Search

Article

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

Effect of macroscopic velocity on accommodation coefficients based on the molecular dynamics method

Zhang Ye Zhang Ran Lai Jian-Qi Li Hua

Citation:

Effect of macroscopic velocity on accommodation coefficients based on the molecular dynamics method

Zhang Ye, Zhang Ran, Lai Jian-Qi, Li Hua
PDF
HTML
Get Citation
  • The accommodation coefficient is an important parameter in the field of rarefied gas dynamics, representing the adaptation level of the momentum and energy between gas molecules and solid surfaces, which is frequently used in the boundary conditions of numerical simulation of rarefied gas flow. In this paper, a physical model of the interaction between a single gas molecule Ar and the metal Pt surface is constructed, which greatly saves computational resources by omitting the collision between gas molecules in the bulk flow. The Pt surface is constructed by the Phontom model to reflect real physical properties. The surface roughness is modeled by a typical pyramid model, which is physically realistic and stable in structure. The molecular dynamics method is used to simulate the collision process of the gas molecules on the solid surface. The velocity sampling method is used so that the incident gas molecules possess the characteristics of macroscopic velocity. According to the average momentum and energy of the gas molecules before incidence and after reflection, the tangential momentum accommodation coefficients (TMACs), the normal momentum accommodation coefficients (NMACs) and the energy accommodation coefficients (EACs) are obtained. Moreover, the variation regularities of the accommodation coefficients with the macroscopic tangential velocity and the macroscopic normal velocity are analyzed under the smooth and rough surface, respectively. The results indicate that the accommodation coefficients have a strong correlation to macroscopic velocity and roughness. The increase of tangential velocity shortens the interaction time of gas molecules with solid surface, which results in the decrease of TMAC, NMAC and EAC of gas molecules, indicating that the tangential velocity has a negative effect on gas-solid adaptation. In addition, the momentum is found to be transformed from the tangential direction to the normal direction at a large tangential velocity, and this transformation tendency becomes more apparent as the tangential velocity increases. However, the influence of normal velocity on the momentum and energy accommodation coefficient is different. With regard to the smooth surface, the increase of normal velocity contributes to the tangential momentum and energy adaptation of gas molecules with the surface. While for the rough surface, the adaptation level of tangential momentum and energy between gas molecules and the surface is weakened as the normal velocity increases. This paper reveals the mechanism of gas molecules scattering on the surface from a microscopic point of view, which is quite different from the macroscopic phenomena. The conclusions of this paper indicate the irrationality of traditional scattering kernel models to represent the degree of accommodation through constant values, which is of great significance for the improvement of boundary conditions in rarefied gas flows.
      Corresponding author: Zhang Ran, zr07024221@126.com
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 11472004)
    [1]

    Verbridge S S, Craighead H G, Parpia J M 2008 Appl. Phys. Lett. 92 013112Google Scholar

    [2]

    Zhang Z Q, Zhang H W, Ye H F 2009 Appl. Phys. Lett. 95 154101Google Scholar

    [3]

    Song H Q, Yu M X, Zhu W Y, Zhang Y, Jiang S X 2013 Chin. Phys. Lett. 30 014701Google Scholar

    [4]

    Rovenskaya O I 2015 Int. J. Heat Mass Tran. 89 1024Google Scholar

    [5]

    Bao F B, Huang Y L, Zhang Y H, Lin J Z 2015 Microfluid Nanofluid 18 1075Google Scholar

    [6]

    Cao B Y, Sun J, Chen M, Guo Z Y 2009 Int. J. Mol. Sci. 10 4638Google Scholar

    [7]

    Bird G A 1994 Molecular Gas Dynamics and the Direct Simulation of Gas Flows (Oxford: Oxford University Press) pp199−206

    [8]

    Fan J, Shen C 2001 J. Comput. Phys. 167 393

    [9]

    Yuan Y D, Rahman S 2016 Physica A 463 25Google Scholar

    [10]

    Verbeek M G 2018 Microfluid. Nanofluid. 22 34Google Scholar

    [11]

