Abstract
CNT based nanofluids have great potential in the field of heat transfer due to their higher thermal conductivity compared to other categories of nanofluids. However, their applicability to different flow conditions is unknown. The flow behaviour of MWCNT/water nanofluids was investigated in this study under a variety of conditions, including concentration, temperature, and shear stress (0–35 Pa). Non-Newtonian flow properties of prepared samples have been found by experiments. MWCNT/Water nanofluids have shown that flow behaviour is strongly influenced by concentration. This contrasting rheological activity of MWCNT/water nanofluid at various concentrations was also attributed to SDS surfactant. The concept of molecular association of MWCNT and SDS molecules over the various structures formed by MWCNT at different concentrations and shear conditions is used to describe the insight flow characteristics of MWCNT. Power-law model-based curve fitting was used to study the variations in flow behaviour of MWCNT/water nanofluid. On the basis of qualitative results, this model was found to be the best-fitting model. Furthermore, an optimal Artificial Neural Network (ANN) was used to predict the complex viscosity of MWCNT/water nanofluid over flow behaviour variation, which is difficult to predict using traditional models. The influence of different parameters such as the weight percent concentration of nanofluid, temperature, shear time, and shear stress are all taken into account in this model. The model was trained on a dataset from current research and demonstrated outstanding accuracy in predicting viscosity (for the testing data, obtained R2 and RMSE are 0.9993 and 0.0035).
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Abbreviations
- n :
-
Flow behavior index
- k :
-
Consistency index (Pa sn)
- T :
-
Temperature (℃)
- m :
-
Mass (kg)
- d :
-
The diameter of the particle (nm)
- N :
-
Nodes
- b :
-
Bias
- h :
-
Interparticle spacing
- C :
-
Correlation factor
- δ :
-
The distance between the center of the particle
- Φ :
-
Volumetric concentration
- σ :
-
Shear stress (Pa)
- γ :
-
Shear rate (s-1)
- λ :
-
Mean free path of the fluid (m)
- τ p :
-
Relaxation time
- μ :
-
Dinamic viscosity[Pa.s]
- ρ :
-
Density of air[kg/m3]
- f :
-
Base fluid
- ρ :
-
Density of air[kg/m3]
- nf :
-
Nano fluid
- p :
-
Particles
- W :
-
Water
- wt :
-
Weight
- vol :
-
Volumetric
- r :
-
Number of dataset
- exp :
-
Experimental value
- pred :
-
Predicted value
References
Ghadimi A, Saidur R, Metselaar HSC (2011) A review of nanofluid stability properties and characterization in stationary conditions. Int J Heat Mass Transf. https://doi.org/10.1016/j.ijheatmasstransfer.2011.04.014
Yadav D, Upadhyay Z, Kushwaha A, Mishra A (2020) Analysis over trio-tube with dual thermal communication surface heat exchanger [T.T.H.Xr.]. In: Recent Trends in Mechanical Engineering pp 1–13
Wang X, Xu X, Choi SUS (1999) Thermal conductivity of nanoparticle-fluid mixture. J Thermophys Heat Transfer 13:474–480. https://doi.org/10.2514/2.6486
Sommers AD, Yerkes KL (2010) Experimental investigation into the convective heat transfer and system-level effects of Al2O3-propanol nanofluid. J Nanopart Res 12:1003–1014. https://doi.org/10.1007/s11051-009-9657-3
Esfe MH, Esfandeh S (2020) The statistical investigation of multi-grade oil based nanofluids: Enriched by MWCNT and ZnO nanoparticles. Phys A 554:122159. https://doi.org/10.1016/j.physa.2019.122159
Mosavian MTH, Heris SZ, Etemad SG, Esfahany MN (2010) Heat transfer enhancement by application of nano-powder. J Nanopart Res 12:2611–2619. https://doi.org/10.1007/s11051-009-9840-6
Choi SUS, Zhang ZG, Yu W (2001) Anomalous thermal conductivity enhancement in nanotube suspensions. Appl Phys Lett https://doi.org/10.1063/1.1408272
de Heer WA, Ch telain A, Ugarte D (1995) A Carbon Nanotube Field-Emission Electron Source. Science 270:1179–1180. https://doi.org/10.1126/science.270.5239.1179
Kong J, Javey A (2009) Carbon Nanotube Electronics. Springer, US, Boston, MA
Kaushik BK, Majumder MK (2015) Carbon nanotube: Properties and Applications pp 17–37
