References

Abdelrahim KA, Ramaswamy HS. High temperature/pressure rheology of carboxymethyl cellulose (CMC). Food Res Int 1995; 28: 285–290.10.1016/0963-9969(94)00045-ASuche in Google Scholar

Acharya A, Mashelkar RA, Ulbrecht J. Mechanics of bubble motion and deformation in non-Newtonian media. Chem Eng Sci 1977; 32: 863–872.10.1016/0009-2509(77)80072-9Suche in Google Scholar

Ahmed Zeki NS. Prediction of bubble size in bubble columns using artificial neural network. Iraqi J Chem Pet Eng 2009; 10: 1–8.10.31699/IJCPE.2009.1.1Suche in Google Scholar

Al-Masry WA, Abdennour A. Gas hold-up estimation in bubble columns using passive acoustic waveforms with neural networks. J Chem Technol Biotechnol 2006; 81: 951–957.10.1002/jctb.1475Suche in Google Scholar

Alvarez E, Correa JM, Riverol C, Navaza JM. Model based in neural networks for the prediction of the mass transfer coefficients in bubble columns. Study in Newtonian and non-Newtonian fluids. Int Commun Heat Mass Transf 2000; 27: 93–98.10.1016/S0735-1933(00)00087-7Suche in Google Scholar

Amiri S, Mehrnia MR, Barzegari D, Yazdani A. Determination of bubble size distribution in a bubble column reactor using artificial neural network. Asia Pac J Chem Eng 2011a; 7: 613–623.10.1002/apj.615Suche in Google Scholar

Amiri S, Mehrnia MR, Barzegari D, Yazdani A. An artificial neural network for prediction of gas holdup in bubble columns with oily solutions. Neural Comput Appl 2011b; 20: 487–494.10.1007/s00521-011-0566-xSuche in Google Scholar

Anastasiou AD, Passos AD, Mouza AA. Bubble columns with fine pore sparger and non-Newtonian liquid phase: prediction of gas holdup. Chem Eng Sci 2013; 98: 331–338.10.1016/j.ces.2013.05.006Suche in Google Scholar

Baawain MS, Gamal El-Din M, Smith DW. Artificial neural networks modelling of ozone bubble columns: mass transfer coefficient, gas hold-up, and bubble size. Ozone Sci Eng 2007; 29: 343–352.10.1080/01919510701549236Suche in Google Scholar

Balamurugan V, Subbarao D, Roy S. Enhancement in gas holdup in bubble columns through use of vibrating internals. Can J Chem Eng 2010; 88: 1010–1020.10.1002/cjce.20362Suche in Google Scholar

Bar N, Das SK. Comparative study of friction factor by prediction of frictional pressure drop per unit length using empirical correlation and ANN for gas-non-Newtonian liquid flow through 180 degree circular bend. Int Rev Chem Eng 2011; 3: 628–643.Suche in Google Scholar

Bar N, Bandyopadhyay TK, Biswas MN, Das SK. Prediction of pressure drop using artificial neural network for non-Newtonian liquid flow through piping components. J Pet Sci Eng 2010a; 71: 187–194.10.1016/j.petrol.2010.02.001Suche in Google Scholar

Bar N, Biswas MN, Das SK. Prediction of pressure drop using artificial neural network for gas non-Newtonian liquid flow through piping components. Ind Eng Chem Res 2010b; 49: 9423–9429.10.1021/ie1007739Suche in Google Scholar

Behkish A, Lemoine R, Sehabiague L, Oukaci R, Morsi BI. Prediction of the gas holdup in industrial-scale bubble columns and slurry bubble column reactors using back-propagation neural networks. Int J Chem React Eng 2005; 3: 1;35.10.2202/1542-6580.1193Suche in Google Scholar

Benchabane A, Bekkour K. Rheological properties of carboxymethyl cellulose (CMC) solutions. Colloid Polym Sci 2008; 286: 1173–1180.10.1007/s00396-008-1882-2Suche in Google Scholar

Benyounes K. Investigation of the influence of molecular weight of polymer on the rheological behavior of carboxymethylcellulose solutions. International Multi disciplinary Scientific GeoConference: SGEM: Surveying Geology & mining Ecology Management 2013; 2: 951–958.10.5593/SGEM2013/BA1.V2/S06.002Suche in Google Scholar

Bhunia K, Kundu G, Mukherjee D. Prediction of gas holdup in a flotation column by artificial neural network. Int J Coal Prep Util 2015; 35: 165–175.10.1080/19392699.2014.916701Suche in Google Scholar