    Maxwell J C 1879 Phil. Trans. R. Soc. Lond. 170 231Google Scholar

    [12]

    Cercignani C, Lampis M 1971 Transp. Theory Stat. Phys. 1 101Google Scholar

    [13]

    Lord R G 1991 Phys. Fluids 3 706Google Scholar

    [14]

    Agrawal A, Prabhu S V 2008 J. Vac. Sci. Technol. A 26 634

    [15]

    Yakunchikov A N, Kovalev V L, Utyuzhnikov S V 2012 Chem. Phys. Lett. 554 225Google Scholar

    [16]

    Zhang W, Meng G, Wei X 2012 Microfluid. Nanofluid. 13 845Google Scholar

    [17]

    Zhang H W, Zhang Z Q, Zheng Y G, Ye H F 2010 Phys. Rev. E 81 066303Google Scholar

    [18]

    Rapaport D C 2004 The Art of Molecular Dynamics Simulation (New York: Cambridge University Press) pp4−5

    [19]

    Bao F B, Huang Y L, Qiu L M, Lin J Z 2015 Mol. Phys. 113 561Google Scholar

    [20]

    Spijker P, Markvoort A J, Nedea S V, Hilbers P A 2010 Phys. Rev. E 81 011203Google Scholar

    [21]

    Bruno D, Cacciatore M, Longo S, Rutigliano M 2000 Chem. Phys. Lett. 320 245Google Scholar

    [22]

    Kovalev V, Yakunchikov A, Li F 2011 Acta Astronaut. 69 744Google Scholar

    [23]

    Dongari N, Zhang Y H, Reese J M 2012 AIP Conf. Proc. 1501 895

    [24]

    Cao B Y, Chen M, Guo Z Y 2005 Appl. Phys. Lett. 86 091905Google Scholar

    [25]

    Finger G W, Kapat J S, Bhattacharya A 2007 J. Fluids Eng. 129 31

    [26]

    Sun J, Li Z X 2008 Mol. Phys. 106 2325Google Scholar

    [27]

    Sun J, Li Z X 2009 Mol. Simul. 35 228Google Scholar

    [28]

    Sun J, Li Z X 2010 Comput. Fluids 39 1345Google Scholar

    [29]

    Prabha S K, Sathian S P 2012 Comput. Fluids 68 47

    [30]

    Pham T T, To Q D, Lauriat G, Leonard C 2012 Phys. Rev. E 86 051201Google Scholar

    [31]

    Liang Z, Keblinski P 2014 Int. J. Heat Mass Tran. 78 161Google Scholar

    [32]

    Reinhold J, Veltzke T, Wells B, Schneider J, Meierhofer F, Colombi Ciacchi L, Chaffee A 2014 Comput. Fluids 97 31Google Scholar

    [33]

    Lim W W, Suaning G J, McKenzie D R 2016 Phys. Fluids 28 097101Google Scholar

    [34]

    Yamaguchi H, Matsuda Y, Niimi T 2017 Phys. Rev. E 96 013116Google Scholar

    [35]

    张冉, 谢文佳, 常青, 李桦 2018 物理学报 67 084701Google Scholar

    Zhang R, Xie W J, Chang Q, Li H 2018 Acta Phys. Sin. 67 084701Google Scholar

    [36]

    Cao B Y, Chen M, Guo Z Y 2006 Int. J. Eng. Sci. 44 927Google Scholar

    [37]

    Xie J F, Cao B Y 2016 Mol. Simul. 43 65

    [38]

    张冉, 常青, 李桦 2018 物理学报 67 223401Google Scholar

    Zhang R, Chang Q, Li H 2018 Acta Phys. Sin. 67 223401Google Scholar

    [39]

    Maruyama S 2000 Advances in Numerical Heat Transfer (Vol.2) (Boca Raton : CRC Press) pp189

    [40]

    张烨, 张冉, 常青, 李桦 2019 物理学报 68 124702Google Scholar

    Zhang Y, Zhang R, Chang Q, Li H 2019 Acta Phys. Sin. 68 124702Google Scholar

    [41]

    Wu L, Bogy D B 2002 J. Tribol.-T. ASME 124 562Google Scholar

  • 图 1  气体分子在固体表面散射的物理模型

    Figure 1.  Physical model for scattering gas molecules on solid surfaces.