Zhang J, Gao L (2007) Dispersion of multiwall carbon nanotubes by sodium dodecyl sulfate for preparation of modified electrodes toward detecting hydrogen peroxide. Mater Lett 61:3571–3574. https://doi.org/10.1016/j.matlet.2006.11.138
Khan MI, Shah F, Hayat T, Alsaedi A (2019) Transportation of CNTs based nanomaterial flow confined between two coaxially rotating disks with entropy generation. Phys A 527:121154. https://doi.org/10.1016/j.physa.2019.121154
Patel HE, Anoop KB, Sundararajan T, Das SK (2008) Model for thermal conductivity of CNT-nanofluids. Bull Mater Sci 31:387–390. https://doi.org/10.1007/s12034-008-0060-y
Yang L, Ji W, Huang J nan, Xu G (2019) An updated review on the influential parameters on thermal conductivity of nano-fluids. J Mol Liq 296
Rehman WU, Merican ZMA, Bhat AH (2019) Synthesis, characterization, stability and thermal conductivity of multi-walled carbon nanotubes (MWCNTs) and eco-friendly jatropha seed oil based nanofluid: An experimental investigation and modeling approach. J Mol Liq 293 https://doi.org/10.1016/j.molliq.2019.111534
Sadri R, Ahmadi G, Togun H (2014) An experimental study on thermal conductivity and viscosity of nanofluids containing carbon nanotubes. Nanoscale Res Lett 9:151. https://doi.org/10.1186/1556-276X-9-151
Lu G, Duan Y-Y, Wang X-D (2014) Surface tension, viscosity, and rheology of water-based nanofluids: a microscopic interpretation on the molecular level. J Nanopart Res 16:2564. https://doi.org/10.1007/s11051-014-2564-2
Yadav D, Kumar R, Singh PK (2018) Experimental investigation on rheology property of MWCNT-Al2O3/water hybrid nanofluid. p 020042
Bobbo S, Fedele L, Benetti A (2012) Viscosity of water based SWCNH and TiO2 nanofluids. Exp Thermal Fluid Sci 36:65–71. https://doi.org/10.1016/j.expthermflusci.2011.08.004
Sen S, Moazzen E, Aryal S (2015) Engineering nanofluid electrodes: controlling rheology and electrochemical activity of γ-Fe2O3 nanoparticles. J Nanopart Res 17:437. https://doi.org/10.1007/s11051-015-3242-8
Garbadeen ID, Sharifpur M, Slabber JM, Meyer JP (2017) Experimental study on natural convection of MWCNT-water nanofluids in a square enclosure. Int Commun Heat Mass Transfer 88:1–8. https://doi.org/10.1016/j.icheatmasstransfer.2017.07.019
Estellé P, Halelfadl S, Maré T (2015) Thermal conductivity of CNT water based nanofluids: Experimental trends and models overview. Journal of Thermal Engineering 1:381. https://doi.org/10.18186/jte.92293
Hojjat M, Etemad SG, Bagheri R, Thibault J (2011) Rheological characteristics of non-Newtonian nanofluids: Experimental investigation. Int Commun Heat Mass Transfer 38:144–148. https://doi.org/10.1016/j.icheatmasstransfer.2010.11.019
Talebizadehsardari P, Shahsavar A, Toghraie D, Barnoon P (2019) An experimental investigation for study the rheological behavior of water–carbon nanotube/magnetite nanofluid subjected to a magnetic field. Phys A 534:122129. https://doi.org/10.1016/j.physa.2019.122129
Hung YH, Chou WC (2012) Chitosan for Suspension Performance and Viscosity of MWCNTs. International Journal of Chemical Engineering and Applications 347–353. https://doi.org/10.7763/IJCEA.2012.V3.215
Esfe MH, Rostamian H, Afrand M, Wongwises S (2016) Examination of effects of multi-walled carbon nanotubes on rheological behavior of engine oil (10W40). J Nanostruct. https://doi.org/10.22052/jns.2016.41620
Allaoui A, Bounia N (2010) Rheological and Electrical Transitions in Carbon Nanotube/Epoxy Suspensions. Curr Nanosci 6:158–162. https://doi.org/10.2174/157341310790945669
Dalkilic ASS, Küçükyıldırım BOO, Akdogan Eker A (2017) Experimental investigation on the viscosity of Water-CNT and Antifreeze-CNT nanofluids. Int Commun Heat Mass Transfer 80:47–59. https://doi.org/10.1016/j.icheatmasstransfer.2016.11.011
Einstein A (1956) Investigations O N the Theory .of ,the Brownian Movement R. F Ü R T H Translated By. Dover, New York
Brinkman HC (1952) The Viscosity of Concentrated Suspensions and Solutions. J Chem Phys 20:571–571. https://doi.org/10.1063/1.1700493
Frankel NA, Acrivos A (1967) On the viscosity of a concentrated suspension of solid spheres. Chem Eng Sci 22:847–853. https://doi.org/10.1016/0009-2509(67)80149-0
