Advertisement

Journal of the Iranian Chemical Society

, Volume 16, Issue 12, pp 2629–2637 | Cite as

A comparative study in the prediction of thermal conductivity enhancement of nanofluids using ANN-MLP, ANN-RBF, ANFIS, and GMDH methods

  • Majid MoosaviEmail author
  • Khadijeh Firoozi Rad
  • Azadeh Daneshvar
Original Paper
  • 39 Downloads

Abstract

In this work, four types of data mining methods, namely adaptive neuro-fuzzy inference system, artificial neural network—multilayer perceptron algorithm (ANN-MLP), artificial neural network—radial basis function algorithm (ANN-RBF), and group method of data handling (GMDH) have been used to predict the enhancement of the relative thermal conductivity of a wide range of nanofluids with different base fluids and nanoparticles. The total number of experimental data used in this work is 483 from 18 different nanofluids. The input parameters are thermal conductivity of base fluid and nanoparticles, volume fraction percent, the average size of nanoparticles, and temperature. Although the results showed that all four models are in relatively good agreement with experimental data, the ANFIS method is the best. The average absolute relative deviations (AARD%) between the experimental data and those of obtained using ANFIS, ANN-MLP, ANN-RBF, and GMDH methods were calculated as 2.7, 2.8, 4.2, and 4.3, respectively, for the test sets and as 1.1, 2.4, 3.9, and 4.5, respectively, for the training sets. Comparison between the predictions of the proposed ANN-MLP, ANN-RBF, ANFIS, and GMDH models and those predicted by traditional models, namely Maxwell and Bruggeman models showed that much better agreements can be obtained using the four models especially ANFIS model. Accordingly, the ANFIS method can able us to predict the relative thermal conductivity of new nanofluids in different conditions with good accuracy.

Keywords

Nanofluids Thermal conductivity Artificial neural network (ANN) Adaptive neuro-fuzzy inference system (ANFIS) Radial basis function (RBF) Group method of data handling (GMDH) 

Notes

Acknowledgements

This research was supported by the Research Council of University of Isfahan. The authors also thank Dr. Vahid Moosavi for his assistance and valuable comments on the used algorithms.

