1. JCCT
  2. All Volumes and Issues
  3. Volume 17, Number 3, 2023
  4. Effects of Brownian Motions and Fractal Structure of Nanoparticles on Natural Convection

Effects of Brownian Motions and Fractal Structure of Nanoparticles on Natural Convection

JCCT.
2023;
Volume 17, Number 3
: pp. 617 - 624
https://doi.org/10.23939/chcht17.03.617
Authors:
  1. Zohreh Zobeidi
  2. Roohollah Sadeghi
  3. Mohamad-Taghi Rostami
1
Department of Chemical Engineering, ACECR institute of Higher Education (Isfahan Branch)
2
Department of Chemical Engineering, ACECR institute of Higher Education (Isfahan Branch)
3
Department of Engineering, Esfahan Oil Refining Company

The study simulated heat transfer in alumina-water nanofluid in a natural convection flow and Rayleigh-Benard configuration considering the Brownian motions and fractal structure of the nanofluids. The simulations were based on a two-dimensional, Eulerian-Eulerian method. Many simulations have been performed to examine the effect of aspect ratio, heat flux, and para-meters related to the structure of the nanoclusters including size, fractal dimension, and volume fraction on the natural convective heat transfer coefficient. The comparison between the simulation results and the experimental data of heat transfer coefficient indicates a good agreement. The simulation results indicated that the enhancement of aspect ratio, heat flux, and fractal dimension increases the heat transfer coefficient. On the other hand, the reduction of nanoclusters and nanoparticle size decreased this coefficient. Moreover, the simulation results showed that in high heat transfer fluxes, the heat transfer coefficient first increases by increasing the nanoparticles solid volume fraction and then decreases. However, heat transfer coefficient decreased steadily with the increase in the nanoparticles solid volume fraction in low heat transfer fluxes. The results suggested that using the nanoparticles Brownian motion mechanism along with their fractal structure can be well-applied in natural-convection heat transfer modelling of nanofluids.

