Numerical simulation and performance optimization of a new loop gravity heat pipe

doi:10.11949/0438-1157.20221530

Abstract

Abstract:

A new loop gravity heat pipe (LGHP) is researched and a simplified two-phase flow numerical model based on VOF method is proposed to study the flow characteristics of the working fluid in the evaporator, which can effectively simulate the generation of bubbles and the location of the dry area in the evaporator of LGHP. Based on the numerical simulation, the channel structure of the evaporator is improved to delay the appearance of the dry zone of the evaporator when it is placed horizontally. Through experimental verification, it is found that the heat transfer performance of the improved evaporator has been greatly improved, and the liquid phase storage capacity of the refrigerant in the evaporator has been improved, which double its critical heat flux (CHF) to 140 kW/m² (heating power 2000.7 W). It is proved that the simplified model is accurate in simulating the location of the dry area, and can provide a reference for further design and improvement of the flow channel structure of the flat evaporator.

Key words: loop gravity-assisted heat pipe, critical heat flux, dry area, pool boiling

摘要：

研究了一种新型的环路重力热管（LGHP），并提出一种基于VOF方法的简化两相流数值模型，能够有效地模拟热管蒸发器内部气泡的产生和干涸区的位置，从而研究蒸发器内部工质的流动特性。在数值模拟的基础上改进了蒸发器的流道结构，以延缓水平放置时蒸发器干涸区的出现。通过实验验证发现改进后蒸发器的传热性能得到了很大的提高，蒸发器中制冷剂的液相积存量得以提升，使其极限热通量（CHF）提高到140 kW/m²（加热功率2000.7 W），为改进前CHF的两倍。证明该简化模型在模拟干涸区位置方面具有准确性，可以为进一步的设计和改进平板蒸发器流道结构提供参考。

关键词: 环路重力热管, 极限热通量, 干涸区, 池沸腾

CLC Number:

TK 172.4

Jianxun CHEN, Jinping LIU, Xiongwen XU, Yinhao YU. Numerical simulation and performance optimization of a new loop gravity heat pipe[J]. CIESC Journal, 2023, 74(2): 721-734.

陈建勋, 刘金平, 许雄文, 余银豪. 一种新型环路重力热管的数值模拟和性能优化[J]. 化工学报, 2023, 74(2): 721-734.

Figures/Tables 24

Fig.1 Schematic diagram of LGHP

Table 1 The structure of evaporator

Parameter	Value
heating block
block size	120 mm×120 mm×50 mm
heating rod size	100 mm×10 mmϕ
evaporator
whole size	140 mm×120 mm×21 mm
top wall thickness	3 mm
side wall thickness	5.5 mm
bottom wall thickness	3 mm
square column size	3 mm×3 mm×15 mm
square column distance	3 mm
inlet diameter (O/I) length	8.5 mm/6.35 mm 53 mm
outlet diameter (O/I) length upward tube	8.5 mm/6.35 mm 65 mm
diameter (O/I)	10 mm/6.5 mm
length	2100 mm
downward tube
diameter (O/I) length	10 mm/6.5 mm 1800 mm

Table 2 Some thermal physical parameters of R134a

饱和温度T_s/℃	饱和压力p_s/MPa	液体密度ρ_l /(kg/m³)	气体密度ρ_g/(kg/m³)	汽化潜热r/(kJ/kg)
0	0.2928	1294.80	14.43	198.60
10	0.4146	1261.00	20.23	190.74
20	0.5717	1225.30	27.78	182.28
30	0.7702	1187.50	37.54	173.10
40	1.0166	1146.70	50.09	163.02

Fig.2 Structure of evaporator before improvement

Fig.3 Schematic diagram of vertical tube falling film condenser

Fig.4 Distribution of temperature measuring points

Table 3 Uncertainty analysis （confidence level 95%）

Parameter

Uncertainty (u)

T-type thermocouple, T

K-type thermocouple, T

0.5 K

1.0 K

Pressure sensor, p

Power sensor, Q

7500 Pa

8.8 W

Fig.5 Temperature distribution diagram of evaporator

Table 4 Settings of geometric model

Wall material	Working fluid	$X m i n / X m a x$	$Y m i n / Y m a x$	$Z m i n / Z m a x$
copper	R-134a	5.5 mm/134.5 mm	4.5 mm/115.5 mm	0 mm/15 mm

Table 4 Settings of geometric model

Wall material	Working fluid	$X m i n / X m a x$	$Y m i n / Y m a x$	$Z m i n / Z m a x$
copper	R-134a	5.5 mm/134.5 mm	4.5 mm/115.5 mm	0 mm/15 mm

Fig.6 The mesh model of evaporator

Fig.7 Verification of mesh independence

Table 5 CFD model settings

CFD模型参数设置项	设置值
求解器类型	Pressure-based
算法（压力-速度耦合）	PISO
空间离散化
Gradient	Least square cell based
Pressure	PRESTO
Density	Second order upwind
Momentum	Second order upwind
Volume fraction	Geo-reconstruct
Turbulent kinetic energy	First order upwind
Turbulent dissipation rate	First order upwind
Energy	Second order upwind
时间步长离散化	First order implicit
残差
Continuity X-velocity Y-velocity Z-velocity Energy k $ε$	1×10^-3 1×10^-4 1×10^-4 1×10^-4 1×10^-8 1×10^-4 1×10^-4
时间步长	0.0002s
每个时间步长的最大迭代次数	40
湍流模型	k-ε realizable
湍流动能传输的有效Prandtl数	0.8
湍流耗散率传输的有效Prandtl数	0.8
能量的湍流Prandtl数	1

Table 5 CFD model settings

CFD模型参数设置项	设置值
求解器类型	Pressure-based
算法（压力-速度耦合）	PISO
空间离散化
Gradient	Least square cell based
Pressure	PRESTO
Density	Second order upwind
Momentum	Second order upwind
Volume fraction	Geo-reconstruct
Turbulent kinetic energy	First order upwind
Turbulent dissipation rate	First order upwind
Energy	Second order upwind
时间步长离散化	First order implicit
残差
Continuity X-velocity Y-velocity Z-velocity Energy k $ε$	1×10^-3 1×10^-4 1×10^-4 1×10^-4 1×10^-8 1×10^-4 1×10^-4
时间步长	0.0002s
每个时间步长的最大迭代次数	40
湍流模型	k-ε realizable
湍流动能传输的有效Prandtl数	0.8
湍流耗散率传输的有效Prandtl数	0.8
能量的湍流Prandtl数	1

Fig.8 The distribution of temperature in evaporator under different heating powers

Fig.9 Numerical simulation of liquid flow in evaporator

Fig.10 The simulation result compared with the actual temperature measurement

Fig.11 The simulation results of evaporator under different heating powers

Fig.12 The structure of the improved evaporator

Fig.13 The simulation results of improved evaporator under different heating powers

Fig.14 The distribution of temperature in the improved evaporator under different heating powers

Fig.15 The simulation result compared with the actual temperature measurement

Fig.16 Temperature distribution diagram of the improved evaporator

Fig.17 Average temperature of the evaporator before and after improvement

Fig.18 Heat transfer coefficient of evaporator before and after improvement

Fig.19 Heat transfer coefficient of evaporator placed vertically before and after improvement

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