Experimental and comparative theoretical study of thermal conductivity of MWCNTs-kapok seed oil-based nanofluid

  • Ahmad Mukhtar
  • , Sidra Saqib
  • , Fatma Safdar
  • , Ayesha Hameed
  • , Sikander Rafiq
  • , Nurhayati Binti Mellon*
  • , Rabia Amen
  • , Muhammad Saad Khan
  • , Sami Ullah
  • , Muhammed Ali Assiri
  • , Muhammad Babar
  • , Mohamad Azmi Bustam
  • , Wajid Ur Rehman
  • , Z. M.A. Merican
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Despite the significant potential of nanofluids in energy storage applications, the experimental determination of thermophysical properties is relatively costly and time-consuming. Therefore, the modeling techniques can be used for the accurate estimation of thermo-physical behavior. The predictive models are useful for the understanding of thermo-physical behavior. Due to restrictions on classical models, there is a need to develop more reliable models to simulate the thermophysical behavior of nanofluids. This paper deals with the synthesis and experimental thermal conductivity measurement of the multi-walled carbon nanotubes (MWCNTs)-Kapok seed oil nanofluid. Additionally, two new correlations based on multiple non-linear regression analysis along well as dimensionless analysis are proposed to estimate thermal conductivity with high precision compared to the classical models. Based on the statistical analysis, the prediction accuracy of the proposed model was ranked. Finally, the sensitivity analysis has been carried out in combination with the residual analysis to assure the accuracy of the model parameters of both proposed models and adequacy of estimated values of model parameters, respectively. The results revealed the global minimum values for all parameters at 0% perturbations indicating that the model parameters were estimated with high accuracy and adequacy.

Original languageEnglish
Article number104402
JournalInternational Communications in Heat and Mass Transfer
Volume110
DOIs
StatePublished - Jan 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

Keywords

  • Artificial neural network
  • Dimensionless group analysis
  • Kapok seed oil
  • Multi-walled carbon nanotubes
  • Nanofluid
  • Thermal conductivity

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • General Chemical Engineering
  • Condensed Matter Physics

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