Buchholz H, Buchholz R, Lucke J, Schugerl K. Bubble swarm behaviour and gas absorption in non-Newtonian fluids in sparged columns. Chem Eng Sci 1978; 33: 1061–1070.10.1016/0009-2509(78)85011-8Suche in Google Scholar

Bulsari AB, Saxen H. Application of artificial neural networks for filtering, smoothing and prediction for a biochemical process. Expert Syst 1994; 11: 159–166.10.1111/j.1468-0394.1994.tb00322.xSuche in Google Scholar

Cancela MA, Alvarez E, Maceiras R. Effects of temperature and concentration on carboxymethylcellulose with sucrose rheology. J Food Eng 2005; 71: 419–424.10.1016/j.jfoodeng.2004.10.043Suche in Google Scholar

Chen BH, Yang NS. Characteristics of a cocurrent multistage bubble column. Ind Eng Chem Res 1989; 28: 1405–1410.10.1021/ie00093a020Suche in Google Scholar

Chen Z, Liu H, Zhang H, Ying W, Fang D. Oxygen mass transfer coefficient in bubble column slurry reactor with ultrafine suspended particles and neural network prediction. Can J Chem Eng 2013; 91: 532–541.10.1002/cjce.21663Suche in Google Scholar

Chhabra RP. Bubbles, drops, and particles in non-Newtonian fluids. Boca Raton, FL: CRC Press, 2006: 17.10.1201/9781420015386Suche in Google Scholar

Clift R, Grace JR, Weber ME. Bubbles, drops, and particles. Mineola, NY: Dover Publications, 1978.Suche in Google Scholar

Craig VS. Bubble coalescence and specific-ion effects. Curr Opin Colloid Inter Sci 2004; 9: 178–184.10.1016/j.cocis.2004.06.002Suche in Google Scholar

Deckwer WD, Schumpe A. Improved tools for bubble column reactor design and scale-up. Chem Eng Sci 1993; 48: 889–911.10.1016/0009-2509(93)80328-NSuche in Google Scholar

Deckwer WD, Nguyen-Tien K, Schumpe A, Serpemen Y. Oxygen mass transfer into aerated CMC solutions in a bubble column. Biotechnol Bioeng 1982; 24: 461–481.10.1002/bit.260240215Suche in Google Scholar

Deng Z, Wang T, Zhang N, Wang Z. Gas holdup, bubble behavior and mass transfer in a 5 m high internal-loop airlift reactor with non-Newtonian fluid. Chem Eng J 2010; 160: 729–737.10.1016/j.cej.2010.03.078Suche in Google Scholar

Devine WD, Shah YT, Morsi BI. Liquid phase axial mixing in a bubble column with viscous non-Newtonian liquids. Can J Chem Eng 1985; 63: 195–201.10.1002/cjce.5450630204Suche in Google Scholar

Dewsbury K, Karamanev D, Margaritis A. Hydrodynamic characteristics of free rise of light solid particles and gas bubbles in non-Newtonian liquids. Chem Eng Sci 1999; 54: 4825–4830.10.1016/S0009-2509(99)00200-6Suche in Google Scholar

Edali M, Esmail MN, Vatistas GH. Rheological properties of high concentrations of carboxymethyl cellulose solutions. J Appl Polym Sci 2001; 79: 1787–1801.10.1002/1097-4628(20010307)79:10<1787::AID-APP70>3.0.CO;2-2Suche in Google Scholar

Eickenbusch H, Brunn PO, Schumpe A. Mass transfer into viscous pseudoplastic liquid in large-diameter bubble columns. Chem Eng Process Process Intensif 1995; 34: 479–485.10.1016/0255-2701(95)00626-5Suche in Google Scholar

El-Temtamy SA, Khalil SA, Nour-el-din AA, Gaber A. Oxygen mass transfer in a bubble column bioreactor containing lysed yeast suspensions. Appl Microbial Biotechnol 1984; 19: 376–381.10.1007/BF00454372Suche in Google Scholar

Elgozali A, Linek V, Fialova M, Wein O, Zahradnık J. Influence of viscosity and surface tension on performance of gas-liquid contactors with ejector type gas distributor. Chem Eng Sci 2002; 57: 2987–2994.10.1016/S0009-2509(02)00165-3Suche in Google Scholar

Esmaeili A, Guy C, Chaouki J. The effects of liquid phase rheology on the hydrodynamics of a gas-liquid bubble column reactor. Chem Eng Sci 2015; 129: 193–207.10.1016/j.ces.2015.01.071Suche in Google Scholar

