2015) 451–458
[7] T. Gholami, M. Salavati-Niasari, M. Bazarganipour, E. Noori, Synthesis and characterization of spherical silica nanoparticles by modified Stober process assisted by organic ligand, Superlattices Microstruct. 61 (2013) 33–41. [8] A.G. Howard, N.H. Khdary, Spray synthesis of monodisperse sub-micron spherical silica particles, Mater. Lett. 61 (2007) 1951–1954. [9] J. Zhang, S.-z. Song, G.-s. Gai, Research on spherical quartz powder: electronic grade, super pure and super fine, Electron. ComponentsMat. 23 (2004) 48–51. [10] B.M. Goortani, P. Proulx, S.W. Xue, N.Y. Mendoza-Gonzalez, Controlling nanostructure in thermal plasma processing: moving from highly aggregated porous structure to spherical silica nanoparticles, Powder Technol. 175 (2007) 22–32. [11] H. Peng, Y. Shikai, Y. Fangli, B. Liuyang, L. Jinlin, C. Yunfa, Effect of plasma spheroidization process on the microstructure and crystallographic phases of silica, alumina and nickel particles, Plasma Sci. Technol. 9 (2007) 611. [12] V. Jakimova, H. Sui, U. Pihlak, E. Krieger, Spheroidization of Quartz Powder in a Low Temperature Plasma Jet, Daaam National Tallinn, Tallinn Tu, Tallinn, 2000 263–266. [13] S. Che, T. Sogabe, N. Sakamoto, Crystallization of spherical dielectric oxide particles in a melting-spheroidization process using chemical flame, Key Eng. Mater. 301 (2005) 223–226. [14] S. Kumar, H. Na, V. Selvarajan, C. Lee, Influence of metal powder shape on drag coefficient in a spray jet, Curr. Appl. Phys. 9 (2009) 678–682. [15] S. Yugeswaran, V. Selvarajan, Excitation temperature and electron number density behavior of atmospheric pressure DC argon plasma jet during spheroidization of nickel, Vacuum 83 (2009) 841–847. [16] H. Jin, N. Song, N. Wang, Y. Wang, J. Zhou, J. Chen, S. Hou, Preparation of low radioactivity spherical silicon oxide powders via chemical-flame spheroidizing process, Colloids Surf. A Physicochem. Eng. Asp. 381 (2011) 13–16. [17] M. Boulos, Plasma power can make better powders, Met. Powder Rep. 59 (2004) 16–21. [18] Z. Károly, J. Szépvölgyi, Plasma spheroidization of ceramic particles, Chem. Eng. Process. Process Intensif. 44 (2005) 221–224. [19] D. Harbec, F. Gitzhofer, A. Tagnit-Hamou, Induction plasma synthesis of nanometric spheroidized glass powder for use in cementitious materials, Powder Technol. 214 (2011) 356–364. [20] S. Suzuki, K. Sasaki, N. Nakatsuka, J. Hayashi, F. Akamatsu, Y. Hagiwara, K. Iino, A study of fine particle spheroidization process by elevated-pressure pure oxygen
[21] [22]
[23] [24] [25]
[26]
[27]
[28]
[29] [30] [31]
[32]
flame, ASME/JSME 2011 8th Thermal Engineering Joint Conference, American Society of Mechanical Engineers, 2011 (pp. T20036-T20036-20037). C. Lu, J. Fan, P. Zhao, F. Yuan, Preparation of hollow silica spheres by DC thermal plasma, Powder Technol. 266 (2014) 210–217. A. Saario, A. Rebola, P. Coelho, M. Costa, A. Oksanen, Heavy fuel oil combustion in a cylindrical laboratory furnace: measurements and modeling, Fuel 84 (2005) 359–369. F. Taghipour, N. Ellis, C. Wong, Experimental and computational study of gas–solid fluidized bed hydrodynamics, Chem. Eng. Sci. 60 (2005) 6857–6867. D. Castiñeira, T.F. Edgar, Computational fluid dynamics for simulation of wind-tunnel experiments on flare combustion systems, Energy Fuel 22 (2008) 1698–1706. N. Ghasemi, M. Sohrabi, M. Khosravi, A.S. Mujumdar, M. Goodarzi, CFD simulation of solid–liquid flow in a two impinging streams cyclone reactor: prediction of mean residence time and holdup of solid particles, Chem. Eng. Process. Process Intensif. 49 (2010) 1277–1283. R. Nayak, T.P. Dora, A. Satapathy, A computational and experimental investigation on thermal conductivity of particle reinforced epoxy composites, Comput. Mater. Sci. 48 (2010) 576–581. V.S. Buddhiraju, V. Runkana, Simulation of nanoparticle synthesis in an aerosol flame reactor using a coupled flame dynamics–monodisperse population balance model, J. Aerosol Sci. 43 (2012) 1–13. K. Wongwatcharaphon, P. Tongtem, S. Jugjai, A numerical and experimental investigation of performance of a nonsprayed porous burner, Heat Transfer Eng. 35 (2014) 942–952. W. Yang, W. Blasiak, Numerical simulation of properties of a LPG flame with hightemperature air, Int. J. Therm. Sci. 44 (2005) 973–985. M. Li, P.D. Christofides, Computational study of particle in-flight behavior in the HVOF thermal spray process, Chem. Eng. Sci. 61 (2006) 6540–6552. X. Lu, L.-p. Zhu, B. Zhang, R.-j. Zhang, X.-b. He, X.-h. Qu, Simulation of flow field and particle trajectory of radio frequency inductively coupled plasma spheroidization, Comput. Mater. Sci. 65 (2012) 13–18. R.F.D. Monaghan, R. Tahir, G. Bourque, R.L. Gordon, A. Cuoci, T. Faravelli, A. Frassoldati, H.J. Curran, Detailed emissions prediction for a turbulent swirling nonpremixed flame, Energy Fuel 28 (2014) 1470–1488.
