微通道内超临界氮气三维热流场实验与数值模拟

doi:10.11949/0438-1157.20211034

摘要/Abstract

摘要：

利用实验与数值模拟相结合的方法研究了超临界氮气（SCN₂）三维热流场特性，在用实验数据验证数值方法可靠性基础上，分析了压力（3.6~7 MPa）和质量流速［800~1200 kg/（m²?s）］对SCN₂对流传热特性的影响，揭示了微通道圆管不同圆周方向上SCN₂热流场规律。结果表明：在低压力和高质量流速下，同一轴向位置处，径向内壁温最大值出现在圆管90°处；质量流速越大，内壁温最大值和对流传热系数最小值由圆管180°向90°处发生了转移；当浮升力系数Gr*/Re²>1时，浮升力有利于强化圆管底部区域流体传热能力；基于获得的数据，提出了一个新的适合预测微通道圆管内SCN₂对流传热特性的无量纲换热关联式，预测误差小于20%。研究结果为微通道换热器优化设计提供了参考。

关键词: 微通道, 超临界氮气, 热流场, 关联式

Abstract:

Three-dimensional heat flow field characteristics of supercritical nitrogen (SCN₂) in the micro-channel was studied by combining experimental and numerical simulation methods. Based on the reliability of numerical method verified by experimental data, the effects of pressure (3.6—7 MPa) and mass flux (800—1200 kg/(m²?s)) on the convective heat transfer characteristics of SCN₂were analyzed. The heat flux field of SCN₂ in different circumferential directions of the tube was revealed. The results show that under low pressure and high mass flux, the maximum radial inner wall temperature appears at 90° of the circular tube at the same axial position. With the increase of mass flux, the maximum inner wall temperature and the minimum heat transfer coefficient gradually shifted from 180° to 90° of tube. When buoyancy coefficient Gr*/Re²>1, the buoyancy force was conducive to enhance the fluid heat transfer capacity at the bottom of the circular tube. Based on the obtained data, a new dimensionless correlation is proposed to predict the convective heat transfer characteristics of SCN₂ in micro-channel, and the prediction error is less than 20%. The results provide a reference for the optimal design of micro-channel heat exchanger.

Key words: micro-channel, supercritical nitrogen, heat flow field, correlation

中图分类号:

TE 088

韩昌亮, 辛镜青, 于广滨, 刘俊秀, 许麒澳, 姚安卡, 尹鹏. 微通道内超临界氮气三维热流场实验与数值模拟[J]. 化工学报, 2022, 73(2): 653-662.

Changliang HAN, Jingqing XIN, Guangbin YU, Junxiu LIU, Qi'ao XU, Anka YAO, Peng YIN. Experimental and numerical simulation on three-dimensional heat flow field of supercritical nitrogen in micro-channel[J]. CIESC Journal, 2022, 73(2): 653-662.

图/表 14

图1 实验装置流程图1—离心式鼓风机;2—玻璃转子流量计;3—甲烷燃料罐;4—燃烧器;5—计算机;6—水箱;7—Pt100热电阻;8—压力变送器;9—高压阀门;10—质量流量计;11—高速摄影机;12—增压泵;13—LN2杜瓦罐

Fig.1 Flow chart of experimental device

表1 SCN2对流传热特性实验参数

Table 1 Convective heat transfer characteristic experimental parameters of SCN2

实验编号	入口温度/K	入口压力/MPa	质量流速/ (kg/(m²?s))	出口温度/K	对流传热系数/ (W/(m²?K))
Case 1	93.72	4.52	60.13	285.3	100.65
Case 2	93.31	4.51	71.05	283.4	135.85
Case 3	93.56	4.52	80.15	281.3	155.36
Case 4	93.46	4.53	95.13	279.7	183.31
Case 5	93.76	4.52	100.34	277.3	205.61

图2 7 MPa下SCN2热物性曲线

Fig.2 Thermo-physical property of SCN2 under 7 MPa

图3 物理模型

Fig.3 Physical model

表2 数值模拟工况

Table 2 Numerical simulation conditions

编号

入口压力/MPa

质量流速/

(kg/(m²?s))

图4 网格示意图

Fig.4 Sketch map of mesh

图5 数值结果与实验值对比

Fig.5 Comparison between numerical results and experimental data

图6 压力和质量流速对内壁温的影响

Fig.6 Effect of pressure and mass flux on inner wall temperature

图7 压力和质量流速对比定压热容和对流传热系数的影响

Fig.7 Effect of pressure and mass flux on specific heat and heat transfer coefficient

图8 拟临界点附近SCN2径向速度和y方向速度分布

Fig.8 Distribution of SCN2 radial velocity and y-direction velocity near pseudo-critical point

图9 拟临界点附近SCN2热物性分布

Fig.9 Distribution of SCN2 thermo-physical properties near the pseudo-critical point

图10 浮升力系数沿轴向分布

Fig.10 Distribution of buoyancy coefficient along the axial direction

表3 常用预测SCN2对流传热无量纲换热关联式

Table 3 Common dimensionless correlations for predicting convective heat transfer of SCN2

Model

Equation

Dittus-Boelter^[31]

N u = 0.023 R e 0.8 P r 0.4 μ f μ w 0.11

Tatsumoto et al.^[32]

$N u = 0.023 ? R e 0.8 P r ˉ 0.4 F c$

$F c = 1 + 108.7 d L 2 0.25 1 + 0.002 Δ T T c r ρ w ρ b 0.34 μ b μ w 0.17$

Zhao et al.^[33]

N u = 0.3791 ? R e 0.5887 P r 0.288

表3 常用预测SCN2对流传热无量纲换热关联式

Table 3 Common dimensionless correlations for predicting convective heat transfer of SCN2

Model

Equation

Dittus-Boelter^[31]

N u = 0.023 R e 0.8 P r 0.4 μ f μ w 0.11

Tatsumoto et al.^[32]

$N u = 0.023 ? R e 0.8 P r ˉ 0.4 F c$

$F c = 1 + 108.7 d L 2 0.25 1 + 0.002 Δ T T c r ρ w ρ b 0.34 μ b μ w 0.17$

Zhao et al.^[33]

N u = 0.3791 ? R e 0.5887 P r 0.288

图11 Nusselt数模拟值与预测值对比

Fig.11 Comparison of simulated and predicted Nusselt number

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