Esmaeili A, Farag S, Guy C, Chaouki J. Effect of elevated pressure on the hydrodynamic aspects of a pilot-scale bubble column reactor operating with non-Newtonian liquids. Chem Eng J 2016; 288: 377–389.10.1016/j.cej.2015.12.017Suche in Google Scholar

Fransolet E, Crine M, Marchot P, Toye D. Analysis of gas holdup in bubble columns with non-Newtonian fluid using electrical resistance tomography and dynamic gas disengagement technique. Chem Eng Sci 2005; 60: 6118–6123.10.1016/j.ces.2005.03.046Suche in Google Scholar

Franz K, Buchholz R, Schuerl K. Comprehensive study of the gas holds up and bubble size distribution in highly viscous liquids II. CMC solutions. Chem Eng Commun 1980; 5: 187–202.10.1080/00986448008935963Suche in Google Scholar

Funfschilling D, Li HZ. Effects of the injection period on the rise velocity and shape of a bubble in a non-Newtonian fluid. Chem Eng Res Des 2006; 84: 875–883.10.1205/cherd.01229Suche in Google Scholar

Gandhi AB, Joshi JB. Unified correlation for overall gas hold-up in bubble column reactors for various gas-liquid systems using hybrid genetic algorithm‐support vector regression technique. Can J Chem Eng 2010; 88: 758–776.10.1002/cjce.20296Suche in Google Scholar

Gandhi AB, Joshi JB, Jayaraman VK, Kulkarni BD. Development of support vector regression (SVR)-based correlation for prediction of overall gas hold-up in bubble column reactors for various gas-liquid systems. Chem Eng Sci 2007; 62: 7078–7089.10.1016/j.ces.2007.07.071Suche in Google Scholar

Garakani AK, Mostoufi N, Sadeghi F, Fatourechi H, Sarrafzadeh M, Mehrnia M. Comparison between different models for rheological characterization of activated sludge. Iran J Environ Health Sci Eng 2011; 8: 255;264.Suche in Google Scholar

Garcia-Ochoa F, Castro EG. Estimation of oxygen mass transfer coefficient in stirred tank reactors using artificial neural networks. Enzym Microb Technol 2001; 28: 560–569.10.1016/S0141-0229(01)00297-6Suche in Google Scholar

Garson GD. Interpreting neural-network connection weights. AI Expert 1991; 6: 47–51.Suche in Google Scholar

Ghannam MT, Esmail MN. Rheological properties of carboxymethyl cellulose. J Appl Polym Sci 1997; 64: 289–301.10.1002/(SICI)1097-4628(19970411)64:2<289::AID-APP9>3.0.CO;2-NSuche in Google Scholar

Ghosh UK, Upadhyay SN. Gas holdup and solid-liquid mass transfer in Newtonian and non-Newtonian fluids in bubble columns. Can J Chem Eng 2007; 85: 825–832.10.1002/cjce.5450850604Suche in Google Scholar

Godbole SP, Honath MF, Shah YT. Holdup structure in highly viscous Newtonian and non-Newtonian liquids in bubble columns. Chem Eng Commun 1982; 16: 119–134.10.1080/00986448208911090Suche in Google Scholar

Godbole SP, Schumpe A, Shah YT, Carr NL. Hydrodynamics and mass transfer in non-Newtonian solutions in a bubble column. AIChE J 1984; 30: 213–220.10.1002/aic.690300207Suche in Google Scholar

Gómez-Dıaz D, Navaza JM. Rheology of aqueous solutions of food additives: effect of concentration, temperature and blending. J Food Eng 2003; 56: 387–392.10.1016/S0260-8774(02)00211-XSuche in Google Scholar

Grace JR. Shapes and velocities of bubbles rising in infinite liquids. Trans Inst Chem Eng 1973; 51: 116–120.Suche in Google Scholar

Gupta R, Wanchoo RK. Motion of a single Newtonian liquid drop through quiescent immiscible visco-elastic liquid: shape and eccentricity. ASME J Fluids Eng 2009; 131: 1;11.10.1115/1.3054284Suche in Google Scholar

Hamed MM, Khalafallah MG, Hassanien EA. Prediction of wastewater treatment plant performance using artificial neural networks. Environ Model Softw 2004; 19: 919–928.10.1016/j.envsoft.2003.10.005Suche in Google Scholar