Contents lists available at ScienceDirect
Powder Technology journal homepage: www.elsevier.com/locate/powtec
Numerical simulation of silica particle trajectory in flow field and silica particle spheroidizing in oxygen–acetylene flame spheroidization process Zhengjia Ji a, Hongyun Jin a,b,⁎, Yaoqing Wu a, Yunlong Li a, Min Liu a, Chunhui Xu a, Pan Hou a, Jie Dong a, Shuen Hou a,b,⁎ a b
Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China Engineering Research Center of Nano-Geomaterials of Ministry of Education, China University of Geosciences, Wuhan 430074, PR China
a r t i c l e
i n f o
Article history: Received 23 October 2014 Received in revised form 20 July 2015 Accepted 24 July 2015 Available online 7 August 2015 Keywords: CFD simulation Oxygen–acetylene flame spheroidization process Spherical silica Particle trajectory
a b s t r a c t A numerical simulation was developed for particle trajectory in flow field and spheroidizing of silica particle in oxygen–acetylene flame spheroidization process. Gas flow field and silica particle behavior in oxygen–acetylene flame spheroidization process was simulated using a Computational Fluid Dynamics (CFD) package FLUENT. A model was proposed for optimizing spheroidization process of silica particle. Oxygen gas and acetylene gas were used as the continuous phase. Silica particle was used as the dispersed phase. The three-dimensional, steady and isothermal flow field was showed for illustrating the continuous phase and the dispersed phase. Conservation equations of mass and momentum for each phase were solved using the finite volume numerical technique. Various gas conditions were discussed systematically. The injected silica particle trajectories were simulated by using dispersed particle surface trajectory. The trajectories and spheroidizations of different size particles were analyzed. The results of numerical simulation reveal that the flame length was reasonable and overall temperature was highest when acetylene gas flow rate was 10 L · min−1, oxygen gas flow rate was 20 L · min−1 and powder carrying gas flow rate was 5 L · min−1 and 40 μm silica particles were difficult to finish spheroidizing within 5 × 10−4 s. The comparison shows that temperature distribution, velocity distribution, particle trajectories, and deformation which were predicted by simulation, were in good agreement with the corresponding experimental results. © 2015 Elsevier B.V. All rights reserved.
1. Introduction With the rapid development of aerospace and information industry, spherical silica particle has attracted more and more attention [1–5]. Because it has the advantages of good fluidity, low thermal expansion and low stress concentration. The spherical silica particle was indispensable, especially in the large-scale integration (LSI) circuits packaging field. The flame spheroidizing process also was widely found in many industrial applications such as spraying industry, metal industry and ceramic industry. Therefore, it was very worthy and necessary to study spheroidizing process of raw silica material to improve the spheroidization rate and flame furnace design. In order to obtain perfect spherical silica particle, particle character and experimental operating condition were investigated [6–8]. In previous study, the researchers tried many experimental methods, which include the direct current arc plasma method, the ratio frequency ⁎ Corresponding authors at: Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China. E-mail address: [email protected] (H. Jin).
http://dx.doi.org/10.1016/j.powtec.2015.07.040 0032-5910/© 2015 Elsevier B.V. All rights reserved.