References

  1. 1.
    X.Q. Wang, A.S. Mujumdar, Int. J. Therm. Sci. 46, 1–19 (2007)CrossRefGoogle Scholar
  2. 2.
    S. Chol, ASME Publ. Fed. 231, 99–106 (1995)Google Scholar
  3. 3.
    C. Kleinstreuer, Y. Feng, Nanoscale Res. Lett. 6, 1–13 (2011)Google Scholar
  4. 4.
    W. Yu, D.M. France, J.L. Routbort, S.U. Choi, Heat Transf. Eng. 29, 432–460 (2008)Google Scholar
  5. 5.
    W. Yu, S. Choi, J. Nanopart. Res. 6, 355–361 (2004)Google Scholar
  6. 6.
    W. Yu, S. Choi, J.Nanopart. Res. 5, 167–171 (2003)Google Scholar
  7. 7.
    Q.-Z. Xue, Phys. Lett. A 307, 313–317 (2003)Google Scholar
  8. 8.
    B.-X. Wang, L.-P. Zhou, X.-F. Peng, Int. J. Heat Mass Transf. 46, 2665–2672 (2003)Google Scholar
  9. 9.
    J. Maxwell, A Treatise on Electricity and Magnetism vol. 1, chap. 9 (Clarendon, Oxford, 1891)Google Scholar
  10. 10.
    R. Hamilton, O. Crosser, Ind. Eng. Chem. Fundam. 1, 187–191 (1962)Google Scholar
  11. 11.
    V.D. Bruggeman, Ann. Phys. 416, 636–664 (1935)Google Scholar
  12. 12.
    D.J. Jeffrey, Royal Soc. 355–367 (1973)Google Scholar
  13. 13.
    R. Davis, Int. J. Thermophys. 7, 609–620 (1986)Google Scholar
  14. 14.
    V. Vijayan, A. Ravikumar, Int. J. Comput. Appl. 95 (2014)Google Scholar
  15. 15.
    M.H. Esfe, H. Rostamian, D. Toghraie, W.-M. Yan, J. Therm. Anal. Calorim. 126, 643–648 (2016)Google Scholar
  16. 16.
    M.H. Esfe, M.R.H. Ahangar, D. Toghraie, M.H. Hajmohammad, H. Rostamian, H. Tourang, J. Therm. Anal. Calorim. 126, 837–843 (2016)Google Scholar
  17. 17.
    M. Bahiraei, M. Hangi, Mater. Chem. Phys. 181, 333–343 (2016)Google Scholar
  18. 18.
    B. Vaferi, F. Samimi, E. Pakgohar, D. Mowla, Powder Technol. 267, 1–10 (2014)Google Scholar
  19. 19.
    M.H. Esfe, S. Saedodin, M. Bahiraei, D. Toghraie, O. Mahian, S. Wongwises, J. Therm. Anal. Calorim. 118, 287–294 (2014)Google Scholar
  20. 20.
    H.H. Balla, S. Abdullah, W.M.F. WanMahmood, M.A. Razzaq, R. Zulkifli, K. Sopian, Res. Chem. Intermed. 39, 2801–2815 (2013)Google Scholar
  21. 21.
    S. Aminossadati, A. Kargar, B. Ghasemi, Int. J. Therm. Sci. 52, 102–111 (2012)Google Scholar
  22. 22.
    M. Mehrabi, M. Sharifpur, J.P. Meyer, Int. Commun. Heat Mass Transf. 39, 971–977 (2012)Google Scholar
  23. 23.
    A. Lotfizadeh, Commun. ACM 37, 77–85 (1994)Google Scholar
  24. 24.
    M.T. Hagan, H.B. Demuth, M.H. Beale, (University of Colorado Bookstore, Boulder, 2002Google Scholar
  25. 25.
    A.G. Ivakhnenko, Soviet Autom. Control 13, 43–55 (1968)Google Scholar
  26. 26.
    A.G. Ivakhnenko, IEEE Trans. Syst. Man Cybern. 1, 364–378 (1971)Google Scholar
  27. 27.
    S.J. Farlow, Am. Stat. 35, 210–215 (1981)Google Scholar
  28. 28.
    A.G. Ivakhnenko, G.A. Ivakhnenko, Pattern Recogn. Image Anal. 5, 527–535 (1995)Google Scholar
  29. 29.
    D.S. Broomhead, D. Lowe, Complex Syst. 2, 321–355 (1988)Google Scholar
  30. 30.
    L. Yu, K.K. Lai, S. Wang, Neurocomputing 71, 3295–3302 (2008)Google Scholar
  31. 31.
    S.A. Iliyas, M. Elshafei, M.A. Habib, A.A. Adeniran, Control Eng. Pract. 21, 962–970 (2013)Google Scholar
  32. 32.
    S. Chen, C.F.N. Cowan, P.M. Grant, IEEE Trans. Neural Netw. 2, 302–309 (1991)PubMedGoogle Scholar
  33. 33.
    M. Hojjat, S.G. Etemad, R. Bagheri, J. Thibault, Int. J. Heat Mass Transf. 54, 1017–1023 (2011)Google Scholar
  34. 34.