Haque MW, Nigam KDP, Joshi JB. Hydrodynamics and mixing in highly viscous pseudo-plastic non-Newtonian solutions in bubble columns. Chem Eng Sci 1986; 41: 2321–2331.10.1016/0009-2509(86)85082-5Suche in Google Scholar

Haque MW, Nigam KDP, Joshi JB, Viswanathan K. Studies on gas holdup and bubble parameters in bubble columns with (carboxymethyl) cellulose solutions. Ind Eng Chem Res 1987; 26: 86–91.10.1021/ie00061a016Suche in Google Scholar

Hecht-Nielson R. Neurocomputing. Reading, MA: Addison-Wesley, 1990.Suche in Google Scholar

Heijnen JJ, Riet K, Wolthuis AJ. Influence of very small bubbles on the dynamic K_La measurement in viscous gas–liquid systems. Biotechnol Bioeng 1980; 22: 1945–1956.10.1002/bit.260220912Suche in Google Scholar

Henzler HJ. Begasen hoherviskoser kltissigkeiten. Cbem.rlng – Techn 1980; 52: 643–652.10.1002/cite.330520807Suche in Google Scholar

Ibrehem AS, Hussain MA. Prediction of bubble size in bubble columns using artificial neural network. J Appl Sci 2009; 9: 3196–3198.10.3923/jas.2009.3196.3198Suche in Google Scholar

Jamialahmadi M, Zehtaban MR, Müller-Steinhagen H, Sarrafi A, Smith JM. Study of bubble formation under constant flow conditions. Chem Eng Res Des 2001; 79: 523–532.10.1205/02638760152424299Suche in Google Scholar

Jana SK, Biswas AB, Das SK. Gas holdup in tapered bubble column using pseudoplastic non-Newtonian liquids. Korean J Chem Eng 2014a; 31: 574–581.10.1007/s11814-013-0205-6Suche in Google Scholar

Jana SK, Biswas AB, Das SK. Pressure drop in tapered bubble columns using non-Newtonian pseudoplastic liquid-experimental and ANN prediction. Can J Chem Eng 2014b; 92: 578–584.10.1002/cjce.21838Suche in Google Scholar

Jana SK, Biswas AB, Das SK. ANN applicability in gas holdup prediction in tapered bubble columns using non-Newtonian pseudoplastic liquids. ChemXpress 2015; 8: 102–111.Suche in Google Scholar

Jhawar AK, Prakash A. Bubble column with internals: effects on hydrodynamics and local heat transfer. Chem Eng Res Des 2014; 92: 25–33.10.1016/j.cherd.2013.06.016Suche in Google Scholar

Joshi JB. Axial mixing in multiphase contactors;a unified correlation. Trans Inst Chem Eng 1980; 58: 155;165.Suche in Google Scholar

Joshi JB, Veera VP, Prasad Ch V, Phanikumar DV, Deshphande NS, Thakre SS, Thorat BN. Gas hold-up structure in bubble column reactors. Pinsa 1998; 64: 441–567.Suche in Google Scholar

Kang Y, Min BT, Nah JB, Kim SD. Mass transfer in continuous bubble columns with floating bubble breakers. AIChE J 1990; 36: 1255–1258.10.1002/aic.690360815Suche in Google Scholar

Kang Y, Cho YJ, Woo KJ, Kim SD. Diagnosis of bubble distribution and mass transfer in pressurized bubble columns with viscous liquid medium. Chem Eng Sci 1999; 54: 4887–4893.10.1016/S0009-2509(99)00209-2Suche in Google Scholar

Kantak MV, Hesketh RP, Kelkar BG. Effect of gas and liquid properties on gas phase dispersion in bubble columns. Chem Eng J Biochem Eng J 1995; 59: 91–100.10.1016/0923-0467(94)02922-9Suche in Google Scholar

Kantarci N, Borak F, Ulgen KO. Bubble column reactors. Process Biochem 2005; 40: 2263–2283.10.1016/j.procbio.2004.10.004Suche in Google Scholar

Kawalec-Pietrenko BT. Time-dependent gas hold-up and bubble size distributions in a gas—highly viscous liquid—solid system. Chem Eng J 1992; 50: B29–B37.10.1016/0300-9467(92)80017-5Suche in Google Scholar

Kawase Y, Moo-Young M. Influence of non-Newtonian flow behaviour on mass transfer in bubble Columns with and without draft tubes. Chem Eng Commun 1986; 40: 67–83.10.1080/00986448608911691Suche in Google Scholar