plasma process, the high-temperature fused quartz jet route and so on [9–12]. The literatures demonstrated changes in the particle morphology, structure and crystallinity during the spheroidization process [13–15]. For economic cost and high spheroidization efficiency, a new oxygen–acetylene flame spheroidization process has been developed [2]. Although the experimental researches for oxygen–acetylene flame spheroidization process have been conducted excessively, the process fundamentals were not yet fully understood due to difficulty of observing in the limited furnace zones, because of its extremely hightemperature and high-speed gas in the furnace. According to literatures, researchers did a lot of investigations on spheroidizing process of silica particle [16–21]. Some investigations of different heat source and spheroidizing process have been performed. Moreover, some empirical formulas have been built in experimental study. However, the process cannot easily realize enlargement of the furnace and optimization of the parameters due to high cost. Previous studies indicate that flame flow field, temperature field characteristics and feed particle size were the major influencing factors of spheroidization rate. Therefore, the computational method was capable of predicting detailed evolution of gas dynamics and particle dynamics would be very useful.
452
Z. Ji et al. / Powder Technology 286 (2015) 451–458
Table 1 Gas flow rate set in the simulation. Gas number
Acetylene gas flow rate/L · min−1
Oxygen gas flow rate/L · min−1
Powder carrying gas flow rate/L · min−1
1# 2# 3#
5 10 20
10 20 40
2.5 5 10
In recent years, FLUENT fluid software has been applied as a useful tool in more and more fields for offering a new method [22–28]. Weihong Yang et al. [29] simulate flame obtained by combustion of liquified propane gas with highly preheated air using a regenerative burner. The results of the numerical calculation showed that the flame spread is very well predicted. Mingheng Li et al. [30] obtained statistical distribution of particle velocity, temperature, impinging angle and position on the substrate as well as particle residence time in a high velocity oxygen–fuel thermal spray coating process by FLUENT. Lu Xin et al. [31] performed the numerical simulation of the argon flow field of inductively coupled plasma spheroidization system by using FLUENT fluid software. They predicted particle collection rate of TiAl alloy powders in spheroidization system. Rory F. D. Monaghan et al. [32] validated a steady-state 3D CFD simulation of the combustor using standard numerical techniques. They used SIMPLE coupling and second-order upwind discretization of the momentum equation. The solution was generally found to give better results. While many studies on the numerical simulation have been undertaken, literatures on the simulation
about melt and spheroidization of silica particles in the furnace have not been reported. In a word, so far no references introduce the numerical simulation of oxygen–acetylene flame spheroidizing process for spherical silica particle in detail by FLUENT. The purpose of this study was to develop two models that can predict silica particle spheroidization inside the gas flame furnace at various operating conditions and particle sizes. In this work, the use of numerical simulation method was discussed also as a predictive tool, and 3D modeling of oxygen–acetylene flame spheroidization system was performed by using FLUENT fluid software. First, temperature field and flow field of the furnace were simulated under different gas condition. Then, the different size silica particle trajectories were simulated in the furnace. Finally, the heat transfer, melt and spheroidization of silica particles were simulated. The flow behavior in oxygen–acetylene flame spheroidization furnace under varying gas conditions was investigated in detail by using the finite volume method on basis of the ANSYS FLUENT software. The effect of spheroidizing of silica powder in oxygen– acetylene flame spheroidization system was predicted. 2. Experimental and numerical modeling 2.1. Experimental setup The silica raw material was natural vein quartz crystal dealt with chemo-mechanical disposal. The purity was 99.9% and the content of the radioactive microelement U was 2.5 × 10−9 g/g. The size distribution of particles was 1–40 μm. The as-mechanical–chemical treated of
Fig. 1. Schematic diagram and mesh model of spheroidization furnace. 1: silica inlet; 2: gas inlet; 3: transverse section mesh; 4: bottom.
