Residence time distribution of high viscosity fluids falling film flow down outside of industrial-scale vertical wavy wall: Experimental investigation and CFD prediction

doi:10.1016/j.cjche.2018.12.022

摘要/Abstract

摘要： The flow behavior of gravity-driven falling film of non-conductive high viscosity polymer fluids on an industrial-scale vertical wavy wall was investigated in terms of film thickness and residence time distribution by numerical simulation and experiment. Falling film flow of high viscosity fluids was found to be steady on a vertical wavy wall in the presence of the large film thickness. The comparison between numerical simulation and experiment for the film thickness both in crest and trough of wavy wall showed good agreement. The simulation results of average residence time of falling film flow with different viscous fluids were also consistent with the experimental results. This work provides the initial insights of how to evaluate and optimize the falling film flow system of polymer fluid.

关键词: Falling film flow, High viscosity polymer fluid, Residence time distribution, Film thickness, Numerical simulation

Abstract: The flow behavior of gravity-driven falling film of non-conductive high viscosity polymer fluids on an industrial-scale vertical wavy wall was investigated in terms of film thickness and residence time distribution by numerical simulation and experiment. Falling film flow of high viscosity fluids was found to be steady on a vertical wavy wall in the presence of the large film thickness. The comparison between numerical simulation and experiment for the film thickness both in crest and trough of wavy wall showed good agreement. The simulation results of average residence time of falling film flow with different viscous fluids were also consistent with the experimental results. This work provides the initial insights of how to evaluate and optimize the falling film flow system of polymer fluid.

Key words: Falling film flow, High viscosity polymer fluid, Residence time distribution, Film thickness, Numerical simulation

Shichang Chen, Lihao Zhang, Yongjun Wang, Xianming Zhang, Wenxing Chen. Residence time distribution of high viscosity fluids falling film flow down outside of industrial-scale vertical wavy wall: Experimental investigation and CFD prediction[J]. 中国化学工程学报, 2019, 27(7): 1586-1594.