    图 2  表面粗糙度的纳米构型

    Figure 2.  Schematic diagram of the roughness geometry.

    图 3  不同宏观切向速度下的切向动量适应系数

    Figure 3.  TMAC values of gas molecular under different macroscopic tangential velocities.

    图 4  不同宏观切向速度下气体分子与表面作用时间

    Figure 4.  Time of gas-solid interaction under different macroscopic tangential velocities.

    图 5  不同宏观切向速度及法向速度下的切向动量适应系数

    Figure 5.  TMAC values of gas molecular under different macroscopic tangential and normal velocities.

    图 6  不同宏观切向速度及法向速度下的法向动量适应系数

    Figure 6.  NMAC values of gas molecular under different macroscopic tangential and normal velocities.

    图 7  不同宏观切向及法向速度下的法向能量适应系数

    Figure 7.  EAC values of gas molecular under different macroscopic tangential and normal velocities.

    图 8  粗糙度为0.5 A的粗糙表面下, 不同宏观切向速度及法向速度下的切向动量适应系数

    Figure 8.  TMAC values of gas molecular on rough surfaces of 0.5 A under different macroscopic tangential and normal velocities

    图 9  粗糙度为0.5 A的粗糙表面下, 不同宏观切向速度及法向速度下的气体分子吸附概率

    Figure 9.  Sticking probability of gas molecular on rough surfaces of 0.5 A under different macroscopic tangential and normal velocities.

    图 10  粗糙度为0.5 A的粗糙表面下, 不同宏观切向速度及法向速度下的法向动量适应系数

    Figure 10.  NMAC values of gas molecular on rough surfaces of 0.5 A under different macroscopic tangential and normal velocities.

    图 11  粗糙度为0.5 A的粗糙表面下, 不同宏观切向速度及法向速度下的能量适应系数

    Figure 11.  EAC values of gas molecular on rough surfaces of 0.5 A under different macroscopic tangential and normal velocities.

    图 12  粗糙度为1.0 A的粗糙表面下, 不同宏观切向速度及法向速度下的切向动量适应系数

    Figure 12.  TMAC values of gas molecular on rough surfaces of 1.0 A under different macroscopic tangential and normal velocities.

    图 13  粗糙度为1.0 A的粗糙表面下, 不同宏观切向速度及法向速度下的气体分子吸附概率

    Figure 13.  Sticking probability of gas molecular on rough surfaces of 1.0 A under different macroscopic tangential and normal velocities.

    图 14  粗糙度为1.0 A的粗糙表面下, 不同宏观切向速度及法向速度下的法向动量适应系数

    Figure 14.  NMAC values of gas molecular on rough surfaces of 1.0 A under different macroscopic tangential and normal velocities.

    图 15  粗糙度为1.0 A的粗糙表面下, 不同宏观切向速度及法向速度下的能量适应系数

    Figure 15.  EAC values of gas molecular on rough surfaces of 1.0 A under different macroscopic tangential and normal velocities.

    表 1  分子动力学模拟中的参数

    Table 1.  Parametersin the MD simulations.