Z. Ji et al. / Powder Technology 286 (2015) 451–458 Table 2 The fixed parameters of silica particle. Density Molecular Standard state Pure solvent Melting Viscosity kg/m3 weight enthalpy J/kg · mol melting heat J/kg point K kg/m · s Value 2650.7 60.1
4.51 × 108
1.28 × 105
1983
0.43
453
Where, the 1st, 2nd, 3rd, 4th and 5th terms on right hand side of Eq.(4) were shear force, pressure force, solid pressure force, gravity force and drag force terms respectively. (c) Energy equations: ∂p ∂ α g ρg hg þ ∇ α g ρg hg ug ¼ ∇ λg ∇T þ þ ug ∇p þ τ : ∇ug þ SE ∂t ∂t
ð5Þ
silica powders were added into spheroidization furnace by powder feeder. Silica powder was fed to the flame jet through powder feeder coaxially fixed to the furnace axis. The initial speed of silica powder was varied by adjusting the flow of carry gas-oxygen. The flame temperature could be adjusted by changing the design of flame jet and proportion of oxygen. The powders were heated and accelerated by oxygen– acetylene flame jet. Then the powders were melted and spheroidized under the effect of surface tension. After removal from high temperature region, the spheroidized powders were cooled and condensed rapidly to spherical solid. The silica powder was characterized by a scanning electron microscope (Quanta200, FEI). Silica spheroidizing experiments were performed at an oxygen and acetylene gas flow rate as 2# in Table 1. 2.2. Numerical modeling of spheroidization furnace establishment 3D modeling of oxygen–acetylene flame spheroidization system was established by using GAMBIT (FLUENT pre-processor). The schematic of flame furnace and unstructured tetrahedral mesh was shown in Fig. 1. The mesh was read into FLUENT software, and the relevant parameters are set. 2.2.1. Governing equations A set of governing equations were solved by implementing the commercial FLUENT software package FLUENT 6.13. The governing equations of mass, momentum and energy are as follows (α, ρ and u are the void fraction, density and velocity respectively for gas (subscript “g”) or particle (subscript “s”), such as C2H2, O2, CO2, H2O and SiO2) [23]: (a) Continuity equations: Conservation equation of mass for gas phase is ∂ α g ρg þ ∇ α g ρg ug ¼ 0: ∂t
ð1Þ
Conservation equation of mass for solids phases is ∂ ðα s ρs Þ þ ∇ ðα s ρs us Þ ¼ 0: ∂t
ð2Þ
(b) Momentum equations: Conservation equation of momentum for gas phase is n X ∂ K gs ug −us : α g ρg ug þ ∇ α g ρg ug ug ¼ ∇ τ g −α g ∇P þ α g ρg g þ ∂t i¼1
ð3Þ Where, the 1st, 2nd, 3rd and 4th terms on right hand side of Eq.(3) were shear force, pressure force, gravity force and drag force terms respectively. Conservation equation of momentum for solids phases is ∂ ðα s ρs us Þ þ ∇ ðα s ρs us us Þ ¼ ∇ τs −α s ∇P−∇P i þ α s ρs g−K gs ug −us ∂t n X þ K sz ðus −uz Þ: z¼1;z≠i
ð4Þ
Where, h was the specific enthalpy, λg was the thermal conductivity of the gas and SE was a source term that denotes the rate of heat liberated due to chemical reaction and heat absorption due to radiation. τ : ∇ug was always negative and which was called the viscous dissipation.
2.2.2. Boundary conditions The boundary conditions were imposed for the model which was same for all the simulation cases. The gas flow rate should be coordinated with the input power to stabilize the flame. According to experiment, under the condition of the acetylene gas flow rate of 10 L · min, oxygen gas flow rate of 20 L · min and powder carrying gas flow rate of 5 L · min, a stable flame was acquired. Three different sets of gas flow rate were considered in simulation, as shown in Table 1. For dispersed phase silica particle, the wall of spheroidization furnace were set as reflect wall boundary, meaning that an inviscid wall was formed when particles impacted the boundary, and the velocity and direction of jet could be decided by the momentum of particles. The bottom of the spheroidization furnace was defined as trap boundary, and particles would be captured when it touched the boundary. 2.2.3. Material characteristics The physical parameters of oxygen and acetylene were given in the material database in FLUENT. The silica powder particle was considered as dispersed phase. The physical and chemical properties of the silica powder particle used are given in Tables 2 and 3 and the diameter of silica particle range from 1 μm to 100 μm. 2.2.4. Solver and numerical method The standard κ-ɛ turbulent model and PISO pressure–velocity coupling algorithm were applied to the numerical simulation of the acetylene–oxygen flow field. As the volume fraction of particles was rather small compared with that of the gas, the interaction between the particles and the flow field could be ignored in the calculation of the particle trajectory. To build up the numerical model and calculate the results, some assumptions were made as follow: (a) The flow was steady in spheroidization furnace. (b) Joule heating was generated by the combustion reaction of acetylene and oxygen. (c) The viscous dissipation and the pressure work in the energy equation were negligible. (d) The inject silica particles had the same size and shape, had no loss of mass, and their density did not change.