Lundgren TS (1972) Slow flow through stationary random beds and suspensions of spheres. J Fluid Mech 51:273–299. https://doi.org/10.1017/S002211207200120X
Batchelor GK (1977) The effect of Brownian motion on the bulk stress in a suspension of spherical particles. J Fluid Mech 83:97–117. https://doi.org/10.1017/S0022112077001062
Krieger IM, Dougherty TJ (1959) A Mechanism for Non-Newtonian Flow in Suspensions of Rigid Spheres. Trans Soc Rheol 3:137–152. https://doi.org/10.1122/1.548848
Eilers H (1941) Die Viskosität von Emulsionen hochviskoser Stoffe als Funktion der Konzentration. Kolloid-Zeitschrift 97:313–321. https://doi.org/10.1007/BF01503023
Saito R, Fujita M, Dresselhaus G, Dresselhaus MS (1992) Electronic structure of chiral graphene tubules. Appl Phys Lett https://doi.org/10.1063/1.107080
Vand V (1948) Viscosity of Solutions and Suspensions. I. Theory. J Phys Colloid Chem 52:277–299. https://doi.org/10.1021/j150458a001
Tseng WJ, Lin K-C (2003) Rheology and colloidal structure of aqueous TiO2 nanoparticle suspensions. Mater Sci Eng, A 355:186–192. https://doi.org/10.1016/S0921-5093(03)00063-7
Namburu PK, Kulkarni DP, Misra D, Das DK (2007) Viscosity of copper oxide nanoparticles dispersed in ethylene glycol and water mixture. Exp Thermal Fluid Sci 32:397–402. https://doi.org/10.1016/j.expthermflusci.2007.05.001
Graham AL (1981) On the viscosity of suspensions of solid spheres. Appl Sci Res 37:275–286. https://doi.org/10.1007/BF00951252
Masoumi N, Sohrabi N, Behzadmehr A (2009) A new model for calculating the effective viscosity of nanofluids. J Phys D Appl Phys 42:055501. https://doi.org/10.1088/0022-3727/42/5/055501
Corcione M (2011) Empirical correlating equations for predicting the effective thermal conductivity and dynamic viscosity of nanofluids. Energy Convers Manage 52:789–793. https://doi.org/10.1016/j.enconman.2010.06.072
Rostamian SH, Biglari M, Saedodin S, Hemmat Esfe M (2017) An inspection of thermal conductivity of CuO-SWCNTs hybrid nanofluid versus temperature and concentration using experimental data, ANN modeling and new correlation. J Mol Liq 231:364–369. https://doi.org/10.1016/j.molliq.2017.02.015
Esfe MH, Naderi A, Akbari M (2015) Evaluation of thermal conductivity of COOH-functionalized MWCNTs/water via temperature and solid volume fraction by using experimental data and ANN methods. J Therm Anal Calorim 121:1273–1278. https://doi.org/10.1007/s10973-015-4565-5
Eshgarf H, Sina N, Esfe MH (2018) Prediction of rheological behavior of MWCNTs–SiO2/EG–water non-Newtonian hybrid nanofluid by designing new correlations and optimal artificial neural networks. J Therm Anal Calorim 132:1029–1038. https://doi.org/10.1007/s10973-017-6895-y
Yadav D, Naruka DS, Singh PK (2020) Employing ANN model for prediction of thermal conductivity of cnt nanofluids. In: 2020 International Conference on Contemporary Computing and Applications (IC3A). IEEE, pp 163–168
Esfe MH, Rostamian SH (2020) Rheological behavior characteristics of MWCNT-TiO2/EG (40%–60%) hybrid nanofluid affected by temperature, concentration, and shear rate: An experimental and statistical study and a neural network simulating. Phys A 553:124061. https://doi.org/10.1016/j.physa.2019.124061
Yadav D, Dansena P, Ghosh SK, Singh PK (2020) A unique multilayer perceptron model (ANN) for different oxide/EG nanofluid’s viscosity from the experimental study. Phys A 549:124030. https://doi.org/10.1016/j.physa.2019.124030
Esfe MH, Reiszadeh M, Esfandeh S, Afrand M (2018) Optimization of MWCNTs (10%) – Al2O3 (90%)/5W50 nanofluid viscosity using experimental data and artificial neural network. Phys A 512:731–744. https://doi.org/10.1016/j.physa.2018.07.040
Wu H, Al-Rashed AAAA, Barzinjy AA (2019) Curve-fitting on experimental thermal conductivity of motor oil under influence of hybrid nano additives containing multi-walled carbon nanotubes and zinc oxide Physica A 535 https://doi.org/10.1016/j.physa.2019.122128
Esfe MH, Afrand M (2020) Mathematical and artificial brain structure-based modeling of heat conductivity of water based nanofluid enriched by double wall carbon nanotubes. Phys A 540:120766. https://doi.org/10.1016/j.physa.2019.04.002