    相互作用$\sigma {\rm{/nm}}$$\varepsilon {\rm{/J}}$mass/kg
    Ar-Ar0.3405$1.670 \times {10^{-{\rm{21}}}}$$6.633 \times {10^{-{\rm{26}}}}$
    Pt-Pt0.2770$52.07 \times {10^{ -{\rm{21}}}}$$32.36 \times {10^{-{\rm{26}}}}$
    Ar-Pt0.3085$0.894 \times {10^{ - {\rm{21}}}}$
    DownLoad: CSV
  • [1]

    Verbridge S S, Craighead H G, Parpia J M 2008 Appl. Phys. Lett. 92 013112Google Scholar

    [2]

    Zhang Z Q, Zhang H W, Ye H F 2009 Appl. Phys. Lett. 95 154101Google Scholar

    [3]

    Song H Q, Yu M X, Zhu W Y, Zhang Y, Jiang S X 2013 Chin. Phys. Lett. 30 014701Google Scholar

    [4]

    Rovenskaya O I 2015 Int. J. Heat Mass Tran. 89 1024Google Scholar

    [5]

    Bao F B, Huang Y L, Zhang Y H, Lin J Z 2015 Microfluid Nanofluid 18 1075Google Scholar

    [6]

    Cao B Y, Sun J, Chen M, Guo Z Y 2009 Int. J. Mol. Sci. 10 4638Google Scholar

    [7]

    Bird G A 1994 Molecular Gas Dynamics and the Direct Simulation of Gas Flows (Oxford: Oxford University Press) pp199−206

    [8]

    Fan J, Shen C 2001 J. Comput. Phys. 167 393

    [9]

    Yuan Y D, Rahman S 2016 Physica A 463 25Google Scholar

    [10]

    Verbeek M G 2018 Microfluid. Nanofluid. 22 34Google Scholar

    [11]

    Maxwell J C 1879 Phil. Trans. R. Soc. Lond. 170 231Google Scholar

    [12]

    Cercignani C, Lampis M 1971 Transp. Theory Stat. Phys. 1 101Google Scholar

    [13]

    Lord R G 1991 Phys. Fluids 3 706Google Scholar

    [14]

    Agrawal A, Prabhu S V 2008 J. Vac. Sci. Technol. A 26 634

    [15]

    Yakunchikov A N, Kovalev V L, Utyuzhnikov S V 2012 Chem. Phys. Lett. 554 225Google Scholar

    [16]

    Zhang W, Meng G, Wei X 2012 Microfluid. Nanofluid. 13 845Google Scholar

    [17]

    Zhang H W, Zhang Z Q, Zheng Y G, Ye H F 2010 Phys. Rev. E 81 066303Google Scholar

    [18]

    Rapaport D C 2004 The Art of Molecular Dynamics Simulation (New York: Cambridge University Press) pp4−5

    [19]

    Bao F B, Huang Y L, Qiu L M, Lin J Z 2015 Mol. Phys. 113 561Google Scholar

    [20]

    Spijker P, Markvoort A J, Nedea S V, Hilbers P A 2010 Phys. Rev. E 81 011203Google Scholar

    [21]

    Bruno D, Cacciatore M, Longo S, Rutigliano M 2000 Chem. Phys. Lett. 320 245Google Scholar

    [22]

    Kovalev V, Yakunchikov A, Li F 2011 Acta Astronaut. 69 744Google Scholar

    [23]

    Dongari N, Zhang Y H, Reese J M 2012 AIP Conf. Proc. 1501 895

    [24]

    Cao B Y, Chen M, Guo Z Y 2005 Appl. Phys. Lett. 86 091905Google Scholar

    [25]

    Finger G W, Kapat J S, Bhattacharya A 2007 J. Fluids Eng. 129 31

    [26]

    Sun J, Li Z X 2008 Mol. Phys. 106 2325Google Scholar

    [27]

    Sun J, Li Z X 2009 Mol. Simul. 35 228Google Scholar

    [28]

    Sun J, Li Z X 2010 Comput. Fluids 39 1345Google Scholar

    [29]

    Prabha S K, Sathian S P 2012 Comput. Fluids 68 47

    [30]

    Pham T T, To Q D, Lauriat G, Leonard C 2012 Phys. Rev. E 86 051201Google Scholar

    [31]

    Liang Z, Keblinski P 2014 Int. J. Heat Mass Tran. 78 161Google Scholar

    [32]

    Reinhold J, Veltzke T, Wells B, Schneider J, Meierhofer F, Colombi Ciacchi L, Chaffee A 2014 Comput. Fluids 97 31Google Scholar