Kawase Y, Moo-Young M. Theoretical prediction of gas holdup in bubble columns with Newtonian and non-Newtonian fluids. Ind Eng Chem Res 1987; 26: 933–937.10.1021/ie00065a014Suche in Google Scholar

Kawase Y, Umeno S, Kumagai T. The prediction of gas holdup in bubble column reactors: Newtonian and non-Newtonian fluids. Chem Eng J 1992; 50: 1–7.10.1016/0300-9467(92)80001-QSuche in Google Scholar

Kelkar BG, Shah YT. Gas holdup and backmixing in bubble column with polymer solutions. AIChE J 1985; 31: 700–702.10.1002/aic.690310424Suche in Google Scholar

Khare AS, Niranjan K. Mechanically agitated contactors: gas hold up in highly viscous media. IChemE Res Event Proc 1994; 1: 120–122.Suche in Google Scholar

Khare AS, Niranjan K. Impeller-agitated aerobic reactor: the influence of tiny bubbles on gas hold-up and mass transfer in highly viscous liquids. Chem Eng Sci 1995; 50: 1091–1105.10.1016/0009-2509(94)00474-6Suche in Google Scholar

Khare AS, Niranjan K. The effect of impeller design on gas holdup in surfactant containing highly viscous non-Newtonian agitated liquids. Chem Eng Process Process Intensif 2002; 41: 239–249.10.1016/S0255-2701(01)00139-8Suche in Google Scholar

Kojima E, Akehata T, Shirai T. Rising velocity and shape of single air bubbles in highly viscous liquids. J Chem Eng Jpn 1968; 1: 45–50.10.1252/jcej.1.45Suche in Google Scholar

Kulkarni AA, Joshi JB. Bubble formation and bubble rise velocity in gas-liquid systems: a review. Ind Eng Chem Res 2005; 44: 5873–5931.10.1021/ie049131pSuche in Google Scholar

Lahiri SK, Ghanta KC. Development of an artificial neural network correlation for prediction of hold-up of slurry transport in pipelines. Chem Eng Sci 2008; 63: 1497–1509.10.1016/j.ces.2007.11.030Suche in Google Scholar

Lakota A. Effect of highly viscous non-Newtonian liquids on gas holdup in a concurrent upflow bubble column. Acta Chim Slovenica 2007; 54: 678.Suche in Google Scholar

Lee DH, Kim JO, Kim SD. Mass transfer and phase holdup characteristics in three-phase fluidized beds. Chem Eng Commun 1993; 119: 179–196.10.1080/00986449308936115Suche in Google Scholar

Lemoine R, Morsi BI. An algorithm for predicting the hydrodynamic and mass transfer parameters in agitated reactors. Chem Eng J 2005; 114: 9–31.10.1016/j.cej.2005.08.015Suche in Google Scholar

Lemoine R, Fillion B, Behkish A, Smith AE, Morsi BI. Prediction of the gas–liquid volumetric mass transfer coefficients in surface-aeration and gas-inducing reactors using neural networks. Chem Eng Process Process Intensif 2003; 42: 621–643.10.1016/S0255-2701(02)00211-8Suche in Google Scholar

Lemoine R, Behkish A, Sehabiague L, Heintz YJ, Oukaci R, Morsi BI. An algorithm for predicting the hydrodynamic and mass transfer parameters in bubble column and slurry bubble column reactors. Fuel Process Technol 2008; 89: 322–343.10.1016/j.fuproc.2007.11.016Suche in Google Scholar

Leonard C, Ferrasse JH, Boutin O, Lefevre S, Viand A. Bubble column reactors for high pressures and high temperatures operation. Chem Eng Res Des 2015; 100: 391–421.10.1016/j.cherd.2015.05.013Suche in Google Scholar

Li S, Ma Y, Fu T, Zhu C, Li H. The viscosity distribution around a rising bubble in shear-thinning non-Newtonian fluids. Braz J Chem Eng 2012a; 29: 265–274.10.1590/S0104-66322012000200007Suche in Google Scholar

Li S, Zhu C, Fu T, Ma Y. Study on the mass transfer of bubble swarms in three different rheological fluids. Int J Heat Mass Transf 2012b; 55: 6010–6016.10.1016/j.ijheatmasstransfer.2012.06.011Suche in Google Scholar

Li S, Ma Y, Jiang S, Fu T, Zhu C, Li HZ. The drag coefficient and the shape for a single bubble rising in non-Newtonian fluids. J Fluids Eng 2012c; 134: 1–4.10.1115/1.4007073Suche in Google Scholar

