期刊
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
卷 118, 期 1, 页码 287-294出版社
SPRINGER
DOI: 10.1007/s10973-014-4002-1
关键词
Neural network; Nanofluids; Thermal conductivity; Particle size
资金
- Thailand Research Fund
- National Science and Technology Development Agency
- National Research University Project
The application of nanofluids in energy systems is developing day by day. Before using a nanofluid in an energy system, it is necessary to measure the properties of nanofluids. In this paper, first the results of experiments on the thermal conductivity of MgO/ethylene glycol (EG) nanofluids in a temperature range of 25-55 A degrees C and volume concentrations up to 5 % are presented. Different sizes of MgO nanoparticles are selected to disperse in EG, including 20, 40, 50, and 60 nm. Based on the results, an empirical correlation is presented as a function of temperature, volume fraction, and nanoparticle size. Next, the model of thermal conductivity enhancement in terms of volume fraction, particle size, and temperature was developed via neural network based on the measured data. It is observed that neural network can be used as a powerful tool to predict the thermal conductivity of nanofluids.
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