    [33]

    Lim W W, Suaning G J, McKenzie D R 2016 Phys. Fluids 28 097101Google Scholar

    [34]

    Yamaguchi H, Matsuda Y, Niimi T 2017 Phys. Rev. E 96 013116Google Scholar

    [35]

    张冉, 谢文佳, 常青, 李桦 2018 物理学报 67 084701Google Scholar

    Zhang R, Xie W J, Chang Q, Li H 2018 Acta Phys. Sin. 67 084701Google Scholar

    [36]

    Cao B Y, Chen M, Guo Z Y 2006 Int. J. Eng. Sci. 44 927Google Scholar

    [37]

    Xie J F, Cao B Y 2016 Mol. Simul. 43 65

    [38]

    张冉, 常青, 李桦 2018 物理学报 67 223401Google Scholar

    Zhang R, Chang Q, Li H 2018 Acta Phys. Sin. 67 223401Google Scholar

    [39]

    Maruyama S 2000 Advances in Numerical Heat Transfer (Vol.2) (Boca Raton : CRC Press) pp189

    [40]

    张烨, 张冉, 常青, 李桦 2019 物理学报 68 124702Google Scholar

    Zhang Y, Zhang R, Chang Q, Li H 2019 Acta Phys. Sin. 68 124702Google Scholar

    [41]