参考文献

[1] T. Liu, Y. Zhang, Y. Xu, H. Lin, X. Xu, Y. Luo, et al., The effects of dust-haze on mortality are modified by seasons and individual characteristics in Guangzhou, China, Environ. Pollut. 187(2014) 116-123.
[2] Q. Zhang, J. Quan, X. Tie, X. Li, Q. Liu, Y. Gao, D. Zhao, Effects of meteorology and secondary particle formation on visibility during heavy haze events in Beijing, China, Sci. Total Environ. 502(2015) 578-584.
[3] M. Gao, S.K. Guttikunda, G.R. Carmichael, Y. Wang, Z. Liu, C. Stanier, et al., Health impacts and economic losses assessment of the 2013 severe haze event in Beijing area, Sci. Total Environ. 511(2015) 553-561.
[4] J. Gao, A. Woodward, S. Vardoulakis, et al., Haze, public health and mitigation measures in China:A review of the current evidence for further policy response, Sci. Total Environ. 578(2017) 148-157.
[5] G. Huang, PM_2.5 opened a door to public participation addressing environmental challenges in China, Environ. Pollut. 197(2015) 313-315.
[6] China's Ministry of Environmental Protection, 2017 China Ecological Environment Situation Report http://www.mep.gov.cn/hjzl/, 2018.
[7] China's Ministry of Environmental Protection, National Ambient Air Quality Standards (GB3095-2012) http://www.mep.gov.cn, 2013.
[8] China's State Council, Action plan on prevention and control of air pollution http://www.gov.cn/zwgk/2013-09/12/content_2486773.htm, 2013.
[9] China's Ministry of Environmental Protection, Clean air research plan http://www.mep.gov.cn/xxgk/hjyw/201309/t20130930_261118.shtml, 2013.
[10] National Bureau of Statistics of China, 2015 China Statistical Yearbook, China Statistics Press, Beijing (China), 2016(in Chinese).
[11] M. Li, L. Zhang, Haze in China:Current and future challenges, Environ. Pollut. 189(2014) 85-86.
[12] China's Ministry of Environmental Protection, Nankai University, Chinese Research Academy of Environmental Sciences, et al., Guidance for Particulate Matter Source Apportionment, 2013(in Chinese).
[13] M. Zheng, Y. Zhang, C. Yan, X. Zhu, J.J. Schauer, Y. Zhang, Review of PM_2.5 source apportionment methods in China, Acta Sci. Nat. Univ. Pekin. 50(2014) 1141-1154(in Chinese).
[14] C.Y. Zhang, S.X. Wang, Y. Zhao, et al., Current status and future prospects of anthropogenic particulate matter emissions in China, J. Environ. Sci. 30(2009) 1881-1887(in Chinese).
[15] G.L. Cao, X.Y. Zhang, S.L. Gong, et al., Emission inventories of primary particles and pollutant gases for China, Chin. Sci. Bull. 56(2011) 261-268(in Chinese).
[16] Y. Zhang, J. Cai, S. Wang, K. He, M. Zheng, Review of receptor-based source apportionment research of fine particulate matter and its challenges in China, Sci. Total Environ. 586(2017) 917-929.
[17] Y. Zhang, M. Zheng, J. Cai, C. Yan, Y. Hu, A.G. Russell, et al., Comparison and overview of PM_2.5 source apportionment methods, Chin. Sci. Bull. 60(2015) 109-121(in Chinese).
[18] C.S. Liang, F.K. Duan, K.B. He, Y.L. Ma, Review on recent progress in observations, source identifications and countermeasures of PM_2.5, Environ. Int. 86(2016) 150-170.
[19] S. Balachandran, J.E. Pachon, Y.T. Hu, D. Lee, J.A. Mulholland, A.G. Russell, Ensemble-trained source apportionment of fine particulate matter and method uncertainty analysis, Atmos. Environ. 61(2012) 387-394.
[20] S. Balachandran, H.H. Chang, J.E. Pachon, H.A. Holmes, J.A. Mulholland, A.G. Russell, Bayesian-based ensemble source apportionment of PM_2.5, Environ. Sci. Technol. 47(2013) 13511-13518.
[21] M.C. Bove, P. Brotto, F. Cassola, E. Cuccia, D. Massabo, A. Mazzino, et al., An integrated PM_2.5 source apportionment study:Positive matrix factorisation vs. the chemical transport model CAMx, Atmos. Environ. 94(2014) 274-286.
[22] Y. Hu, S. Balachandran, J.E. Pachon, J. Baek, C. Ivey, H. Holmes, et al., Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach, Atmos. Chem. Phys. 14(2014) 5415-5431.
[23] M.L. Maier, S. Balachandran, S.E. Sarnat, J.R. Turner, J.A. Mulholland, A.G. Russell, Application of an ensemble-trained source apportionment approach at a site impacted by multiple point sources, Environ. Sci. Technol. 47(2013) 3743-3751.
[24] S. Han, J. Wu, Y. Zhang, Z. Cai, et al., Characteristics and formation mechanism of a winter haze-fog episode in Tianjin, China, Atmos. Environ. 98(2014) 323-330.
[25] X. Zhang, M. Mao, Brown haze types due to aerosol pollution at Hefei in the summer and fall, Chemosphere 119(2015) 1153-1162.
[26] J. Li, H. Du, Z. Wang, Y. Sun, W. Yang, et al., Rapid formation of a severe regional winter haze episode over a megacity cluster on the North China Plain, Environ. Pollut. 223(2017) 605-615.
[27] Y. Zhu, L. Huang, J. Li, Q. Ying, H. Zhang, et al., Sources of particulate matter in China:Insights from source apportionment studies published in 1987-2017, Environ. Int. 115(2018) 343-357.
[28] Y. Yang, X. Liu, Y. Qu, J. Wang, J. An, Y. Zhang, F. Zhang, Formation mechanism of continuous extreme haze episodes in the megacity Beijing, China, in January 2013, Atmos. Res. 5(2015) 192-203.
[29] X. Tie, Q. Zhang, H. He, J. Cao, S. Han, Y. Gao, et al., A budget analysis of the formation of haze in Beijing, Atmos. Environ. 100(2015) 25-36.
