Knowledge discovery from nanofluids thermal properties and heat exchange data set using intelligent technique

Abstract

Nano technology has shown a rapid development in various engineering field and it has the capability of reducing the sizes and by means of that enhancing the efficiency. This technology facilitated to develop nano sized particles and aid to the development of nano-fluids. Nano-fluids are a new group of fluids which comprise of nano sized particles dispersed in the conventional base fluids. The invention of nano-fluids is mainly to improve the thermal efficiency in the heat exchanger systems. Conventional base fluids have possess lower thermal conductivity which leads to inefficiency of heat exchanger systems. Inclusion of nano sized solid particles in the base fluid improves the thermal conductivity of the fluid. Thermo physical properties of nano-fluids are the most significant. The properties are thermal conductivity, viscosity, thermal diffusivity and convective heat transfer efficient. Due to these exceptional properties, nano-fluids are utilized in various engineering fields especially in mechanical engineering applications and also in cosmetic applications. The most important thermo physical properties of nano-fluids are thermal conductivity and viscosity. These properties of nano-fluids depend upon various factors such as particle volume fraction, size of particle, shape of particle, material of particle, base fluid, temperature, pH values, shear rate and surfactants. Many mathematical models are developed to predict the thermal behavior of the nano-fluids. Various researchers conducted experiments and investigated the behavior of the nano-fluids. It needs more test runs and it is tiresome.Moreover there exist least correlations between the theoretical models and experimental values. Soft computing tools using artificial intelligence techniques are capable of creating intelligence in machines by using Mathand#8223;s algorithm and learning the data model automatically by itself with the existing knowledge. Knowledge discovery from the existing data and predicting the future outcome is the proficiency of soft comput