Flow pattern visualization and nonlinear analysis of gas-liquid mixing process with top-blowing gas stirring

Kai Yang , Shi-Bo Wang , Xiu-Le Zhu , Jian-Xin Xu , Hua Wang

Journal of Central South University ›› 2019, Vol. 26 ›› Issue (8) : 2029 -2040.

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Journal of Central South University ›› 2019, Vol. 26 ›› Issue (8) : 2029 -2040. DOI: 10.1007/s11771-019-4151-2
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Flow pattern visualization and nonlinear analysis of gas-liquid mixing process with top-blowing gas stirring

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Abstract

The evaluation of the mixing effect of gas-liquid two-phase flow during the top-blown gas agitation mixing is one of the difficulties in the testing field, especially in the process of using the model method to study the metallurgical top-blowing process. In order to evaluate the effect of gas-liquid two-phase flow mixing, a gas chromatography simulation based on capacitance tomography was used to visualize the flow pattern and analyze the mixed characteristics. A gas top-blown agitation test rig was set up, the gas phase was air-selected, and the liquid phase was selected from synthetic heat-conducting oil. The top-blown stirring test process was measured and imaged by electrical capacitance tomography (ECT) equipment from ECT Instruments Ltd (UK). The MATLAB program was used to identify the mixing areas of the images to obtain the distribution of gas-liquid two-phase. The flow pattern of the gas-liquid mixing region was obtained. The chaotic detection of the gas-liquid mixing process was performed by the three-state test method; the images were processed by the counting box dimension-corrosion method to obtain the mixing uniformity time of gas-liquid flow. Results show that it is feasible to use the capacitance tomography technique to visualize the gas-liquid two-phase distribution. The uniformity time quantification of the gas-liquid mixing process is also achieved.

Keywords

top-blowing / electrical capacitance tomography / gas-liquid mixing / visualization / three-state test / mixing uniformity time

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Kai Yang, Shi-Bo Wang, Xiu-Le Zhu, Jian-Xin Xu, Hua Wang. Flow pattern visualization and nonlinear analysis of gas-liquid mixing process with top-blowing gas stirring. Journal of Central South University, 2019, 26(8): 2029-2040 DOI:10.1007/s11771-019-4151-2

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References

[1]

BassingD, BraeuerA S. The lag between micro- and macro-mixing in compressed fluid flows [J]. Chemical Engineering Science, 2017, 163: 105-113

[2]

ZaishaM, ChaoY. Perspective to study on macromixing in chemical reactors [J]. CIESC Journal, 2015, 66(8): 2795-2804

[3]

XiaoQ, WangH, WangS, YangP, WuK, XuJ. Chaotic characterization of multiphase macromixing efficiency based on modified 0-1 test [J]. Chemical Engineering (China), 2016, 44(2): 46-51(in Chinese)

[4]

WangS, ChenY, LiD, XueC. Experimental study on three dimensional turbulent flow in a water model of a metallurgical vessel stirred by a eccentric bottom gas injection [J]. Aerodynamic Experiment and Measurement & Control, 1992, 1: 17-24(in Chinese)

[5]

XuJ, WangH, FangH. Multiphase mixing quantification by computational homology and imaging analysis [J]. Applied Mathematical Modelling, 2011, 35(5): 2160-2171

[6]

PengJ, ChenZ, LiuS-x, ChengL-zhen. Numerical simulation and single factor influence analysis of multi-phase flow in copper top-blown furnace [J]. The Chinese Journal of Process Engineering, 2017, 17(5): 926-934

[7]

LouW, ZhuM Y. Numerical simulation of gas and liquid two-phase flow in gas-stirred systems based on Euler-Euler approach [J]. Metallurgical & Materials Transactions B, 2013, 44(5): 1251-1263

[8]

LiY, LouW T, ZhuM Y. Numerical simulation of gas and liquid flow in steelmaking converter with top and bottom combined blowing [J]. Ironmaking & Steelmaking, 2013, 40(7): 505-514

[9]

HeC, YangN, HuangQ, LiuC, WuL, HuY, FuZ, GaoZ. A multi-phase numerical simulation of a four-nozzle oxygen lance top-blown convertor [J]. Procedia Earth & Planetary Science, 2011, 2(1): 64-69

[10]

WuK, XiaoQ, WangS, XuJ, WangH, YangF. A study on the method for RGB color model applied in evaluate the top-blown mixing time [J]. Chemical Industry and Engineering Progress, 2016, 35(9): 2728-2734

[11]