Table 3 The variable parameters of silica particle. Temperature 273.15–1983.15 K 1983.15–5000 K Specific heat (J/kg · K) 694 Thermal conductivity (W/m · K) 7.6 Surface tension (N/m) 0
Y = 1045 + 9.95 × 10−2T Y = −0.1141 + 6 × 10−5T Y = 0.2449 + 2.5 × 10−5T
454
Z. Ji et al. / Powder Technology 286 (2015) 451–458
Fig. 2. Temperature distribution of the 1#(a), 2#(b) and 3#(c) in Table 1.
(e) The motion of the particles in the flow field was influenced only by flow drag force and gravity, other forces ignored. (f) After passing through the flow field, the all particles would go out through bottom of furnace.
using GAMBIT software. Due to the surface symmetric character of the single-particle, such model was simplified in order to reduce the computational time. Base on literatures, melting point, specific heat capacity, coefficient of thermal conductivity, surface tension and viscosity have been set (Tables 2 and 3). Finally, solidification and melting model have been selected in the FLUENT software.
2.3. Particle melting model
3. Results and discussion
To research heat transferring and spheroidization mechanism of the silica particle, 3D numerical modeling of single-particle melting was established. The model simulates process of silica particle melting and spheroidizing in the surrounding of 2500 K. The mesh was constructed
3.1. Simulation of flow field in spheroidization furnace The information of the flow field velocity and temperature distribution inside the furnace was of great importance for the particle behavior
Fig. 3. Velocity distribution of the 1#(a), 2#(b) and 3#(c) in Table 1.
Z. Ji et al. / Powder Technology 286 (2015) 451–458
455
Table 4 Selection of simulation parameters. Model
Settings
Solver Time Space Injection type Number of particle streams Particle type Diameter distribution X-velocity (m/s) Y-velocity (m/s) Z-velocity (m/s) Diameter (μm) Temperature (K) Total flow rate (kg/s) Turbulent dispersion
Pressure Steady 3D Group 300 Inert Linear 11.6 0 0 1–100 300 0.001 Close
and the spheroidizing quality control. The flow field velocity and temperature distribution in the furnace could be adjusted by changing the gas flow rate. Different gas flow rates were employed in this study (Table 1). Fig. 2 showed the temperature distribution of the flow field with different gas flow rates in Table 1. The combustion reaction of acetylene took place small zone of the furnace front where the reaction heat generated high temperature. The high temperature regions of flame extend axially with burning of acetylene in jet. The temperature gradually decreased by heat conduction and radial convection from center of high temperature toward the furnace wall of low temperature. As seen in Fig. 2(a), the length of the flame was 0.4 m and the highest temperature reached 5250 K. In Fig. 2(b), the highest temperature was 5590 K and the length of the flame was 0.2 m. What is more, the highest temperature was 3800 K and the length of the flame was 0.15 m in Fig. 2(c). From Fig. 2, it can be seen that increasing of the gas flow rate decreased the length of flame. Compared with Fig. 2(a) and (c), (b) flame was perfect for temperature distribution and flame length. It was considered that the temperature distribution and length of flame were reasonable in spheroidizing process. On one hand, if there were higher temperature and longer flame length in furnace, smaller silica powders would evaporate during this spheroidizing process. On the other hand, if there were lower temperature and shorter flame length in furnace, bigger silica powders would not melt during this spheroidizing process. This means that the gas flow rate enhanced the controllability of the temperature field of the spheroidization furnace. Fig. 3 showed the velocity distribution of the flow field with different gas flow rates in Table 1. The highest velocity of 1#, 2# and 3# was 80.5 m/s, 150 m/s and 272 m/s, respectively. The difference of the
Fig. 5. Curves of vertical displacement and average residence time for particles with various sizes.
velocity magnitude among 1#, 2#, and 3# mainly depended upon gas flow rate. It was noted that the flow rate of oxygen gas and acetylene gas decreases rapidly after entering the spheroidization furnace. As seen in Fig. 3(a), velocity of gas declined rapidly to 2.68 m/s after passing a distance of 0.35 m in 1#. Also, decrease of the flow rate was fastest in 3#. It was thus clear that the increase of total gas flow rate caused the rise of the velocity in entire spheroidization system, while the flow direction has no obvious change. In addition, according to the ideal gas law, expanding gas will caused rise of gas velocity at high temperature in the combustion region. Meanwhile, total gas flow rate would control burning of acetylene and particle residence time in high temperature region. It was important that reasonable velocity have been chosen. 3.2. Influence of particle size on particle trajectory In the study, discrete phase model was opened after calculating gas flow field. Due to the increasing particle velocity with an increasing flow velocity, it was pivotal and important to preferably choose a gas flow rate. A jet flow composed of 300 silica powder particles was defined in the flow field with a gas flow rate of 2#, which of temperature distribution was showed in Fig. 2(b). The particle of different sizes might have different dynamic behavior during flight due to different momentum, so various sizes were studied. The particles were injected into the flow field from powder feed inlet, and their initial
Fig. 4. Trajectories of particles with different sizes in spheroidization furnace. (a) 1 μm; (b) 5 μm; (c) 10 μm; (d) 40 μm and (e) 100 μm.