Esfe MH, Saedodin S, Mahian O, Wongwises S (2014) Thermophysical properties, heat transfer and pressure drop of COOH-functionalized multi walled carbon nanotubes/water nanofluids. Int Commun Heat Mass Transfer 58:176–183. https://doi.org/10.1016/j.icheatmasstransfer.2014.08.037
Hamaker HC (1937) The London-van der Waals attraction between spherical particles. Physica 4:1058–1072. https://doi.org/10.1016/S0031-8914(37)80203-7
Duan WH, Wang Q, Collins F (2011) Dispersion of carbon nanotubes with SDS surfactants: A study from a binding energy perspective. Chem Sci 2:1407–1413. https://doi.org/10.1039/c0sc00616e
Waele O-D (1923) Viscometry and Plastometry. Journal of the Oil & Colour Chemists Association 6:33–69
Boersma WH, Laven J, Stein HN (1990) Shear thickening (dilatancy) in concentrated dispersions. AIChE J 36:321–332. https://doi.org/10.1002/aic.690360302
Naiya TK, Kumar R, Mohapatra S, Mandal A (2014) Studies on the Effect of Surfactants on Rheology of Synthetic Crude. Journal of Petroleum Science Research 3:90. https://doi.org/10.14355/jpsr.2014.0302.06
Malkin AY, Isayev AI (2011) Rheology: Concepts, methods, and applications: Second edition
Hemmat Esfe M, Abbasian Arani AA, Madadi MR, Alirezaie A (2018) A study on rheological characteristics of hybrid nano-lubricants containing MWCNT-TiO2 nanoparticles. J Mol Liq 260:229–236. https://doi.org/10.1016/j.molliq.2018.01.101
Mishra PC, Mukherjee S, Nayak SK, Panda A (2014) A brief review on viscosity of nanofluids. International Nano Letters 4:109–120. https://doi.org/10.1007/s40089-014-0126-3
Meyer JP, Adio SA, Sharifpur M, Nwosu PN (2016) The Viscosity of Nanofluids: A Review of the Theoretical, Empirical, and Numerical Models. Heat Transfer Eng 37:387–421. https://doi.org/10.1080/01457632.2015.1057447
Garg P, Alvarado JL, Marsh C (2009) An experimental study on the effect of ultrasonication on viscosity and heat transfer performance of multi-wall carbon nanotube-based aqueous nanofluids. Int J Heat Mass Transf 52:5090–5101. https://doi.org/10.1016/j.ijheatmasstransfer.2009.04.029
Phuoc TX, Massoudi M, Chen R-H (2011) Viscosity and thermal conductivity of nanofluids containing multi-walled carbon nanotubes stabilized by chitosan. Int J Therm Sci 50:12–18. https://doi.org/10.1016/j.ijthermalsci.2010.09.008
Li F-C, Yang J-C, Zhou W-W (2013) Experimental study on the characteristics of thermal conductivity and shear viscosity of viscoelastic-fluid-based nanofluids containing multiwalled carbon nanotubes. Thermochim Acta 556:47–53. https://doi.org/10.1016/j.tca.2013.01.023
Yu L, Bian Y, Liu Y, Xu X (2019) Experimental investigation on rheological properties of water based nanofluids with low MWCNT concentrations. Int J Heat Mass Transf 135:175–185. https://doi.org/10.1016/j.ijheatmasstransfer.2019.01.120
Nasiri A, Shariaty-Niasar M, Rashidi AM, Khodafarin R (2012) Effect of CNT structures on thermal conductivity and stability of nanofluid. Int J Heat Mass Transf 55:1529–1535. https://doi.org/10.1016/j.ijheatmasstransfer.2011.11.004
Gu B, Hou B, Lu Z (2013) Thermal conductivity of nanofluids containing high aspect ratio fillers. Int J Heat Mass Transf 64:108–114. https://doi.org/10.1016/j.ijheatmasstransfer.2013.03.080
Almanassra IW, Manasrah AD, Al-Mubaiyedh UA (2020) An experimental study on stability and thermal conductivity of water/CNTs nanofluids using different surfactants: A comparison study. J Mol Liq 304:111025. https://doi.org/10.1016/j.molliq.2019.111025
Glory J, Bonetti M, Helezen M (2008) Thermal and electrical conductivities of water-based nanofluids prepared with long multiwalled carbon nanotubes. J Appl Phys 103. https://doi.org/10.1063/1.2908229
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The authors gratefully acknowledge the CRF facility of IIT (ISM) Dhanbad for providing the research facility and support during this work.
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Yadav, D., Naruka, D.S. & Singh, P.K. The insight flow characteristics of concentrated MWCNT in water base fluid: experimental study and ANN modelling. Heat Mass Transfer 57, 1829–1844 (2021). https://doi.org/10.1007/s00231-021-03086-x
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DOI: https://doi.org/10.1007/s00231-021-03086-x