[30] R. Zhang, X. Sun, A. Shi, Y. Huang, J. Yan, et al., Secondary inorganic aerosols formation during haze episodes at an urban site in Beijing, China, Atmos. Environ. 177(2018) 275-282.
[31] R. Huang, Y. Zhang, C. Bozzetti, K. Ho, J. Cao, Y. Han, et al., High secondary aerosol contribution to particulate pollution during haze events in China, Nature 514(2014) 218-222.
[32] S. Guo, M. Hu, M.L. Zamora, J. Peng, et al., Elucidating severe urban haze formation in China, Proc. Natl. Acad. Sci. U. S. A. 111(2014) 17373-17378.
[33] W. Huang, X. Li, S. Yang, Y. Qian, Dynamic flexibility analysis of chemical reaction systems with time delay:Using a modified finite element collocation method, Chem. Eng. Res. Des. 89(2011) 1938-1946.
[34] W. Huang, Y. Qian, Y. Shao, Y. Qiu, H. Fan, Delay sensitivity analysis for typical reactor systems with flexibility consideration, Ind. Eng. Chem. Res. 53(2014) 14721-14734.
[35] W. Huang, H. Fan, Y. Qiu, F. Cheng, Assessment and computation of the delay tolerability for batch reactors under uncertainty, Chem. Eng. Res. Des. 124(2017) 74-84.
[36] Z. Huang, Y. Lin, X. Wang, C. Ye, L. Li, Optimization and control of a reactive distillation process for the synthesis of dimethyl carbonate, Chin. J. Chem. Eng. 25(2017) 1079-1090.
[37] Y. Sun, Q. Jiang, Y. Xu, Y. Ma, et al., Aerosol characterization over the North China Plain:Haze life cycle and biomass burning impacts in summer, J. Geophys. Res. Atmos. 121(2016) 2508-2521.
[38] W. Huang, H. Fan, Y. Qiu, Z. Cheng, Y. Qian, Application of fault tree approach for the causation mechanism of urban haze in Beijing-Considering the risk events related with exhausts of coal combustion, Sci. Total Environ. 544(2016) 1128-1135.
[39] W. Huang, P. Xu, Y. Qian, Causation mechanism analysis of urban haze based on FTA method:Taking Tianjin as a case study, CIESC J. 69(2018) 982-991.
[40] W. Huang, H. Fan, Y. Qiu, Z. Cheng, P. Xu, Y. Qian, Causation mechanism analysis for haze pollution related to vehicle emission in Guangzhou, China by employing the fault tree approach, Chemosphere 151((2016) 9-16.
[41] T. Bedford, R. Cooke, Probabilistic Risk Analysis:Foundations and Methods, Cambridge University Press, Cambridge, 2001.
[42] R.F. Abdul, A. Varuttamaseni, M. Kintner-Meyer, J.C. Lee, Application of fault tree analysis for customer reliability assessment of a distribution power system, Reliab. Eng. Syst. Saf. 111(2013) 76-85.
[43] S. Cheng, Z. Li, H. Mang, K. Neupane, M. Wauthelet, E.M. Huba, Application of fault tree approach for technical assessment of small-sized biogas systems in Nepal, Appl. Energy 113(2014) 1372-1381.
[44] A. Lindhe, T. Norberg, L. Rosén, Approximate dynamic fault tree calculations for modelling water supply risks, Reliab. Eng. Syst. Saf. 106(2012) 61-71.
[45] L. Placca, R. Kouta, Fault tree analysis for PEM fuel cell degradation process modelling, Int. J. Hydrogen Energy 36(2011) 393-405.
[46] A. Volkanovski, M. Cepin, B. Mavko, Application of the fault tree analysis for assessment of power system reliability, Reliab. Eng. Syst. Saf. 94(2009) 1116-1127.
[47] P. Zhang, J. Wu, Impact of mandatory targets on PM_2.5 concentration control in Chinese cities, J. Clean. Prod. 197(2018) 323-331.
[48] H. Fu, J. Chen, Formation, features and controlling strategies of severe haze-fog pollutions in China, Sci. Total Environ. 578(2017) 121-138.
[49] G. Liu, Z. Yang, B. Chen, Y. Zhang, M. Su, S. Ulgiati, Prevention and control policy analysis for energy-related regional pollution management in China, Appl. Energy 166(2016) 292-300.
[50] H. Zhang, S. Wang, J. Hao, X. Wang, S. Wang, et al., Air pollution and control action in Beijing, J. Clean. Prod. 112(2016) 1519-1527.
[51] J. Tao, L. Zhang, Z. Zhang, R. Huang, Y. Wu, R. Zhang, J. Cao, Y. Zhang, Control of PM_2.5 in Guangzhou during the 16th Asian Games period:Implication for hazy weather prevention, Sci. Total Environ. 508(2015) 57-66.
[52] Q.C. Yang, C.W. Zhang, D.W. Zhang, H.R. Zhou, Development of a coke oven gas assisted coal to ethylene glycol process for high techno-economic performance and low emission, Ind. Eng. Chem. Res. 57(2018) 7600-7612.
[53] Q.C. Yang, D.W. Zhang, H.R. Zhou, C.W. Zhang, Process simulation, analysis and optimization of a coal to ethylene glycol process, Energy 155(2018) 521-534.
[54] G. Guan, Clean coal technologies in Japan:A review, Chin. J. Chem. Eng. 25(2017) 689-697.
[55] Z. Zhang, W. Wang, M. Cheng, S. Liu, J. Xu, et al., The contribution of residential coal combustion to PM_2.5 pollution over China's Beijing-Tianjin-Hebei region in winter, Atmos. Environ. 159(2017) 147-161.
[56] D. Wu, X. M, S. Zhang, Integrating synergistic effects of air pollution control technologies:More cost-effective approach in the coal-fired sector in China, J. Clean. Prod. 199(2018) 1035-1042.
[57] D. Sun, J. Fang, J. Sun, Health-related benefits of air quality improvement from coal control in China:Evidence from the Jing-Jin-Ji region, Resour. Conserv. Recycl. 129(2018) 416-423.
[58] Y. Zhang, C. Liu, K. Li, Y. Zhou, Strategy on China's regional coal consumption control:A case study of Shandong province, Energy Policy 112(2018) 316-327.
[59] X. Yang, F. Teng, The air quality co-benefit of coal control strategy in China, Resour. Conserv. Recycl. 129(2018) 373-382.