Mandal A, Kundu G, Mukherjee D. Gas holdup and entrainment characteristics in a modified downflow bubble column with Newtonian and non-Newtonian liquid. Chem Eng Process Process Intensif 2003; 42: 777–787.10.1016/S0255-2701(02)00134-4Suche in Google Scholar

Mitra T, Singha B, Bar N, Das SK. Removal of Pb (II) ions from aqueous solution using water hyacinth root by fixed-bed column and ANN modeling. J Hazard Mater 2014; 273: 94–103.10.1016/j.jhazmat.2014.03.025Suche in Google Scholar PubMed

Mok YS, Kim YH, Kim SY. Bubble and gas holdup characteristics in a bubble column of CMC solution. Korean J Chem Eng 1990; 7: 31–39.10.1007/BF02697339Suche in Google Scholar

Moo-Young M, Kawase Y. Gas holdup and mass transfer in a bubble column with visco-elastic fluids. Can J Chem Eng 1987; 65: 113–118.10.1002/cjce.5450650118Suche in Google Scholar

Muller FL, Davidson JF. On the contribution of small bubbles to mass transfer in bubble columns containing highly viscous liquids. Chem Eng Sci 1992; 47: 3525–3532.10.1016/0009-2509(92)85066-KSuche in Google Scholar

Nakanoh M, Yoshida F. Gas absorption by Newtonian and non-Newtonian liquids in a bubble column. Ind Eng Chem Process Des Dev 1980; 19: 190–195.10.1021/i260073a033Suche in Google Scholar

Nishikawa M, Kato H, Hashimoto K. Heat transfer in aerated tower filled with non-Newtonian liquid. Ind Eng Chem Process Des Dev 1977; 16: 133–137.10.1021/i260061a607Suche in Google Scholar

Olden JD. An artificial neural network approach for studying phytoplankton succession. Hydrobiologia 2000; 436: 131–143.10.1023/A:1026575418649Suche in Google Scholar

Olden JD, Jackson DA. Illuminating the “black box”: a randomization approach for understanding variable contributions in artificial neural networks. Ecol Model 2002; 154: 135–150.10.1016/S0304-3800(02)00064-9Suche in Google Scholar

Olden JD, Joy MK, Death RG. An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data. Ecol Model 2004; 178: 389–397.10.1016/j.ecolmodel.2004.03.013Suche in Google Scholar

Olivieri G, Russo ME, Simeone M, Marzocchella A, Salatino P. Effects of viscosity and relaxation time on the hydrodynamics of gas–liquid systems. Chem Eng Sci 2011; 66: 3392–3399.10.1016/j.ces.2011.01.027Suche in Google Scholar

Ozturk SS, Schumpe A. The influence of suspended solids on oxygen transfer to organic liquids in a bubble column. Chem Eng Sci 1987; 42: 1781–1785.10.1016/0009-2509(87)80182-3Suche in Google Scholar

Pandit AB, Joshi YK. Mixing time studies in bubble column reactor with and without internals. Int J Chem React Eng 2005; 3: 1–25.10.2202/1542-6580.1182Suche in Google Scholar

Pareek VK, Brungs MP, Adesina AA, Sharma R. Artificial neural network modeling of a multiphase photodegradation system. J Photochem Photobiol A Chem 2002; 149: 139–146.10.1016/S1010-6030(01)00640-2Suche in Google Scholar

Passos AD, Voulgaropoulos VP, Paras SV, Mouza AA. The effect of surfactant addition on the performance of a bubble column containing a non-Newtonian liquid. Chem Eng Res Des 2015; 95: 93–104.10.1016/j.cherd.2015.01.008Suche in Google Scholar

Philip J, Proctor JM, Niranjan K, Davidson JF. Gas hold-up and liquid circulation in internal loop reactors containing highly viscous Newtonian and non-Newtonian liquids. Chem Eng Sci 1990; 45: 651–664.10.1016/0009-2509(90)87008-GSuche in Google Scholar

Pilizota V, Subaric D, Lovric T. Rheological properties of CMC dispersions at low temperatures. Food Technol Biotechnol 1996; 34: 87–90.Suche in Google Scholar

Pirdashti M, Curteanu S, Kamangar MH, Hassim MH, Khatami MA. Artificial neural networks: applications in chemical engineering. Rev Chem Eng 2013; 29: 205–239.10.1515/revce-2013-0013Suche in Google Scholar

Pradhan AK, Parichha RK, De P. Flow behavior and gas holdup in two-phase bubble column. Inst Eng (India) 1991; 72: 6–9.Suche in Google Scholar

