Skip to main content
SpringerLink
Log in

Optimizing flow properties of the different nanofluids inside a circular tube by using entropy generation minimization approach

  • Published:
Journal of Thermal Analysis and Calorimetry Aims and scope Submit manuscript

Abstract

The use of nanofluids as working fluid is one of the represented methods in efficiency enhancement of various systems. One of the most important subjects in nanofluid utilization is finding the optimal conditions. In this study, the efforts have been made to find optimal condition of forced convection nanofluid flow inside a circular tube. The flow is assumed turbulent, and optimization process is carried out for two metallic oxide nanoparticles (Al2O3, CuO) and one nonmetallic oxide nanoparticle (SiO2), dispersed in a 60:40% ethylene glycol/water base fluid. The optimization process has been performed based on the second law of thermodynamic and entropy generation minimization approach. The process has been focused on finding the optimal values for volume fraction, Reynolds number, diameter of particles and average flow temperature. Results show that two metallic oxide nanofluids generate less entropy compared with nonmetallic oxide nanofluid. In addition, comparing these two metallic oxide nanofluids, the maximum amount of total entropy generation is 20% lower when CuO nanoparticles added to the base fluid instead of Al2O3.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Abbreviations

\(A\) :

Cross-sectional area of the tube (m2)

\(B\) :

Duty parameter

\(Be\) :

Bejan number

\(C_{\text{p}}\) :

Specific heat (J kg−1 K−1)

\(D\) :

Inside diameter of the tube (m)

\(d_{\text{p}}\) :

Nanoparticle diameter (nm)

\(f\) :

Friction factor

\(h\) :

Heat transfer coefficient (W m−2 K−1)

\(k\) :

Thermal conductivity (W m−1 K−1)

\(L\) :

Length of the tube (m)

\(\dot{m}\) :

Mass flow rate (kg s−1)

\(N_{\text{s}}\) :

Entropy generation number

\(Nu\) :

Nusselt number

\(Pr\) :

Prandtl number

\(Q\) :

Dimensionless heat flux

\(q\) :

Heat transfer per unit tube length (W m−1)

\(q''\) :

Heat flux (W m−2)

\(Re\) :

Reynolds number

\(R^{2}\) :

Coefficient of determination

\(\dot{S}_{g}^{\prime }\) :

Entropy generation rate per unit tube length (W m−1 K−1)

\(S_{{{\text{g}},{\text{h}}}}\) :

Entropy generation due to the heat transfer (W K−1)

\(S_{{{\text{g}},{\text{f}}}}\) :

Entropy generation due to the fluid friction (W K−1)

\(S_{{{\text{g}},{\text{tot}}}}\) :

Total entropy generation (W K−1)

\(St\) :

Stanton number

\(T\) :

Average flow temperature (K)

\(T_{0}\) :

Reference temperature, 273 K

\(\kappa\) :

Boltzmann constant, 1.381 × 10−23 (J K−1)

\(\mu\) :

Viscosity (Ns m−2)

\(\rho\) :

Density (kg m−3)

\(\varPhi\) :

Irreversibility distribution ratio

\(\phi\) :

Particle volumetric concentration (%)

B:

Brownian motion

bf:

Base fluid

nf:

Nanofluid

opt:

Optimum

p:

Particle

s:

Static

References

  1. Mwesigye A, Huan Z, Meyer JP. Thermodynamic optimisation of the performance of a parabolic trough receiver using synthetic oil-Al2O3 nanofluid. Appl Energy. 2015;156:398–412. https://doi.org/10.1016/j.apenergy.2015.07.035.

    Article  CAS  Google Scholar 

  2. Okati V, Behzadmehr A, Farsad S. Analysis of a solar desalinator (humidification–dehumidification cycle) including a compound system consisting of a solar humidifier and subsurface condenser using DoE. Desalination. 2016;397:9–21.

    Article  CAS  Google Scholar 

  3. Jamal-abadi MT, Zamzamian AH. Optimization of thermal conductivity of Al2O3 nanofluid by using ANN and GRG methods. Int J Nanosci Nanotechnol. 2013;9:177–84.