456
Z. Ji et al. / Powder Technology 286 (2015) 451–458
Fig. 6. Curves of time and particle temperature for particles with various sizes.
speed was supposed to be the same as powder carrying gas. The parameter setting was given in Table 4. Fig. 4 presented the trajectory of the particles with the size of 1 μm, 5 μm, 10 μm, 40 μm and 100 μm in the spheroidization furnace. After falling into spheroidization furnace, the velocity of all particles decreased rapidly. The velocity magnitude of 1 μm particles was about 4.2 m/s, decline to 2.6 m/s for 5 μm particles, 1.8 m/s for 10 μm particles and 1.5 m/s for 40 μm particles at outlet of the furnace. But, the velocity of 100 μm particles was 2.0 m/s. Meanwhile, the particle velocity direction changed due to various particle sizes. In the Fig. 4(a), for the 1 μm particles, they moved along the initial direction, and trajectory of particles were affected by eddy current. From the Fig. 4(a), (b) and (c), it was illustrated that the range of the particle trajectory became more and more wide with the particle size increasing because of particle momentum. On one hand, smaller particles possess lower momentum, and their velocity magnitude and direction tend to change under the drag force of gas flow. On the other hand, bigger particles possess higher momentum, so particles tend to take
place longer radial displacement. From the Fig. 4(d) and (e), it was found that the range of the particle trajectory became more and more narrow with the particle size increasing, because the particle gravity was dominant. The gravity direction was vertically downward. What was more obvious, the velocity direction of 100 μm particles became vertical downward and fly almost vertically to the furnace outlet. We can draw a conclusion, small particle trajectory was mainly controlled by gas flow field and big particle trajectory was mainly controlled by gravity. Fig. 5 showed the curves of vertical displacement and average residence time for particles with different sizes. It was obvious that it takes longer time for smaller particles to get through the spheroidization furnace, especially in the region 0.6–1.6 m. Furthermore, it was seen that particle residence time was very short in the region 0–0.6 m, which means that the particle residence time was very short in high temperature region of furnace. The residence time of 100 μm particles was mere 0.4 s and the residence time of small particles was about 1.0 s. Because there was no obvious difference between 1 μm, 5 μm and 10 μm particles, three curves overlap in the Fig. 5. However, the temperature of smaller particles changes faster than that of larger particles (Fig. 6). As shown in Fig. 2(b), the highest temperature reached 5000 K in small region. As shown Fig. 6, 1 μm particle easily reached high temperature 4000 K. Because that the boiling point of silica was 2503 K, the particles that were smaller than 1 μm easily evaporated. So, the small particles would vapor if they stay in high temperature region for a long time. 3.3. Particle spheroidization model In order to study melting and spheroidizing of silica particle during flight inside the furnace, spheroidization process of different size particles was simulated in this section. Fig. 7 showed particle phase contours of volume fraction in horizontal plane (YZ plane) at 5 × 10−4 s. Computational domain was reasonably adjusted depending on particle size. It was seen that silica phase was perfect round in the Fig. 7(a) and (b). The silica phase was irregular in the Fig. 7(d). It was thus concluded that spheroidization process of bigger particles need more time than
Fig. 7. Particle phase contours of volume fraction in horizontal plane (YZ plane) at 5 × 10−4 s. (a):1 μm; (b):5 μm; (c):10 μm and (d):40 μm.
Z. Ji et al. / Powder Technology 286 (2015) 451–458
457
Fig. 8. SEM photos of spherical powders of different particle size distribution: (a) and (b) wide particle size distribution; (c) and (d) narrow particle size distribution.