Pradhan AK, Parichha RK, De P. Gas hold-up in non-Newtonian solutions in a bubble column with internals. Can J Chem Eng 1993; 71: 468–471.10.1002/cjce.5450710319Suche in Google Scholar

Reisener J, Reuter MA, Kruger J. Modelling of the mass transfer in gas-sparged electrolysers with neural nets. Chem Eng Sci 1993; 48: 1089–1101.10.1016/0009-2509(93)81039-XSuche in Google Scholar

Rodrigue D. Drag coefficient;Reynolds number transition for gas bubbles rising steadily in viscous fluids. Can J Chem Eng 2001; 79: 119;123.10.1002/cjce.5450790118Suche in Google Scholar

Roy S, Parichha RK, De P, Ray P, Barman B. Gas holdup in bubble column with immersed tubes. Proc Indian Chem Eng Cong 1989; 1: 72–77.Suche in Google Scholar

Rumelhart DE, Hinton GE, Williams RJ. Learning internal representation by error propagation. In: Rumelhart DE, McClelland JL, editors. Parallel distributed processing, Vol. 1, Chapter 8. Cambridge, MA: MIT Press, 1986.10.7551/mitpress/5236.001.0001Suche in Google Scholar

Ryu HW, Chang YK, Kim SD. Gas holdup and mass transfer characteristics of carboxymethyl cellulose solutions in a bubble column with a radial gas sparger. Bioprocess Eng 1993; 8: 271–277.10.1007/BF00369840Suche in Google Scholar

Saxena SC, Vadivel R. Heat transfer from a tube bundle in a bubble column. Int Commun Heat Mass Transf 1988; 15: 657–667.10.1016/0735-1933(88)90056-5Suche in Google Scholar

Schumpe A, Deckwer WD. Gas holdups, specific interfacial areas, and mass transfer coefficients of aerated carboxymethyl cellulose solutions in a bubble column. Ind Eng Chem Process Des Dev 1982; 21: 706–711.10.1021/i200019a028Suche in Google Scholar

Schumpe A, Deckwer WD. Organic liquids in a bubble column: holdups and mass transfer coefficients. AIChE J 1987a; 33: 1473–1480.10.1002/aic.690330907Suche in Google Scholar

Schumpe A, Deckwer WD. Viscous media in tower bioreactors: hydrodynamic characteristics and mass transfer properties. Bioprocess Eng 1987b; 2: 79–94.10.1007/BF00369528Suche in Google Scholar

Schumpe A, Deckwer WD, Nigam KD. Gas-liquid mass transfer in three-phase fluidized beds with viscous pseudoplastic liquids. Can J Chem Eng 1989; 67: 873–877.10.1002/cjce.5450670523Suche in Google Scholar

Schwarz S, Kempe T, Fröhlich J. An immersed boundary method for the simulation of bubbles with varying shape. J Comput Phys 2016; 315: 124–149.10.1016/j.jcp.2016.01.033Suche in Google Scholar

Shah YT, Kelkar BG, Godbole SP, Deckwer WD. Design parameters estimations for bubble column reactors. AIChE J 1982; 28: 353–379.10.1002/aic.690280302Suche in Google Scholar

Shaikh A, Al-Dahhan M. Development of an artificial neural network correlation for prediction of overall gas holdup in bubble column reactors. Chem Eng Process Process Intensif 2003; 42: 599–610.10.1016/S0255-2701(02)00209-XSuche in Google Scholar

Sharma R, Singh K, Singhal D, Ghosh R. Neural network applications for detecting process faults in packed towers. Chem Eng Process Process Intensif 2004; 43: 841–847.10.1016/S0255-2701(03)00103-XSuche in Google Scholar

Suh IS, Schumpe A, Deckwer WD, Kulicke WM. Gas-liquid mass transfer in the bubble column with viscoelastic liquid. Can J Chem Eng 1991; 69: 506–512.10.1002/cjce.5450690215Suche in Google Scholar

Takahashi T, Miyahara T, Izawa H. Drag coefficient and wake volume of single bubbles rising through quiescent liquid. Kagaku Kogaku Ronbunshu 1976; 2: 480–487.10.1252/kakoronbunshu.2.480Suche in Google Scholar

Tripathi MK, Sahu KC, Govindarajan R. Dynamics of an initially spherical bubble rising in quiescent liquid. Nat Commun 2015; 6: 1–9.10.1038/ncomms7268Suche in Google Scholar

