CFD simulation of hydrodynamics characteristics in a tank stirred by a hollow self‐inducing impeller

Li, Liangchao; Chen, Ning; Ke-feng, Xiang; Xiang, Baoqiang

doi:10.1002/cjce.23135

Cited by 10 publications

(7 citation statements)

References 41 publications

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“…Structurally, the combination of an anchor for the outer impeller and a Rushton for the inner impeller was used, which was highly efficient in terms of mass transfer . According to previous research, , a smaller diameter and a larger off-bottom clearance of the inner impeller were recommended. Therefore, the diameter and off-bottom clearance of the inner impeller were set at 133 and 210 mm, respectively.…”

Section: Experiments Setupmentioning

confidence: 99%

Study on the Numerical Model of Gas–Liquid Dispersion Driven by a Coaxial Mixer

Yang

et al. 2023

Ind. Eng. Chem. Res.

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As the flow basis for gas–liquid mixing, turbulence plays an important role in the movement of bubbles in a stirred tank. Motivated by the fact that the current models in the framework of computational fluid dynamics-population balance model lack an adequate assessment of the turbulence effects, the coaxial mixer was chosen as the subject of study, and different turbulence models, drag models, and breakup and coalescence models were compared and optimized. The results showed that the RNG k-ε model better characterized the turbulent scale and achieved a higher exactness for the gas-phase concentration in the axial direction. The Luo–Luo model modified based on the eddy capture mechanism could effectively describe the coalescence and breakup processes of bubbles. Additionally, in the presence of strong turbulence, the Ishii & Zuber model and the Brucato model outperformed other models in predicting gas dispersion and flow structure but still failed to capture the peak gas holdup. By analyzing the available data, a new correlation was proposed to elucidate the increase in drag coefficient caused by turbulence, which significantly improved the prediction accuracy of gas holdup.

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Section: Experiments Setupmentioning

confidence: 99%

Study on the Numerical Model of Gas–Liquid Dispersion Driven by a Coaxial Mixer

Yang

et al. 2023

Ind. Eng. Chem. Res.

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“…According to Ampere's law, the magnetic circuit equation can be obtained Formulas (7) and ( 8) are the formulas for magnetic field and magnetic flux, respectively…”

Section: Magnetic Circuit Modelmentioning

confidence: 99%

“…A CFD simulation study was conducted to understand the hydrodynamic characteristics of this type of stirred tank under aerated and unaerated conditions. 7 Lin et al 8 investigated the flow resistance and internal flow characteristics of gate valves at different inlet velocities by combined CFD and experimental research. Erdodi and Hos 9 focused on modeling the dynamic instability (flutter/chatter) of gas-service direct spring operated pressure relief valves (DSOPRVs).…”

Section: Introductionmentioning

confidence: 99%

Numerical calculation and experimental study on response characteristics of pneumatic solenoid valves

Zhang

Lü

et al. 2019

Measurement and Control

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In order to analyze the response characteristics of the solenoid valve in depth, the flow field of the solenoid valve is analyzed by means of the computational fluid dynamics, and the aerodynamic parameters that are difficult to be obtained by the traditional methods are obtained with software FLUENT. We also set up the mathematical model of the solenoid valve, including the aerodynamic model, the circuit model, the magnetic circuit model and the mechanical motion model. The calculation is completed in the Simulink, and the results of the calculation are analyzed. A set of the solenoid valve response characteristic test system is built, and the response characteristic parameters such as response time and maximum action frequency of the solenoid valve are tested. The experimental results are verified by comparing them with the simulation results. The final result shows that the response characteristics are basically irrelevant to the action frequency at a suitable working frequency. The open switching time of the solenoid valve decreases with the increase in the inlet pressure and the driving voltage and increases with the increase in the number of coil turns. The close switching time increases with the increase in the inlet pressure, the driving voltage and the number of coil turns.

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“…Moreover, computational fluid dynamics (CFD) has played a crucial role in furthering research on self-inducing reactors and expanding their applicability in a variety of fields. 3−5 Research on reactor characteristics focuses predominantly on key parameters including critical speed, 6 suction rate, 7 power consumption, 8,9 gas hold-up, and volumetric mass transfer coefficient. 10,11 The investigation of these parameters is conducted by employing a combination of experimental methods, mathematical models, and numerical simulations.…”

Section: Introductionmentioning

confidence: 99%

“…Research on reactor characteristics focuses predominantly on key parameters including critical speed, suction rate, power consumption, , gas hold-up, and volumetric mass transfer coefficient. , The investigation of these parameters is conducted by employing a combination of experimental methods, mathematical models, and numerical simulations. This comprehensive approach serves as the basis for the optimization of reactor design.…”

Section: Introductionmentioning

confidence: 99%

Self-inducing Reactors for Bioengineering

Gan,

Liu,

Chen

et al. 2023

ACS Omega

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Packed tower reactors, mechanically stirred reactors, airlift reactors, and gas-self-inducing reactors are frequently utilized among the various types of reactors. Self-inducing reactors exhibit notable advantages owing to their simple structure, effective gas–liquid intermixing, and low energy requirements, rendering them highly suitable for bioengineering endeavors. The purpose of this analysis is to shed light on the use of self-inducing reactors in bioengineering by examining the following five parameters: critical speed, suction rate, volumetric mass transfer coefficient, power characteristics, and gas hold-up. Through a comprehensive analysis of the advancements achieved in these domains, it is possible to determine the challenges and opportunities that lie ahead in the realm of bioengineering.

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CFD simulation of hydrodynamics characteristics in a tank stirred by a hollow self‐inducing impeller

Cited by 10 publications

References 41 publications

Study on the Numerical Model of Gas–Liquid Dispersion Driven by a Coaxial Mixer

Study on the Numerical Model of Gas–Liquid Dispersion Driven by a Coaxial Mixer

Numerical calculation and experimental study on response characteristics of pneumatic solenoid valves

Self-inducing Reactors for Bioengineering

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