    M. Chandrasekar, S. Suresh, A.C. Bose, Exp. Therm. Fluid Sci. 34, 210–216 (2010)Google Scholar
  35. 35.
    K. Anoop, T. Sundararajan, S.K. Das, Int. J. Heat Mass Transf. 52, 2189–2195 (2009)Google Scholar
  36. 36.
    S. Murshed, K. Leong, C. Yang, Int. J. Therm. Sci. 47, 560–568 (2008)Google Scholar
  37. 37.
    W.-Q. Lu, Q.-M. Fan, Eng. Anal. Bound Elem. 32, 282–289 (2008)Google Scholar
  38. 38.
    D.-H. Yoo, K. Hong, H.-S. Yang, Thermochim. Acta 455, 66–69 (2007)Google Scholar
  39. 39.
    C.H. Li, G. Peterson, J. Appl. Phys. 101, 44312 (2007)Google Scholar
  40. 40.
    C.H. Li, G. Peterson, J. Appl. Phys. 99, 084314 (2006)Google Scholar
  41. 41.
    C.H. Chon, K.D. Kihm, S.P. Lee, S.U. Choi, Appl. Phys. Lett. 87, 3107 (2005)Google Scholar
  42. 42.
    D. Wen, Y. Ding, Int. J. Heat Mass Transf. 47, 5181–5188 (2004)Google Scholar
  43. 43.
    S.K. Das, N. Putra, P. Thiesen, W. Roetzel, J. Heat Transf. 125, 567–574 (2003)Google Scholar
  44. 44.
    H. Xie, J. Wang, T. Xi, Y. Liu, F. Ai, Q. Wu, J. Appl. Phys. 91, 4568–4572 (2002)Google Scholar
  45. 45.
    X. Wang, X. Xu, S.U.S. Choi, J. Thermophys. Heat Transf. 13, 474–480 (1999)Google Scholar
  46. 46.
    S. Lee, S.-S. Choi, S. Li, J. Eastman, J. Heat Transf. 121, 280–289 (1999)Google Scholar
  47. 47.
    D. Lee, J.-W. Kim, B.G. Kim, J. Phys. Chem. B 110, 4323–4328 (2006)PubMedGoogle Scholar
  48. 48.
    W. Duangthongsuk, S. Wongwises, Int. J. Heat Mass Transf. 53, 334–344 (2010)Google Scholar
  49. 49.
    A. Turgut, I. Tavman, M. Chirtoc, H. Schuchmann, C. Sauter, S. Tavman, Int. J. Thermophys. 30, 1213–1226 (2009)Google Scholar
  50. 50.
    W. Duangthongsuk, S. Wongwises, Exp. Therm. Fluid Sci. 33, 706–714 (2009)Google Scholar
  51. 51.
    H. Chen, S. Witharana, Y. Jin, C. Kim, Y. Ding, Particuology 7, 151–157 (2009)Google Scholar
  52. 52.
    D. Wen, Y. Ding, Int. J. Heat Fluid Flow 26, 855–864 (2005)Google Scholar
  53. 53.
    S. Murshed, K. Leong, C. Yang, Int. J. Therm. Sci. 44, 367–373 (2005)Google Scholar
  54. 54.
    S.W. Lee, S.D. Park, S. Kang, I.C. Bang, J.H. Kim, Int. J. Heat Mass Transf. 54, 433–438 (2011)Google Scholar
  55. 55.
    H.-Q. Xie, J.-C. Wang, T.-G. Xi, Y. Liu, Int. J. Thermophys. 23, 571–580 (2002)Google Scholar
  56. 56.
    M.-S. Liu, M.C.-C. Lin, C. Tsai, C.-C. Wang, Int. J. Heat Mass Transf. 49, 3028–3033 (2006)Google Scholar
  57. 57.
    Y. Xuan, Q. Li, Int. J. Heat Fluid Flow 21, 58–64 (2000)Google Scholar
  58. 58.
    H.U. Kang, S.H. Kim, J.M. Oh, Exp. Heat Transf. 19, 181–191 (2006)Google Scholar
  59. 59.
    H. Chen, Y. Ding, A. Lapkin, X. Fan, 11, 1513–1520 (2009)Google Scholar
  60. 60.
    H. Chen, Y. Ding, Y. He, C. Tan, Chem. Phys. Lett. 444, 333–337 (2007)Google Scholar
  61. 61.
    J. Garg, B. Poudel, M. Chiesa, J. Gordon, J. Ma, J. Wang, Z. Ren, Y. Kang, H. Ohtani, J. Nanda, J. Appl. Phys. 103, 074301 (2008)Google Scholar
  62. 62.
    J.A. Eastman, S. Choi, S. Li, W. Yu, L. Thompson, Appl. Phys. Lett. 78, 718–720 (2001)Google Scholar
  63. 63.
    T.-K. Hong, H.-S. Yang, C. Choi, J. Appl. Phys. 97, 064311 (2005)Google Scholar
  64. 64.
    J.C. Maxwell, (Clarendon press, 1881)Google Scholar

Copyright information

© Iranian Chemical Society 2019

Authors and Affiliations

  1. 1.Department of ChemistryUniversity of IsfahanIsfahanIran

Personalised recommendations