Application of Artificial Neural Network (ANN) for the prediction of thermal conductivity of oxide-water nanofluids

作者：Longo Giovanni A^*; Zilio Claudio; Ceseracciu Elena; Reggiani Monica

来源：Nano Energy, 2012, 1(2): 290-296.

DOI：10.1016/j.nanoen.2011.11.007

• Nanofluids
• Thermal conductivity
• Artificial Neural Network

This paper presents a 3-input and a 4-input Artificial Neural Network (ANN) model for the prediction of the thermal conductivity of oxide-water nanofluids. Both models account for the effect of temperature, nanoparticle volume fraction, and nanoparticle thermal conductivity, whereas the 4-input model also considers the effect of nanoparticle cluster average size. The models have been trained on a set of data obtained by the present authors and tested both with cross-validation and on data coming from other authors. Both models show a reasonable agreement in predicting experimental data, even if the 4-input model exhibits better performance. The inclusion of the cluster average size within the input variables improves the predicting performance of the ANN nanofluid thermal conductivity model; however, this parameter is usually missing from data presented in literature. The characteristic parameters of the presented ANN models are fully reported in the paper.

• 出版日期2012-3