Modelling and measuring the thermal conductivity of multi-metallic Zn/Cu nanofluid

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

A metallic nanofluid is a suspension of metallic nanoparticles in a base fluid. Multi-metallic nanoparticles are a combination of two or more types of metallic particles. Such multi-metallic nanoparticles were suspended in water using an ultrasonic vibrator for different total volume fractions and different ratios of metallic/metallic nanoparticles. A transient hot wire setup was built to measure the thermal conductivity of the nanofluid at different temperatures. The experimental results were in good agreement with the results in the literature. Then, the experimental results were used as input data for an adaptive neural fuzzy inference system (ANFIS) to predict the thermal conductivity of the multi-metallic nanofluid. The maximum deviation between the ANFIS results and experimental measurements was 1 %. The predicted results and the experimental data were compared with other models. The ANFIS model was found to have good ability to predict the thermal conductivity of the multi-metallic nanofluid over the range of the experimental results.

Original languageEnglish
Pages (from-to)2801-2815
Number of pages15
JournalResearch on Chemical Intermediates
Volume39
Issue number6
DOIs
Publication statusPublished - Jul 2013

Fingerprint

Thermal conductivity
Fuzzy inference
Nanoparticles
Vibrators
Volume fraction
Suspensions
Ultrasonics
Wire
Fluids
Water
Temperature

Keywords

  • ANFIS application
  • Multi-metallic nanofluid
  • Thermal conductivity enhancement

ASJC Scopus subject areas

  • Chemistry(all)

Cite this

@article{f818d029cb1d46acaf5d8fc565857543,
title = "Modelling and measuring the thermal conductivity of multi-metallic Zn/Cu nanofluid",
abstract = "A metallic nanofluid is a suspension of metallic nanoparticles in a base fluid. Multi-metallic nanoparticles are a combination of two or more types of metallic particles. Such multi-metallic nanoparticles were suspended in water using an ultrasonic vibrator for different total volume fractions and different ratios of metallic/metallic nanoparticles. A transient hot wire setup was built to measure the thermal conductivity of the nanofluid at different temperatures. The experimental results were in good agreement with the results in the literature. Then, the experimental results were used as input data for an adaptive neural fuzzy inference system (ANFIS) to predict the thermal conductivity of the multi-metallic nanofluid. The maximum deviation between the ANFIS results and experimental measurements was 1 {\%}. The predicted results and the experimental data were compared with other models. The ANFIS model was found to have good ability to predict the thermal conductivity of the multi-metallic nanofluid over the range of the experimental results.",
keywords = "ANFIS application, Multi-metallic nanofluid, Thermal conductivity enhancement",
author = "Balla, {Hyder H.} and Shahrir Abdullah and {Wan Mahmood}, {Wan Mohd Faizal} and {Abdul Razzaq}, M. and Rozli Zulkifli and Kamaruzzaman Sopian",
year = "2013",
month = "7",
doi = "10.1007/s11164-012-0799-z",
language = "English",
volume = "39",
pages = "2801--2815",
journal = "Research on Chemical Intermediates",
issn = "0922-6168",
publisher = "Springer Netherlands",
number = "6",

}

TY - JOUR

T1 - Modelling and measuring the thermal conductivity of multi-metallic Zn/Cu nanofluid

AU - Balla, Hyder H.

AU - Abdullah, Shahrir

AU - Wan Mahmood, Wan Mohd Faizal

AU - Abdul Razzaq, M.

AU - Zulkifli, Rozli

AU - Sopian, Kamaruzzaman

PY - 2013/7

Y1 - 2013/7

N2 - A metallic nanofluid is a suspension of metallic nanoparticles in a base fluid. Multi-metallic nanoparticles are a combination of two or more types of metallic particles. Such multi-metallic nanoparticles were suspended in water using an ultrasonic vibrator for different total volume fractions and different ratios of metallic/metallic nanoparticles. A transient hot wire setup was built to measure the thermal conductivity of the nanofluid at different temperatures. The experimental results were in good agreement with the results in the literature. Then, the experimental results were used as input data for an adaptive neural fuzzy inference system (ANFIS) to predict the thermal conductivity of the multi-metallic nanofluid. The maximum deviation between the ANFIS results and experimental measurements was 1 %. The predicted results and the experimental data were compared with other models. The ANFIS model was found to have good ability to predict the thermal conductivity of the multi-metallic nanofluid over the range of the experimental results.

AB - A metallic nanofluid is a suspension of metallic nanoparticles in a base fluid. Multi-metallic nanoparticles are a combination of two or more types of metallic particles. Such multi-metallic nanoparticles were suspended in water using an ultrasonic vibrator for different total volume fractions and different ratios of metallic/metallic nanoparticles. A transient hot wire setup was built to measure the thermal conductivity of the nanofluid at different temperatures. The experimental results were in good agreement with the results in the literature. Then, the experimental results were used as input data for an adaptive neural fuzzy inference system (ANFIS) to predict the thermal conductivity of the multi-metallic nanofluid. The maximum deviation between the ANFIS results and experimental measurements was 1 %. The predicted results and the experimental data were compared with other models. The ANFIS model was found to have good ability to predict the thermal conductivity of the multi-metallic nanofluid over the range of the experimental results.

KW - ANFIS application

KW - Multi-metallic nanofluid

KW - Thermal conductivity enhancement

UR - http://www.scopus.com/inward/record.url?scp=84879461585&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84879461585&partnerID=8YFLogxK

U2 - 10.1007/s11164-012-0799-z

DO - 10.1007/s11164-012-0799-z

M3 - Article

AN - SCOPUS:84879461585

VL - 39

SP - 2801

EP - 2815

JO - Research on Chemical Intermediates

JF - Research on Chemical Intermediates

SN - 0922-6168

IS - 6

ER -