    Google Scholar 

  4. Minea AA, Lorenzini G. A numerical study on ZnO based nanofluids behavior on natural convection. Int J Heat Mass Transf. 2017;114:286–96. https://doi.org/10.1016/j.ijheatmasstransfer.2017.06.069.

    Article  CAS  Google Scholar 

  5. Minea AA. Comparative study of turbulent heat transfer of nanofluids: effect of thermophysical properties on figure-of-merit ratio. J Therm Anal Calorim. 2016;124:407–16.

    Article  CAS  Google Scholar 

  6. Ahmadi MH, Ahmadi MA, Nazari MA, Mahian O, Ghasempour R. A proposed model to predict thermal conductivity ratio of Al2O3/EG nanofluid by applying least squares support vector machine (LSSVM) and genetic algorithm as a connectionist approach. J Therm Anal Calorim. 2018;123456789:1–11. https://doi.org/10.1007/s10973-018-7035-z.

    Article  CAS  Google Scholar 

  7. Maganti LS, Dhar P. Consequences of flow configuration and nanofluid transport on entropy generation in parallel microchannel cooling systems. Int J Heat Mass Transf. 2017;109:555–63. https://doi.org/10.1016/j.ijheatmasstransfer.2017.02.036.

    Article  CAS  Google Scholar 

  8. Ibáñez G, López A, Pantoja J, Moreira J, Reyes JA. Optimum slip flow based on the minimization of entropy generation in parallel plate microchannels. Energy. 2013;50:143–9. https://doi.org/10.1016/j.energy.2012.11.036.

    Article  Google Scholar 

  9. Arabpour A, Karimipour A, Toghraie D, Akbari OA. Investigation into the effects of slip boundary condition on nanofluid flow in a double-layer microchannel. Netherlands: J Therm Anal Calorim. Springer; 2017. p. 1–17.

    Google Scholar 

  10. Safi MA, Ghozatloo A, Hamidi AA, Shariaty-Niassar M. Calculation of heat transfer coefficient of MWCNT-TiO2 nanofluid in plate heat exchanger. Iran Nanotechnol Soc 2014;10:153–62. http://www.ijnnonline.net/article_9092_10.html.

  11. Hosseinnezhad R, Akbari OA, Hassanzadeh Afrouzi H, Biglarian M, Koveiti A, Toghraie D. Numerical study of turbulent nanofluid heat transfer in a tubular heat exchanger with twin twisted-tape inserts. J Therm Anal Calorim. 2017. https://doi.org/10.1007/s10973-017-6900-5.

    Article  Google Scholar 

  12. Esfahani JA, Akbarzadeh M, Rashidi S, Rosen MA, Ellahi R. Influences of wavy wall and nanoparticles on entropy generation over heat exchanger plat. Int J Heat Mass Transf. 2017;109:1162–71. https://doi.org/10.1016/j.ijheatmasstransfer.2017.03.006.

    Article  CAS  Google Scholar 

  13. Bahiraei M, Berahmand M, Shahsavar A. Irreversibility analysis for flow of a non-Newtonian hybrid nanofluid containing coated CNT/Fe3O4 nanoparticles in a minichannel heat exchanger. Appl Therm Eng. 2017;125:1083–93. https://doi.org/10.1016/j.applthermaleng.2017.07.100.

    Article  CAS  Google Scholar 

  14. Delfani S, Karami M, Akhavan Bahabadi MA. Experimental investigation on performance comparison of nanofluid-based direct absorption and flat plate solar collectors. Int J Nano Dimens. 2015;7:85–96. http://www.ijnd.ir/article_15588_2444.html.

  15. Meibodi SS, Kianifar A, Mahian O, Wongwises S. Second law analysis of a nanofluid-based solar collector using experimental data. J Therm Anal Calorim. 2016;126:617–25.

    Article  CAS  Google Scholar 

  16. Gong X, Wang F, Wang H, Tan J, Lai Q, Han H. Heat transfer enhancement analysis of tube receiver for parabolic trough solar collector with pin fin arrays inserting. Sol Energy. 2017;144:185–202. https://doi.org/10.1016/j.solener.2017.01.020.

    Article  Google Scholar 

  17. MohammadZadeh P, Sokhansefat T, Kasaeian AB, Kowsary F, Akbarzadeh A. Hybrid optimization algorithm for thermal analysis in a solar parabolic trough collector based on nanofluid. Energy. 2015;82:857–64. https://doi.org/10.1016/j.energy.2015.01.096.