DongZ. System design of flow velocity measurement gas-solid two-phase flow [D]. Shenyang: Northeastern University, 2014(in Chinese)

[12]

AhmadR, MustafaM, HayatT, AlsaediA. Numerical study of MHD nanofluid flow and heat transfer past a bidirectional exponentially stretching sheet [J]. Journal of Magnetism & Magnetic Materials, 2016, 407: 69-74

[13]

PereraK, PradeepC, MylvaganamS, TimeR. Imaging of oil-water flow patterns by Electrical Capacitance Tomography [J]. Flow Measurement & Instrumentation, 2017, 56: 23-34

[14]

ZhangM, SoleimaniM. Imaging floating metals and dielectric objects using electrical capacitance tomography [J]. Measurement, 2015, 74: 143-149

[15]

LiuJ, LiuS, ZhouW, QiX, LeiJ, MuH. Sensing flame structure by process tomography [J]. Philos Trans A: Math Phys Eng Sci, 2016, 374(2070): 20150340

[16]

AguC E, TokheimL A, EikelandM, Moldestad, BmE. Determination of onset of bubbling and slugging in a fluidized bed using a dual-plane electrical capacitance tomography system [J]. Chemical Engineering Journal, 2017, 328: 997-1008

[17]

DuB, WarsitoW, FanL S. ECT studies of gas-solid fluidized beds of different diameters [J]. Industrial & Engineering Chemistry Research, 2005, 44(14): 5020-5030

[18]

SunJ, YangW, TianW. 3D imaging based on fringe effect of an electrical capacitance tomography sensor [J]. Measurement, 2015, 74186-199

[19]

LiX, JaworskiA J, MaoX. Bubble size and bubble rise velocity estimation by means of electrical capacitance tomography within gas-solids fluidized beds [J]. Measurement, 2018, 117: 226-240

[20]

ChandrasekeraT C, LiY, MoodyD, SchnellmannM A, DennisjS, HollaneD J. Measurement of bubble sizes in fluidized beds using electrical capacitance tomography [J]. Chemical Engineering Science, 2015, 126: 679-687

[21]

QiuG, YeJ, WangH, YangW. Investigation of flow hydrodynamics and regime transition in a gas-solids fluidized bed with different riser diameters [J]. Chemical Engineering Science, 2014, 116: 195-207

[22]

JiangY, QiuG, WangH. Modelling and experimental investigation of the full-loop gas-solid flow in a circulating fluidized bed with six cyclone separators [J]. Chemical Engineering Science, 2014, 109(16): 85-97

[23]

YangD, LiuL, FengW. Experimental investigation of an internally circulating fluidized bed with 32-electrode electrical capacitance volume tomography [J]. Measurement, 2018, 127: 227-237

[24]

MohamadE J, RahimR A, RahimanM H F, AmeranH L, MujiS Z M, MarwahM P. Measurement and analysis of water/oil multiphase flow using electrical capacitance tomography sensor [J]. Flow Measurement & Instrumentation, 2016, 47: 62-70

[25]

RimpiläinenV, PoutiainenS, HeikkinenL M, SavolainenT, VauhkonenM, KetolainenJ. Electrical capacitance tomography as a monitoring tool for high-shear mixing and granulation [J]. Chemical Engineering Science, 201140904100

[26]

RimpiläinenV, HeikkinenL M, VauhkonenM. Moisture distribution and hydrodynamics of wet granules during fluidized-bed drying characterized with volumetric electrical capacitance tomography [J]. Chemical Engineering Science, 2012, 75(25): 220-234

[27]

YangW Q, PengL. Image reconstruction algorithms for electrical capacitance tomography [J]. Journal of Tsinghua University, 2004, 14(4): 478-484

[28]

NayakS R, MishraJ, KhandualA, PalaiG. Fractal dimension of RGB color images [J]. Optik-International Journal for Light and Electron Optics, 2018, 162: 196-205

[29]

FoudaJ S A E, KoepfW. Efficient detection of the quasi-periodic route to chaos in discrete maps by the three-state test [J]. Nonlinear Dynamics, 2014, 78(2): 1477-1487

[30]

de PaulaA V, MöllerS V. On the chaotic nature of bistable flows [J]. Experimental Thermal and Fluid Science (Exp Therm Fluid Sci), 2018, 94: 172-191

[31]

CoentA L L, RivoireA, BrianconS, LietoJ. An original image-processing technique for obtaining the mixing time: The box-counting with erosions method [J]. Powder Technology, 2005, 152(1): 62-71

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