    Wu L, Bogy D B 2002 J. Tribol.-T. ASME 124 562Google Scholar

  • [1] Han Tong-Wei, Li Xuan-Zheng, Zhao Ze-Ruo, Gu Ye-Tong, Ma Chuan, Zhang Xiao-Yan. Mechanical properties and deformation mechanisms of two-dimensional borophene under different loadings. Acta Physica Sinica, 2024, 73(11): 116201. doi: 10.7498/aps.73.20240066
    [2] Wang Lu-Sheng, Luo Long, Liu Hao, Yang Xin, Ding Jun, Song Kun, Lu Shi-Qing, Huang Xia. Law and mechanism of impact velocity on spalling and fracture behavior of single crystal nickel. Acta Physica Sinica, 2024, 73(16): 164601. doi: 10.7498/aps.73.20240244
    [3] Zhang Yu-Hang, Li Xiao-Bao, Zhan Chun-Xiao, Wang Mei-Qin, Pu Yu-Xue. Molecular dynamics simulation study on mechanical properties of Janus MoSSe monolayer. Acta Physica Sinica, 2023, 72(4): 046201. doi: 10.7498/aps.72.20221815
    [4] Wang Kang, Xu Cheng, Wu Jin-Feng, Yang Kai, Yuan Bing. Single-molecule study of interaction between melittin and one-component lipid membrane. Acta Physica Sinica, 2021, 70(17): 178701. doi: 10.7498/aps.70.20210477
    [5] Yu Hang, Zhang Ran, Yang Fan, Li Hua. Molecular dynamics study on the conversion mechanism between momentum and energy components in gas-surface interaction. Acta Physica Sinica, 2021, 70(2): 024702. doi: 10.7498/aps.70.20201192
    [6] Zhao Zhong-Hua, Qu Guang-Hao, Yao Jia-Chi, Min Dao-Min, Zhai Peng-Fei, Liu Jie, Li Sheng-Tao. Molecular dynamics simulation of phase transition by thermal spikes in monoclinic ZrO2. Acta Physica Sinica, 2021, 70(13): 136101. doi: 10.7498/aps.70.20201861
    [7] Diwu Min-Jie, Hu Xiao-Mian. Molecular dynamics simulation of shock-induced isostructural phase transition in single crystal Ce. Acta Physica Sinica, 2020, 69(11): 116202. doi: 10.7498/aps.69.20200323
    [8] Pan Deng, Liu Chang-Xin, Zhang Ze-Yang, Gao Yu-Jin, Hao Xiu-Hong. Effect of velocity on polytetrafluoroethylene friction coefficient using molecular dynamics simulaiton. Acta Physica Sinica, 2019, 68(17): 176801. doi: 10.7498/aps.68.20190495
    [9] Yin Ling-Kang, Xu Shun, Seongmin Jeong, Yongseok Jho, Wang Jian-Jun, Zhou Xin. Vapor-liquid coexisting morphology of all-atom water model through generalized isothermal isobaric ensemble molecular dynamics simulation. Acta Physica Sinica, 2017, 66(13): 136102. doi: 10.7498/aps.66.136102
    [10] Chang Xu. Ripples of multilayer graphenes:a molecular dynamics study. Acta Physica Sinica, 2014, 63(8): 086102. doi: 10.7498/aps.63.086102
    [11] Yang Cheng-Bing, Xie Hui, Liu Chao. Molecular dynamics simulation of average velocity of lithium iron across the end of carbon nanotube. Acta Physica Sinica, 2014, 63(20): 200508. doi: 10.7498/aps.63.200508
    [12] Zhou Hua-Guang, Lin Xin, Wang Meng, Huang Wei-Dong. Calculation of crystal-melt interfacial free energy of Cu by molecular dynamics simulation. Acta Physica Sinica, 2013, 62(5): 056803. doi: 10.7498/aps.62.056803
    [13] Ke Chuan, Zhao Cheng-Li, Gou Fu-Jun, Zhao Yong. Molecular dynamics study of interaction between the H atoms and Si surface. Acta Physica Sinica, 2013, 62(16): 165203. doi: 10.7498/aps.62.165203
    [14] Zhou Guang-Gang, Lu Gui-Wu, Jiao Yu-Qiu, Li Ying-Feng, Wang Kun, Yu Yang-Xin. A molecular simulation study on adsorption behavior of solid-liquid interface in KDP crystal. Acta Physica Sinica, 2012, 61(1): 010204. doi: 10.7498/aps.61.010204
    [15] Zhao Cheng-Li, Lü Xiao-Dan, Ning Jian-Ping, Qing You-Min, He Ping-Ni, Gou Fu-Jun. Molecular dynamics simulations of energy effectson atorn F interaction with SiC(100). Acta Physica Sinica, 2011, 60(9): 095203. doi: 10.7498/aps.60.095203
    [16] Qin You-Min, Zhao Cheng-Li, He Ping-Ni, Gou Fu-Jun, Ning Jian-Ping, Lü Xiao-Dan, Bogaerts A.. Molecular dynamics simulation of temperature effects on CF+3 etching of Si surface. Acta Physica Sinica, 2010, 59(10): 7225-7231. doi: 10.7498/aps.59.7225
    [17] Shao Jian-Li, Wang Pei, Qin Cheng-Sen, Zhou Hong-Qiang. Shock-induced phase transformations of iron studied with molecular dynamics. Acta Physica Sinica, 2007, 56(9): 5389-5393. doi: 10.7498/aps.56.5389
    [18] Zhang Chao, Wang Yong-Liang, Yan Chao, Zhang Qing-Yu. Numerical simulation of the influence of substitutional impurity on the interaction between low-energy Pt atoms and Pt(111) surface. Acta Physica Sinica, 2006, 55(6): 2882-2891. doi: 10.7498/aps.55.2882
    [19] Chen Jun, Jing Fu-Qian, Zhang Jing-Lin, Chen Dong-Quan. . Acta Physica Sinica, 2002, 51(10): 2386-2392. doi: 10.7498/aps.51.2386
    [20] Zhang Chao, Lv Hai-Feng, Zhang Qing-Yu. . Acta Physica Sinica, 2002, 51(10): 2329-2334. doi: 10.7498/aps.51.2329
Metrics
  • Abstract views:  8951
  • PDF Downloads:  97
  • Cited By: 0
Publishing process
  • Received Date:  28 June 2019
  • Accepted Date:  19 July 2019
  • Available Online:  01 November 2019
  • Published Online:  20 November 2019

/

返回文章
返回