    Article  CAS  Google Scholar 

  18. Mahian O, Kianifar A, Sahin AZ, Wongwises S. Entropy generation during Al2O3/water nanofluid flow in a solar collector: effects of tube roughness, nanoparticle size, and different thermophysical models. Int J Heat Mass Transf. 2014;78:64–75. https://doi.org/10.1016/j.ijheatmasstransfer.2014.06.051.

    Article  CAS  Google Scholar 

  19. Liu ZH, Li YY. A new frontier of nanofluid research—application of nanofluids in heat pipes. Int J Heat Mass Transf. 2012;55:6786–97. https://doi.org/10.1016/j.ijheatmasstransfer.2012.06.086.

    Article  CAS  Google Scholar 

  20. Farzaneh-Gord M, Ameri H, Arabkoohsar A. Tube-in-tube helical heat exchangers performance optimization by entropy generation minimization approach. Appl Therm Eng. 2016;108:1279–87. https://doi.org/10.1016/j.applthermaleng.2016.08.028.

    Article  Google Scholar 

  21. Gutiérrez F, Méndez F. Entropy generation minimization for the thermal decomposition of methane gas in hydrogen using genetic algorithms. Energy Convers Manag. 2012;55:1–13.

    Article  CAS  Google Scholar 

  22. Ellahi R, Hassan M, Zeeshan A, Khan AA. The shape effects of nanoparticles suspended in HFE-7100 over wedge with entropy generation and mixed convection. Appl Nanosci. 2015;6:1–11. https://doi.org/10.1007/s13204-015-0481-z.

    Article  CAS  Google Scholar 

  23. Siavashi M, Jamali M. Heat transfer and entropy generation analysis of turbulent flow of TiO2-water nanofluid inside annuli with different radius ratios using two-phase mixture model. Appl Therm Eng. 2016;100:1149–60. https://doi.org/10.1016/j.applthermaleng.2016.02.093.

    Article  CAS  Google Scholar 

  24. Shalchi-Tabrizi A, Seyf HR. Analysis of entropy generation and convective heat transfer of Al2O3 nanofluid flow in a tangential micro heat sink. Int J Heat Mass Transf. 2012;55:4366–75. https://doi.org/10.1016/j.ijheatmasstransfer.2012.04.005.

    Article  CAS  Google Scholar 

  25. Bianco V, Manca O, Nardini S. Performance analysis of turbulent convection heat transfer of Al2O3 water-nanofluid in circular tubes at constant wall temperature. Energy. 2014;77:403–13. https://doi.org/10.1016/j.energy.2014.09.025.

    Article  CAS  Google Scholar 

  26. Singh PK, Anoop KB, Sundararajan T, Das SK. Entropy generation due to flow and heat transfer in nanofluids. Int J Heat Mass Transf. 2010;53:4757–67. https://doi.org/10.1016/j.ijheatmasstransfer.2010.06.016.

    Article  CAS  Google Scholar 

  27. Torabi M, Torabi M, Ghiaasiaan SM, Peterson GP. The effect of Al2O3-water nanofluid on the heat transfer and entropy generation of laminar forced convection through isotropic porous media. Int J Heat Mass Transf. 2017;111:804–16. https://doi.org/10.1016/j.ijheatmasstransfer.2017.04.041.

    Article  CAS  Google Scholar 

  28. Mwesigye A, Huan Z. Thermodynamic analysis and optimization of fully developed turbulent forced convection in a circular tube with water-Al2O3 nanofluid. Int J Heat Mass Transf. 2015;89:694–706. https://doi.org/10.1016/j.ijheatmasstransfer.2015.05.099.

    Article  CAS  Google Scholar 

  29. Ghasemi SE, Ranjbar AA. Thermal performance analysis of solar parabolic trough collector using nanofluid as working fluid: a CFD modelling study. J Mol Liq. 2016;222:159–66. https://doi.org/10.1016/j.molliq.2016.06.091.

    Article  CAS  Google Scholar 

  30. Oullette WR, Bejan A. Conservation of available work (exergy) by using promoters of swirl flow in forced convection heat transfer. Energy. 1980;5:587–96.