Utomo MB, Sakai T, Uchida S, Maezawa A. Simultaneous measurement of mean bubble diameter and local gas holdup using ultrasonic method with neural network. Chem Eng Technol 2001; 24: 493–500.10.1002/1521-4125(200105)24:5<493::AID-CEAT493>3.0.CO;2-LSuche in Google Scholar

Utomo MB, Sakai T, Uchida S. Use of neural network–ultrasonic technique for measuring gas and solid hold‐ups in a slurry bubble column bubble colum. Chem Eng Technol 2002; 25: 293–299.10.1002/1521-4125(200203)25:3<293::AID-CEAT293>3.0.CO;2-XSuche in Google Scholar

Valente GFS, Mendonça RCS, Pereira JAM, Felix LB. Artificial neural network prediction of chemical oxygen demand in dairy industry effluent treated by electrocoagulation. Sep Purif Technol 2014; 132: 627–633.10.1016/j.seppur.2014.05.053Suche in Google Scholar

Vatai GY, Tekic MN. Gas holdup and mass transfer in bubble columns with pseudoplastic liquids. Chem Eng Sci 1989; 44: 2402–2407.10.1016/0009-2509(89)85178-4Suche in Google Scholar

Veera UP, Joshi JB. Measurement of gas holdup profiles in bubble column by gamma ray tomography: effect of liquid phase properties. Chem Eng Res Des 2000; 78: 425–434.10.1205/026387600527329Suche in Google Scholar

Vinaya M, Varma YBG. Some aspects of hydrodynamics in multistage bubble columns. Bioprocess Eng 1995; 13: 231–237.10.1007/BF00417633Suche in Google Scholar

Wanchoo RK, Sharma SK, Bansal R. Rheological parameters of some water-soluble polymers. J Polym Mater 1996; 13: 49–55.Suche in Google Scholar

Wanchoo RK, Sharma SK, Gupta R. Shape of a Newtonian liquid drop moving through an immiscible quiescent non-Newtonian liquid. Chem Eng Process Process Intensif 2003; 42: 387–393.10.1016/S0255-2701(02)00059-4Suche in Google Scholar

Wellek RM, Agrawal AK, Skelland AHP. Shape of liquid drops moving in liquid media. AIChE J 1966; 12: 854–862.10.1002/aic.690120506Suche in Google Scholar

Wenyuan F, Youguang M, Shaokun J, Ke Y, Huaizhi L. An experimental investigation for bubble rising in non-Newtonian fluids and empirical correlation of drag coefficient. J Fluids Eng 2010; 132: 1–7.10.1115/1.4000739Suche in Google Scholar

Wenyuan F, XiaoHong Y. A laser imaging-LDV coupling measurement of single bubble forming and rising in shear-thinning fluid. J Thermal Sci 2014; 23: 233;238.10.1007/s11630-014-0700-zSuche in Google Scholar

Yamashita F. Effects of vertical pipe and rod internals on gas holdup in bubble columns. J Chem Eng Jpn 1987a; 20: 204–206.10.1252/jcej.20.204Suche in Google Scholar

Yamashita F. Effect of shape of baffle plates and mesh and cross-sectional area of wire gauges on gas hold-up and pressure drop in a bubble column. J Chem Eng Jpn 1987b; 20: 201–204.10.1252/jcej.20.201Suche in Google Scholar

Yang H, Fang B, Reuss M. k_La Correlation established on the basis of a neural network model. Can J Chem Eng 1999; 77: 838–843.10.1002/cjce.5450770508Suche in Google Scholar

Youssef AA, Al-Dahhan MH. Impact of internals on the gas holdup and bubble properties of a bubble column. Ind Eng Chem Res 2009; 48: 8007–8013.10.1021/ie900266qSuche in Google Scholar

Yuanxin W, Xianghua L, Qiming C, Dinghuo LI, Shirong L, Al-Dahhan MH, Dudukovic MP. Prediction of gas holdup in bubble columns using artificial neural network. Chin J Chem Eng 2003; 11: 162–165.Suche in Google Scholar

Zhang L, Yang C, Mao ZS. An empirical correlation of drag coefficient for a single bubble rising in non-Newtonian liquids. Ind Eng Chem Res 2008a; 47: 9767–9772.10.1021/ie8010319Suche in Google Scholar

Zhang L, Yang C, Mao ZS. Unsteady motion of a single bubble in highly viscous liquid and empirical correlation of drag coefficient. Chem Eng Sci 2008b; 63: 2099–2106.10.1016/j.ces.2008.01.010Suche in Google Scholar