Computational Simulation of Mixing Performance in the Circulating Jet Mixing Tank
-
Yan-Fang Yu
,
Jian-Hua Wu
Abstract
Computational fluid dynamics (CFD) was used to investigate the turbulent mixing performance in a vertical CJT in the range of Re=3,668−18,342. Energy source of hot water was centrally placed just below the top of the tank and temperature instead of concentration measurements were used to quantify mixing performance. The 95 % criterion for temperature equilibrium was employed to evaluate the local mixing degree, and the global mixing performance was evaluated based on the ratio of well-mixed volume to total fluid volume. It was obviously observed from the axial distributions of t95 % that the macro-mixing times decreased slightly for z/H < 0.6 and a deep downward trends appeared with the increase of z/H with given r/R. The macro-mixing time in the jet mixing boundary layer were uniform which were a little longer than those in the bulk zones below z/H=0.5 and decreased sharply by 37.5−87.5 % than that in the bulk zone above z/H=0.5. The values of 95 % mixing time increased with the increase of r/R. The global t95 % decreased with the increasing Reynolds number, and a power correlation between the global t95 % values and Re was proposed. With the increasing logarithm of mixing time, the logarithm of segregation intensity rapidly decreased linearly in the slopes from –0.996 to –0.955. The segmentation intensity first decreased then increased with the increasing values of θ.
Funding source: National Natural Science Foundation of China
Award Identifier / Grant number: “Nos. 21476142, 21306115 and 21106086”
Funding statement: Science Foundation for Doctorate Research of the Liaoning Science and Technology Bureau of China (Grant / Award Number: “No. 20131090”); Program for Liaoning Excellent Talents in University (Grant / Award Number: “No. LR2015051”); Liaoning BaiQianWan Talents Program (Grant / Award Number: “No. 2013921047”); Science and Technology Research Project of Education Department of Liaoning Province (Grant / Award Number: “No. L2013164”); National Natural Science Foundation of China (Grant / Award Number: “Nos. 21476142, 21306115 and 21106086”); Natural Science Foundation of the Liaoning Science and Technology Bureau of China (Grant / Award Number: “No. 2015020148”)
Acknowledgments
The authors acknowledge the financial support from the National Natural Science Foundation of China (Nos. 21476142, 21306115 and 21106086), the Program for Liaoning Excellent Talents in University (No. LR2015051), the Natural Science Foundation of the Liaoning Science and Technology Bureau of China (No. 2015020148), the Science Foundation for Doctorate Research of the Liaoning Science and Technology Bureau of China (No. 20131090), and Liaoning BaiQianWan Talents Program (No. 2013921047). We also thank the referees for their enlightening remarks which helped us both in English and in depth to improve the quality of the paper. Conflict of interest: The authors have declared no conflict of interest.
Nomenclature
- c
[kg m−3] instantaneous concentration
- c̄
[kg m−3] final mean tracer concentration
- dj
[m] diameter of the jet nozzles
- H
[m] tank height
- Is
[−] intensity of segregation
- Mb
[kg] liquid mass of the bulk zone
- Mt
[kg] liquid mass of the tracer
- N0
[−] the number of jet nozzles
- p
[Pa] pressure
- q
[W · m−2] sub-grid scale heat flux
- Q
[m3h−1] volumetric flow rate
- R
[m] tank radius
- Re
[−] jet Reynolds number
- t95 %
[s] mixing time
- T1–31
[−] measurement points of temperature
- V
[m3] volume of a computational cell
- ūi
[m · s−1] mean velocity component
- w
[m] width of rectangle outlets
- xi
[m] coordinate component
Greek symbols
- θ
[°] circumferential angle of polar coordinate
- Θ
[K] instantaneous temperature of the bulk liquid
- Θi
[K] initial temperature of the energy resource
- Θm
[K] final equilibrium value of temperature
- Θ0
[K] initial temperature of the bulk liquid
- μ
[Pa · s] viscosity
- νt
[m2s−1] eddy viscosity
- ρ
[kg m−3] density
- σij
[N · m−3] the stress tensor
- τij
[N · m−2] the sub-grid scale stress
- ϑ
[−] dimensionless temperature
- ϑ̄
[−] average dimensionless temperature
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Articles in the same Issue
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- Experimental Study and Mathematical Modeling of Propane-SCR-NOx Using Group Method of Data Handling and Artificial Neural Network
- Experimental and Kinetic Study of Esterification of Acrylic Acid with Ethanol Using Homogeneous Catalyst
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- Heat Transfer Enhancement Around a Cylinder – A CFD Study of Effect of Corner Radius and Prandtl Number
- CFD Modeling with Experimental Validation of the Internal Hydrodynamics in a Pilot-Scale Slurry Bubble Column Reactor
- Computational Simulation of Mixing Performance in the Circulating Jet Mixing Tank
- In Situ Gasification Chemical Looping Combustion of Coal Using the Mixed Oxygen Carrier of Natural Anhydrite Ore and Calcined Limestone
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Articles in the same Issue
- Frontmatter
- Research Articles
- Adsorption Properties of Arc Produced Multi Walled Carbon Nanotubes for Bovine Serum Albumin
- Experimental Study and Mathematical Modeling of Propane-SCR-NOx Using Group Method of Data Handling and Artificial Neural Network
- Experimental and Kinetic Study of Esterification of Acrylic Acid with Ethanol Using Homogeneous Catalyst
- Synthesis of Butyl Acetate in a Membrane Reactor in a Flow-Through Mode
- Heat Transfer Enhancement Around a Cylinder – A CFD Study of Effect of Corner Radius and Prandtl Number
- CFD Modeling with Experimental Validation of the Internal Hydrodynamics in a Pilot-Scale Slurry Bubble Column Reactor
- Computational Simulation of Mixing Performance in the Circulating Jet Mixing Tank
- In Situ Gasification Chemical Looping Combustion of Coal Using the Mixed Oxygen Carrier of Natural Anhydrite Ore and Calcined Limestone
- Effect of L/D Ratio on Phase Holdup and Bubble Dynamics in Slurry Bubble Column using Optical Fiber Probe Measurements