nanofluid
alumina-water
nanoclusters
fractal dimension
natural convective heat transfer coefficient
  1. Kouloulias, K.; Sergis, A.; Hardalupas, Y.Sedimentation in Nanofluids During a Natural Convection Experiment.Int. J. Heat Mass Transf.2016, 101, 1193-1203. https://doi.org/10.1016/j.ijheatmasstransfer.2016.05.113
  2. Ghadimi, A.; Saidur, R.; Metselaar, H.A Review of Nanofluid Stability Properties and Characterization in Stationary Conditions. Int. J. Heat Mass Transf.2011, 54, 4051-4068. https://doi.org/10.1016/j.ijheatmasstransfer.2011.04.014
  3. Hadad, Z.; Oztop, H.F.; Abu-Nada, E.;Mataoui, A.A Review on Natural Convective Heat Transfer of Nanofluids. Renew. Sust.Energ. Rev. 2012, 16, 5363-5378. https://doi.org/10.1016/j.rser.2012.04.003
  4. Yuan, M.; Mohebbi, R.; Rashidi, M.M.;Zhigang, Y.Simulation of Nanofluid Natural Convection in a U-Shaped Cavity Equipped by a Heating Obstacle: Effect of Cavity's Aspect Ratio. J Taiwan Inst Chem Eng2018, 93, 263-276. https://doi.org/10.1016/j.jtice.2018.07.026
  5. Meng, X.; Li,Y.Numerical Study of Natural Convection in a Horizontal Cylinder Filled with Water-Based Alumina Nanoflu-id.Nanoscale. Res. Let.2015, 10, 142. https://doi.org/10.1186/s11671-015-0847-x
  6. Ilyas, S.U.; Pendyala, R.; Narahari, M. Experimental Investiga-tion of Natural Convection Heat Transfer Characteristics in MWCNT-thermal Oil Nanofluid. J Therm Anal Calorim2019, 135, 1197-1209. https://doi.org/10.1007/s10973-018-7546-7
  7. Sarkar, J.A Critical Review on Convective Heat Transfer Correlations of Nanofluids.Renew. Sust. Energ. Rev. 2011, 15, 3271-3277. https://doi.org/10.1016/j.rser.2011.04.025
  8. Sheikhzadeh, G.A.;Ebrahim Qomi, M.; Hajialigol, N.; Fattahi, A.Numerical Study of Mixed Convection Flows in a Lid-Driven Enclosure Filled with Nanofluid Using Variable Properties.Results Phys.2012, 2, 5-13. https://doi.org/10.1016/j.rinp.2012.01.001
  9. Ehteram, H.R.; Abbasianarani, A.A.; Sheikhzadeh, G.A.;Aghaei, A.; Malihi,A.R.The Effect of Various Conductivity and Viscosity Models Considering Brownian Motion on Nanofluids Mixed Convection Flow and Heat Transfer. Chall. Nano Micro Scale Sci. Tech.2016, 4, 19-28. https://doi.org/10.7508/tpnms.2016.01.003
  10. Ghasemi, B.; Aminossadati S.M.Brownian Motion of Nano-particles in a Triangular Enclosure with Natural Convection.Int. J. Therm. Sci. 2010, 49, 931-940. https://doi.org/10.1016/j.ijthermalsci.2009.12.017
  11. Aminfar, H.; Haghgoo, M.R.Brownian Motion and Thermo-phoresis Effects on Natural Convection of Alumina–Water Nanofluid.J. Mech. Eng. Sci. 2012, 227, 100. https://doi.org/10.1177/0954406212445683
  12. Haddad, Z.; Abu-Nada, E.; Oztop, H F.; Mataoui, A.Natural Convection in Nanofluids: Are the Thermophoresis and Brownian Motion Effects Significant in Nanofluid Heat Transfer Enhance-ment?Int. J. Therm. Sci. 2012, 57, 152-162. https://doi.org/10.1016/j.ijthermalsci.2012.01.016
  13. Hong, J.; Kim, D.Effects of Aggregation on the Thermal Conductivity of Alumina/Water Nanofluids.Thermochim. Acta2011, 542, 28-32.https://doi.org/10.1016/j.tca.2011.12.019
  14. Shalkevich, N.; Shalkevich, A.; Bürgi, T.Thermal Conductivi-ty of Concentrated Colloids in Different States.J. Phys. Chem. 2010, 114, 9568-9572.https://doi.org/10.1021/jp910722j
  15. Hong, K.S.; Hong, T.K.; Yang, H.S.Thermal Conductivity of Fe nanofluids Depending on the Cluster Size of Nanoparticles.App. Phys. Lett. 2006, 88, 031901.https://doi.org/10.1063/1.2166199
  16. Wu, C.; Cho, T.J.; Xu, J.;Lee, D.; Yang, B.; Zachariah, M.R.Effect of Nanoparticle Clustering on the Effective Thermal Conductivity of Concentrated Silica Colloids.Phys. Rev. 2010, 81, 011406. https://doi.org/10.1103/PhysRevE.81.011406
  17. Sadeghi, R.; Haghshenasfard, M.; Etemad, S.Gh.;Keshavarzi, E.Theoretical Investigation of Nanoparticles Aggregation Effect on Water-Alumina Laminar Convective Heat Transfer.Int. Commun. Heat Mass Transf.2016, 72, 57-63. https://doi.org/10.1016/j.icheatmasstransfer.2016.01.006
  18. Artyukhov, A.; Sklabinskyi, V.Theoretical Analysis of Gra-nules Movement Hydrodynamics in the Vortex Granulators of Ammonium Nitrate and Carbamide Production.Chem. Chem. Tech-nol. 2015, 9, 175-180.https://doi.org/10.23939/chcht09.02.175
  19. Nagursky, O.; Gumnitsky, Ya.; Vaschuk, V.Unsteady Heat Transfer during Encapsulation of Dispersed Materials in Quasi-liquefied State.Chem. Chem. Technol. 2015, 9, 497-501. https://doi.org/10.23939/chcht09.04.497
  20. Kindzera, D.; Hosovskyi, R.; Atamanyuk, V.; Symak, D.Heat Transfer Process During Filtration Drying of Grinded Sunflower Biomass.Chem. Chem. Technol. 2021, 15, 118-124. https://doi.org/10.23939/chcht15.01.118
  21. ANSYS CFX Solver Theory Guide r15; ANSYS Inc., 2015.
  22. Schiller, L.; Naumann, A. A Drag Coefficient Corre-lation. VDI Zeitung1935, 77, 318-320.
  23. Li, A.; Ahmadi, G.Dispersion and Deposition of Spherical Particles from Point Sources in a Turbulent Channel Flow.Aerosol. Sci. Technol. 1992, 16, 209-226. https://doi.org/10.1080/02786829208959550
  24. Evans, W.; Prasher, R.; Fish, J.;Meakin, P.; Phelan, P.; Keb-linski, P.Effect of Aggregation and Interfacial Thermal Resistance on Thermal Conductivity of Nanocomposites and Colloidal Nanof-luids.Int. J. Heat Mass Transf.2008, 51, 1431-1438. https://doi.org/10.1016/j.ijheatmasstransfer.2007.10.017
  25. Nan, C.-W.; Birringer, R.; Clarke, D.R.;Gleiter, H.Effective Thermal Conductivity of Particulate Composites with Interfacial Thermal Resistance.J. App. Phys. 1997, 81, 6692-6699. https://doi.org/10.1063/1.365209