    Article  CAS  Google Scholar 

  31. Paoletti S, Rispoli F, Sciubba E. Calculation of exergetic losses in compact heat exchanger passages. ASME AES. 1989;10:21–9.

    Google Scholar 

  32. Pascale S, Gregory JM, Ambaum M, Tailleux R. Climate entropy budget of the HadCM3 atmosphere–ocean general circulation model and of FAMOUS, its low-resolution. Clim Dyn. 2010;10:125–39.

    Google Scholar 

  33. Vajjha RS. Measurements of thermophysical properties of nanofluids and computation of heat transfer characteristics. University of Alaska Fairbanks; 2008.

  34. Lajos K. International news No uvelles in terna tionales. 1979;56–7.

  35. Al-Ansary H, Zeitoun O. Numerical study of conduction and convection heat losses from a half-insulated air-filled annulus of the receiver of a parabolic trough collector. Sol Energy. 2011;85:3036–45. https://doi.org/10.1016/j.solener.2011.09.002.

    Article  Google Scholar 

  36. Bellos E, Tzivanidis C, Tsimpoukis D. Thermal enhancement of parabolic trough collector with internally finned absorbers. Sol Energy. 2017;157:514–31. https://doi.org/10.1016/j.solener.2017.08.067.

    Article  Google Scholar 

  37. Vajjha RS, Das DK. Experimental determination of thermal conductivity of three nanofluids and development of new correlations. Int J Heat Mass Transf. 2009;52:4675–82. https://doi.org/10.1016/j.ijheatmasstransfer.2009.06.027.

    Article  CAS  Google Scholar 

  38. Sahoo BC. Measurement of rheological and thermal properties and the freeze-thaw characteristics of nanofluids. University of Alaska Fairbanks; 2008.

  39. Koo J, Kleinstreuer C. A new thermal conductivity model for nanofluids. J Nanoparticle Res. 2004;6:577–88.

    Article  Google Scholar 

  40. Vajjha RS, Das DK, Kulkarni DP. Development of new correlations for convective heat transfer and friction factor in turbulent regime for nanofluids. Int J Heat Mass Transf. 2010;53:4607–18. https://doi.org/10.1016/j.ijheatmasstransfer.2010.06.032.

    Article  CAS  Google Scholar 

  41. Mwesigye A, Meyer JP. Optimal thermal and thermodynamic performance of a solar parabolic trough receiver with different nanofluids and at different concentration ratios. Appl Energy. 2017;193:393–413. https://doi.org/10.1016/j.apenergy.2017.02.064.

    Article  CAS  Google Scholar 

  42. Menbari A, Alemrajabi AA, Rezaei A. Heat transfer analysis and the effect of CuO/Water nanofluid on direct absorption concentrating solar collector. Appl Therm Eng. 2016;104:176–83. https://doi.org/10.1016/j.applthermaleng.2016.05.064.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Mechanical Engineering, Shahrood University of Technology, Shahrood, Iran

    Behnam Mohseni-Gharyehsafa, V. Okati, Mahmood Farzaneh-Gord & Mohammad Hossein Ahmadi

  2. Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran

    Amir Ebrahimi-Moghadam

  3. Faculty of Marine Engineering, Chabahar Maritime University, Chabahar, Iran

    V. Okati

  4. Dipartimento di Ingegneria e Architettura, Università degli Studi di Parma, Parco Area delle Scienze 181/A, 43124, Parma, Italy

    Giulio Lorenzini

Authors
  1. Behnam Mohseni-Gharyehsafa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amir Ebrahimi-Moghadam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. Okati
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mahmood Farzaneh-Gord
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mohammad Hossein Ahmadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Giulio Lorenzini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Amir Ebrahimi-Moghadam or Mohammad Hossein Ahmadi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mohseni-Gharyehsafa, B., Ebrahimi-Moghadam, A., Okati, V. et al. Optimizing flow properties of the different nanofluids inside a circular tube by using entropy generation minimization approach. J Therm Anal Calorim 135, 801–811 (2019). https://doi.org/10.1007/s10973-018-7276-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10973-018-7276-x

Keywords

Search

Navigation