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The fundamental issues related to heat and mass transfer in microchannels have significant scientific research demands in various engineering fields, including new materials, microelectronics, and aerospace. This paper addresses the problem of predicting mass transport characteristics within microtubes by developing numerical methods, conducting experimental measurements for validation, and analyzing prediction errors.
A one-dimensional approximation method is employed to simplify the compressible flow equations, and a fourth-order Runge-Kutta numerical method is used to iteratively solve the governing equations. A theoretical calculation method suitable for predicting mass transport characteristics in microtubes is established. This method can calculate various flow parameters along the length of the microtube and can handle different flow conditions, such as static pressure matching at the outlet or flow choking.
Subsequently, by comparing the numerical calculation results with the theoretical results of the Fanuo line parameter ratio, the correctness of the numerical calculation method has been verified. Also, Schlieren experiments and a self-designed mass flow measurement device are used to qualitatively and quantitatively verify the effectiveness of physical computing models. Under typical driving pressure differences, the qualitative agreement between the calculated and schlieren results for the outlet conditions of the microtube demonstrate the rationality of the numerical method in terms of static pressure matching and flow choking calculations. Regarding mass flow prediction, comparisons between theoretical calculations and experimental measurements under different driving pressures revealed that when the flow inside the microtube is in a fully laminar state, the mass flow prediction error is within 3%. When the flow is fully turbulent, the prediction error is within 8%. However, when the flow involves a transition from laminar to turbulent, the prediction error increases to 29%.
During the numerical calculations, the transition Reynolds number and the turbulent friction factor formula are set as input parameters based on existing research results. However, analysis of the Reynolds numbers along the length of the microtube and the average friction factors under different conditions show that the actual transition Reynolds number in the microtube is lower than the value set in the numerical calculations. Additionally, there is a significant discrepancy between the calculated turbulent friction factor and the actual value. Moreover, during the transition from laminar to turbulent flow, the friction factor should increase continuously with the Reynolds number, but the numerical calculations directly used the turbulent friction factor to represent this process. These factors are the main reasons for the larger mass flow prediction errors when the flow involves transition and turbulence.-
Keywords:
- One-dimensional processing method /
- Mass transfer /
- Numerical prediction /
- Friction coefficient /
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[1] Berg H R, Seldam C A, Gulik P S 1993 J.Fluid.Mech. 246 1
[2] Lorenzini M, Morini G L, Salvigni S 2010 Int.J.Therm. 49 248
[3] Xin Fang, Xiangan Yue, Weiqing An, Xuegang Feng 2019 Microfluid.Nanofluidics.23 5
[4] O Reynolds 1883 Philos.Trans. 174 935
[5] Kawashima D, Yamada T, Hong C, Asako Y 2016 J.Mech.Eng. 230 420
[6] ANSI N14.5 2022. American National Standard for Radioactive Materials Leak-age Teats on Packages for Shipment.
[7] Anderson B L, Carlson R W, Fischer L E 1994 Nuclear Regulatory Commission, Washington, DC (United States). Div. of Industrial and Medical Nuclear Safety; Lawrence Livermore National Lab. (LLNL), Livermore, CA, United States
[8] Chen C S, Kuo W J 2004 Numer.Heat.Transfer. 45 85
[9] Asako Y, Nakayama K, Shinozuka T 2005 Int.J.Heat.Mass. Transfer. 48 4985
[10] Asako Y, Pi T, Turner S E, Faghri M 2003 Int.J.Heat.Mass.Transfer. 46 3041
[11] Murakami S, Toyoda K, Asako Y 2021 J.Fluids.Eng. 134 111301
[12] Hong C, Asako Y, Suzuki K, Faghri M 2012 Numer.Heat.Transfer.61 163
[13] Hong C, Tanaka G, Asako Y, Katanoda H 2018 Int.J.Heat.Mass.Transfer. 121 187
[14] Lijo V, Kim H D, Setoguchi T 2012 Int.J.Heat.Mass.Transfer. 55 701
[15] WANG H, XING J, SUN Z, GU H, SUN X, WANG Y 2023 AEST. 57 74
[16] Agrawal A, Kushwaha H M, R S Jadhav J 2020 Microscale Flow and Heat Transfer (New York: Springer)
[17] Shome B 2023 Phys.Fluids. 35
[18] Yovanovich M M, Khan W A 2020 J.Thermophys.Heat.Trans. 34 792
[19] Valougeorgis D 2007 Phys.Fluids. 19 091702
[20] Barber R W, Emerson D R 2006 HTE. 27 3
[21] Bykov N Y, Zakharov V V 2022 Phys.Fluids. 34 057106
[22] Wang X, Li Y, Gao Y, Gao C, Fu W 2023 Aerospace. 10 126
[23] Xu K, Huang J C 2010 J. Comput. Phys. 229 7747
[24] Guo Z, Xu K, Wang R 2013 Phys. Rev. E. 88 033305.
[25] Hong C, Yamada T, Asako Y, Faghri M 2012 Int.J.Heat.Mass. Transfer. 55 4397
[26] Celata G P, Lorenzini M, Morini G L, Zummo G 2009 Int.J.Heat.Fluid.Flow. 30 814
[27] Rehman D, Barattini D, Hong C, Morini G L 2021 Exp.Fluids. 62 1
[28] Rehman D, Morini G L, Hong C 2019 Micromachines. 10 1
[29] Hong C, Asako Y, Morini G L, Faghri M 2024Exp.Therm.Fluid.Sci. 155 111196
[30] Brackbill T, Kandlikar S 2007 Proceedings of the International Conference on Nanochannels, Microchannels and Minichannels, June 18-20, Puebla, Mexico 4272 509
[31] Eckhardt B, Schneider T M, Hof B, Westerweel J 2007 Annu.Rev.Fluid.Mech. 39 468
[32] Morini G L, Lorenzini M, Salvigni S 2006 Exp.Therm.Fluid.Sci. 30 733
[33] Du D, Li Z, Guo Z 2000 Sci.China.Technol.Sci. 43 171
[34] Sonnad J R, Goudar C T 2006 J.Hydraul.Eng, 132 863
[35] Zucrow M J, Hoffman J D (translated by Wang R Y) 1984 Gas Dynamics (Vol.1) (Beijing: National Defense Industry Press) (in Chinese) [左克罗, 霍夫曼著 (王汝涌译) 气体动力学. 上册. 北京：国防工业出版社]
[36] Tang G H, Li Z, He Y L, Tao W Q 2007 Int.J.Heat.Mass.Transfer. 50 2282
[37] Lorenzini M, Morini G L, Salvigni S 2010 Int.J.Therm.Sci. 49 248
[38] Moody L F 1944 Transactions of the ASME. 66 671
[39] Avci A, Karagoz I 2019 Eur.J.Mech.B.Fluids.78 182.
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