Prediction of thermal conductivity of alumina water-based nanofluids by artificial neural networks
Authors:
- M.A. ArianaMAM.A. Ariana
- B. VaferiBVB. Vaferi
- G. KarimiGKG. Karimi
- 1 July 2015
- journal article
- Published by Elsevier in Powder Technology
- Vol. 278, 1-10
Abstract
No abstract availableThis publication has 41 references indexed in Scilit:
- Modeling the influence of a process control agent on the properties of metal matrix composite powders using artificial neural networksPowder Technology, 2012
- Application of Artificial Neural Network (ANN) for the prediction of thermal conductivity of oxide–water nanofluidsNano Energy, 2012
- Modeling thermal conductivity augmentation of nanofluids using diffusion neural networksInternational Journal of Thermal Sciences, 2011
- The effect of alumina/water nanofluid particle size on thermal conductivityApplied Thermal Engineering, 2010
- New temperature dependent thermal conductivity data for water-based nanofluidsInternational Journal of Thermal Sciences, 2009
- Study of thermal conductivity of nanofluids for the application of heat transfer fluidsThermochimica Acta, 2007
- Effect of interfacial nanolayer on the effective thermal conductivity of nanoparticle-fluid mixtureInternational Journal of Heat and Mass Transfer, 2005
- Aggregation structure and thermal conductivity of nanofluidsAIChE Journal, 2003
- Neural networks for predicting thermal conductivity of bakery productsJournal of Food Engineering, 2002
- Thermal Conductivity of Nanoparticle - Fluid MixtureJournal of Thermophysics and Heat Transfer, 1999