Numerical simulation of shear-thinning droplet impact on surfaces with different wettability

Xue-Feng Shen; Yu Cao; Jun-Feng Wang; Hai-Long Liu

doi:10.7498/aps.69.20191682

Journals >Acta Physica Sinica >Volume 69 >Issue 6 >Page 064702-1 > Article

Acta Physica Sinica
Vol. 69, Issue 6, 064702-1 (2020)

Numerical simulation of shear-thinning droplet impact on surfaces with different wettability

Xue-Feng Shen, Yu Cao, Jun-Feng Wang, and Hai-Long Liu^*

Author Affiliations

School of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China

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DOI: 10.7498/aps.69.20191682 Cite this Article

Xue-Feng Shen, Yu Cao, Jun-Feng Wang, Hai-Long Liu. Numerical simulation of shear-thinning droplet impact on surfaces with different wettability[J]. Acta Physica Sinica, 2020, 69(6): 064702-1 Copy Citation Text

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Fig. 1. Computation domain for numerical simulation.

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Fig. 2. Grid generation of computation domain.

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Fig. 3. Comparisons between simulation results in this work and phase-field simulation results^[33].

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Fig. 4. Comparisons between numerical simulation in this work and experiment results^[11], the left half of each image is obtained from the experiment, while the right half is the snapshots from our simulation.

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Fig. 5. Mesh convergence study of droplet impact on solid surfaces

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Fig. 6. Variation of shear viscosity with shear rate at different power-law index.

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Fig. 7. Dimensionless diameter of droplet spread varying with dimensionless time at different power-law index (We = 4.53).

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Fig. 8. Dimensionless height of droplet spread varying with dimensionless time at different power-law index (We = 4.53).

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Fig. 9. Process of droplet impact on surface at different power-law index: (a) m = 0.85, Re_n = 24.37, We = 4.53; (b) m = 0.80, Re_n = 29.50, We = 4.53.

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Fig. 10. Dimensionless diameter of droplet spread varying with dimensionless time at different power-law index (We = 4.53, Re_n = 13.75 (m = 1.00), Re_n = 24.37 (m = 0.85))

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Fig. 11. Dimensionless height of droplet spread varying with dimensionless time at different power-law index (We = 4.53, Re_n = 13.75 (m = 1.00), Re_n = 24.37 (m = 0.85)).

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Fig. 12. Process of droplet impact on surface at different power-law index: (a) m = 1, Re_n = 13.75, We = 4.53; (b) m = 0.80, Re_n = 29.50, We = 4.53.

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Fig. 13. Comparison of

between model prediction values and simulation data.

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参数	符号/单位	数值
重新初始化参数	$\gamma /{\rm{m}} \cdot {{\rm{s}}^{ - 1}}$	1
界面厚度	$\varepsilon /\text{μm}$	$5 \times {10^{ - 2}}$
气体密度	${\rho _1}/{\rm{kg}} \cdot {{\rm{m}}^{ - {\rm{3}}}}$	1.2
气体黏度	${\eta _1}{\rm{/Pa}} \cdot {\rm{s}}$	$2 \times {10^{ - 5}}$
液体密度	${\rho _2}/{\rm{kg}} \cdot {{\rm{m}}^{ - {\rm{3}}}}$	1000
液体黏度	${\eta _2}{\rm{/Pa}} \cdot {\rm{s}}$	$8.9 \times {10^{ - 4}}$
温度	T/℃	25
液滴初始直径	${D_0}/{\text{μ} m }$	55
液滴撞击速度	u_z$/{\rm{m}} \cdot {{\rm{s}}^{ - 1}}$	2.45
接触角	$\theta /{(^ \circ })$	55
气液界面张力	$\sigma /{\rm{mN}} \cdot {{\rm{m}}^{ - 1}}$	72.8

Table 1.

Symbols and constants in numerical simulation

数值模拟参数设置

模型出处	方程	均方根误差
Jones^[37]	$D_{\max }^* = {({\rm{4/3} }Re_{\rm{n} } ^{1/4})^{1/2} }$	0.20
Madejski^[38]	$D_{\max }^* = Re_{\rm{n} } ^{1/5}$	0.31
Pasandideh-Fard等^[39]	$D_{\max }^* = 0.5 Re_{\rm{n} } ^{1/4}$	0.64
Scheller和Bousfield^[40]	$D_{\max }^* = 0.61{(R{e_{\rm{n}}}W{e^{1{\rm{/}}2}}{\rm{)}}^{0.166}}$	0.65
Roisman^[41]	$D_{\max }^* = 0.87 Re_{\rm{n} } ^{1/5} - {\rm{0} }{\rm{.40} }Re_{\rm{n} }^{2/5}W{e^{ - 1/2} }$	0.97
Luu和Forterre^[8]	$D_{\max }^* = Re_{\rm{n} } ^{1/(2 m + 3)}$	0.44
Andrade等^[14]	$D_{\max }^* = 1.28 + 0.071 W{e^{1/4} }Re_{\rm{n} } ^{1/4}$	0.43
本文预测模型	$D_{\max }^* = Re_{\rm{n} } ^{0.17} = {\left[ {\rho D_0^mV_0^{2 - m}/k} \right]^{0.17} }$	0.06

Table 2.

Prediction models of maximum dimensionless factor.

最大无量纲直径预测模型

Xue-Feng Shen, Yu Cao, Jun-Feng Wang, Hai-Long Liu. Numerical simulation of shear-thinning droplet impact on surfaces with different wettability[J]. Acta Physica Sinica, 2020, 69(6): 064702-1

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