Numerical Simulation of Internal Flow Field in Optimization Model of Gas–Liquid Mixing Device
Abstract
:1. Introduction
2. Methodology
2.1. Numerical Methods
2.2. Experimental Setup
2.3. Simulation Model Verification
3. Results and Discussion
3.1. Numerical Simulation of the JP21/G2 Fire Truck
3.1.1. Changes in the Time Dimension of Mixing Effects
3.1.2. Variation Law of Liquid Phase Volume Fraction
3.1.3. Static Pressure Variation Pattern
3.1.4. Speed Streamline
3.2. Orthogonal Experimental Design
3.3. The Impact of Flow Rate on the Mixing Effect
3.3.1. Impact of Flow Rate on Optimal Pipe Diameter
3.3.2. Impact of Flow Rate on the Shortest Mixing Distance
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Foam Agent | Compressed Air | |
---|---|---|
Flow Q (L/min) | 10,000 | 50,000 |
Pressure P (MPa) | 1 | 1.1 |
Hydraulic diameter D (mm) | 250 | 60 |
Density ρ (kg/m3) | 1010 | 13.072 |
Dynamic viscosity μ (kg/(m·s)) | 0.0187 | 1.82 10−5 |
Speed v (m/s) | 3.397 | 98.294 |
Evaluating Indicator | Evaluation Criterion |
---|---|
Liquid phase volume fraction contour | The more vortices there are, the more thorough the mixing of the two phases is; the more uniform the size of the vortex, the better |
Pressure drop before and after mixing chamber | The smaller the pressure drop value, the less energy consumption it indicates |
Uniformity coefficient COV value | The smaller the COV value, the better the fluid uniformity and the value drops to 0.05, reaching the industrial standard |
Liquid phase velocity streamline | The sparser and more uniform the streamline distribution, the higher the mixing stability |
Number | Mixer Cone Angle (°)/A | Air Inlet Angle (°)/B | Main Pipeline Diameter (mm)/C | Uniformity Index COV Coefficient |
---|---|---|---|---|
1 | 50 | 40 | 160 | 0.2745 |
2 | 50 | 50 | 190 | 0.18148 |
3 | 50 | 60 | 220 | 0.291 |
4 | 50 | 70 | 250 | 0.3946 |
5 | 55 | 40 | 190 | 0.3352 |
6 | 55 | 50 | 160 | 0.4409 |
7 | 55 | 60 | 250 | 0.394 |
8 | 55 | 70 | 220 | 0.4601 |
9 | 60 | 40 | 220 | 0.3614 |
10 | 60 | 50 | 250 | 0.4141 |
11 | 60 | 60 | 160 | 0.606 |
12 | 60 | 70 | 190 | 0.6116 |
13 | 65 | 40 | 250 | 0.36524 |
14 | 65 | 50 | 220 | 0.1282 |
15 | 65 | 60 | 190 | 0.4828 |
16 | 65 | 70 | 160 | 0.6325 |
Analyze Parameters | A | B | C |
---|---|---|---|
1.14158 | 1.33634 | 1.9539 | |
1.6302 | 1.16468 | 1.61108 | |
1.9931 | 1.7738 | 1.2407 | |
1.60874 | 2.0988 | 1.56794 | |
1.3032 | 1.7858 | 3.81773 | |
2.65755 | 1.35648 | 2.59558 | |
3.97245 | 3.15908 | 1.53934 | |
2.58804 | 4.405 | 2.45843 | |
0.09141 | 0.13769 | 0.06387 | |
0.03047 | 0.046 | 0.02129 | |
Proportion of (%) | 31.168 | 47.054 | 21.778 |
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Chen, H.; Zhang, J.; Ji, Y.; Zhou, J.; Hu, W. Numerical Simulation of Internal Flow Field in Optimization Model of Gas–Liquid Mixing Device. Processes 2024, 12, 1707. https://doi.org/10.3390/pr12081707
Chen H, Zhang J, Ji Y, Zhou J, Hu W. Numerical Simulation of Internal Flow Field in Optimization Model of Gas–Liquid Mixing Device. Processes. 2024; 12(8):1707. https://doi.org/10.3390/pr12081707
Chicago/Turabian StyleChen, Hongyu, Jie Zhang, Yun Ji, Jiawei Zhou, and Weibo Hu. 2024. "Numerical Simulation of Internal Flow Field in Optimization Model of Gas–Liquid Mixing Device" Processes 12, no. 8: 1707. https://doi.org/10.3390/pr12081707