smaller ones, which agreed with experimental results. Fig. 8 showed SEM photos of spherical silica powders of various particle size distribution after spheroidization. From the Fig. 8(a) and (b), there are various particles with size ranging from 5 to 40 μm. The larger particles are poorly spheroidized, while the smallers are completely spheroidized. In other words, the larger the particle size was, the more difficult spheroidization was. In the experiment, 10 μm particles spheroidized for almost 100% at the proper condition as shown in Fig. 8(c) and (d). The particles are amorphous silica. Through CFD simulation of silica particle trajectory and particle spheroidization, the results showed that 1 μm and 5 μm silica particles can complete spheroidization. Because the time period in high temperature (the magnitude 10−3 s) was longer than the time period of melting and spheroidizing of silica particle (the magnitude 10−4 s). The particles that were smaller than 40 μm easily become perfect spherical particle. The above-mentioned results have been verified by the experimental results, which proves that the finite volume model of oxygen– acetylene flame spheroidization system established in this paper was reasonable. 4. Conclusion The FLUENT software was used for numerical simulation of silica particle spheroidization in oxygen–acetylene flame spheroidization system. The oxygen–acetylene flow field, the particle trajectories of silica powder and particle temperature model were calculated. The flow field properties in the furnace were very important to determine the spheroidization rate. The temperature distribution and velocity distribution of the flow field with different gas flow rates have been obtain by FLUENT software. When acetylene gas flow rate was 10 L · min−1, oxygen gas flow rate was 20 L · min−1 and powder carrying gas flow rate was 5 L · min− 1, the flame length was reasonable and overall temperature was highest. With the increasing of the oxygen gas and acetylene gas flow rate, the gas velocity magnitude increased and the
gas velocity direction has no obvious changed. The different size silica particles fly inside the furnace with different trajectories and the particle trajectories were affected by gas flow drag force, eddy current and gravity. Compared simulative date with experimental date, the results indicated the numerical simulation of the spheroidization furnace gas flow field and injected silica powder particle trajectories in oxygen– acetylene flame spheroidization process was reliable. The study can be used to further optimize spheroidizing processes under real operating conditions and to accurately predict particle trajectories. The simulation results can be applied to metallurgy, ceramics and other industry fields. Acknowledgments The work was carried out under the financial of China (No: NSFC51102218), Natural Science Foundation of Hubei Province (No:2013CFB412),Wuhan Scientific and technological project (No: 201210321099) and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (No: CUG120402, CUG120118). References [1] T. Jesionowski, Preparation of spherical silica in emulsion systems using the co-precipitation technique, Mater. Chem. Phys. 113 (2009) 839–849. [2] H. Jin, L. Xu, S. Hou, Preparation of spherical silica powder by oxygen–acetylene flame spheroidization process, J. Mater. Process. Technol. 210 (2010) 81–84. [3] S. Mishra, R. Mitra, M. Vijayakumar, Structure-property correlation in cellular silica processed through hydrophobized fused silica powder for aerospace application, J. Alloys Compd. 504 (2010) 76–82. [4] C. Larson, J.R. Smith, G.J. Armstrong, Current research on surface finishing and coatings for aerospace bodies and structures — a review, Trans. Inst. Met. Finish. 91 (2013) 120–132. [5] T. Li, J. Zhang, H. Wang, Z. Hu, Y. Yu, High-performance light-emitting diodes encapsulated with silica-filled epoxy materials, ACS Appl. Mater. Interfaces 5 (2013) 8968–8981. [6] S.L. Chen, G.M. Yuan, C.T. Hu, Preparation and size determination of monodisperse silica microspheres for particle size certified reference materials, Powder Technol. 207 (2011) 232–237.
458
Z. Ji et al. / Powder Technology 286 (2015) 451–458
[7] T. Gholami, M. Salavati-Niasari, M. Bazarganipour, E. Noori, Synthesis and characterization of spherical silica nanoparticles by modified Stober process assisted by organic ligand, Superlattices Microstruct. 61 (2013) 33–41. [8] A.G. Howard, N.H. Khdary, Spray synthesis of monodisperse sub-micron spherical silica particles, Mater. Lett. 61 (2007) 1951–1954. [9] J. Zhang, S.-z. Song, G.-s. Gai, Research on spherical quartz powder: electronic grade, super pure and super fine, Electron. ComponentsMat. 23 (2004) 48–51. [10] B.M. Goortani, P. Proulx, S.W. Xue, N.Y. Mendoza-Gonzalez, Controlling nanostructure in thermal plasma processing: moving from highly aggregated porous structure to spherical silica nanoparticles, Powder Technol. 175 (2007) 22–32. [11] H. Peng, Y. Shikai, Y. Fangli, B. Liuyang, L. Jinlin, C. Yunfa, Effect of plasma spheroidization process on the microstructure and crystallographic phases of silica, alumina and nickel particles, Plasma Sci. Technol. 9 (2007) 611. [12] V. Jakimova, H. Sui, U. Pihlak, E. Krieger, Spheroidization of Quartz Powder in a Low Temperature Plasma Jet, Daaam National Tallinn, Tallinn Tu, Tallinn, 2000 263–266. [13] S. Che, T. Sogabe, N. Sakamoto, Crystallization of spherical dielectric oxide particles in a melting-spheroidization process using chemical flame, Key Eng. Mater. 301 (2005) 223–226. [14] S. Kumar, H. Na, V. Selvarajan, C. Lee, Influence of metal powder shape on drag coefficient in a spray jet, Curr. Appl. Phys. 9 (2009) 678–682. [15] S. Yugeswaran, V. Selvarajan, Excitation temperature and electron number density behavior of atmospheric pressure DC argon plasma jet during spheroidization of nickel, Vacuum 83 (2009) 841–847. [16] H. Jin, N. Song, N. Wang, Y. Wang, J. Zhou, J. Chen, S. Hou, Preparation of low radioactivity spherical silicon oxide powders via chemical-flame spheroidizing process, Colloids Surf. A Physicochem. Eng. Asp. 381 (2011) 13–16. [17] M. Boulos, Plasma power can make better powders, Met. Powder Rep. 59 (2004) 16–21. [18] Z. Károly, J. Szépvölgyi, Plasma spheroidization of ceramic particles, Chem. Eng. Process. Process Intensif. 44 (2005) 221–224. [19] D. Harbec, F. Gitzhofer, A. Tagnit-Hamou, Induction plasma synthesis of nanometric spheroidized glass powder for use in cementitious materials, Powder Technol. 214 (2011) 356–364. [20] S. Suzuki, K. Sasaki, N. Nakatsuka, J. Hayashi, F. Akamatsu, Y. Hagiwara, K. Iino, A study of fine particle spheroidization process by elevated-pressure pure oxygen
[21] [22]
[23] [24] [25]
[26]
[27]
[28]
[29] [30] [31]
[32]
flame, ASME/JSME 2011 8th Thermal Engineering Joint Conference, American Society of Mechanical Engineers, 2011 (pp. T20036-T20036-20037). C. Lu, J. Fan, P. Zhao, F. Yuan, Preparation of hollow silica spheres by DC thermal plasma, Powder Technol. 266 (2014) 210–217. A. Saario, A. Rebola, P. Coelho, M. Costa, A. Oksanen, Heavy fuel oil combustion in a cylindrical laboratory furnace: measurements and modeling, Fuel 84 (2005) 359–369. F. Taghipour, N. Ellis, C. Wong, Experimental and computational study of gas–solid fluidized bed hydrodynamics, Chem. Eng. Sci. 60 (2005) 6857–6867. D. Castiñeira, T.F. Edgar, Computational fluid dynamics for simulation of wind-tunnel experiments on flare combustion systems, Energy Fuel 22 (2008) 1698–1706. N. Ghasemi, M. Sohrabi, M. Khosravi, A.S. Mujumdar, M. Goodarzi, CFD simulation of solid–liquid flow in a two impinging streams cyclone reactor: prediction of mean residence time and holdup of solid particles, Chem. Eng. Process. Process Intensif. 49 (2010) 1277–1283. R. Nayak, T.P. Dora, A. Satapathy, A computational and experimental investigation on thermal conductivity of particle reinforced epoxy composites, Comput. Mater. Sci. 48 (2010) 576–581. V.S. Buddhiraju, V. Runkana, Simulation of nanoparticle synthesis in an aerosol flame reactor using a coupled flame dynamics–monodisperse population balance model, J. Aerosol Sci. 43 (2012) 1–13. K. Wongwatcharaphon, P. Tongtem, S. Jugjai, A numerical and experimental investigation of performance of a nonsprayed porous burner, Heat Transfer Eng. 35 (2014) 942–952. W. Yang, W. Blasiak, Numerical simulation of properties of a LPG flame with hightemperature air, Int. J. Therm. Sci. 44 (2005) 973–985. M. Li, P.D. Christofides, Computational study of particle in-flight behavior in the HVOF thermal spray process, Chem. Eng. Sci. 61 (2006) 6540–6552. X. Lu, L.-p. Zhu, B. Zhang, R.-j. Zhang, X.-b. He, X.-h. Qu, Simulation of flow field and particle trajectory of radio frequency inductively coupled plasma spheroidization, Comput. Mater. Sci. 65 (2012) 13–18. R.F.D. Monaghan, R. Tahir, G. Bourque, R.L. Gordon, A. Cuoci, T. Faravelli, A. Frassoldati, H.J. Curran, Detailed emissions prediction for a turbulent swirling nonpremixed flame, Energy Fuel 28 (2014) 1470–1488.