Modeling of effective properties of nanofluids and numerical analysis of heat transfer around a circular cylinder

Abstract

1 Introduction Ultrahigh-performance cooling has become the prime requirement in several industrial technologies, due to the popular trend of miniaturization. Miniature devices with high output capacities are subjected to high density heat fluxes. Hence, efficient cooling becomes inevitable to assure the performance and reliability of many industrial devices. However, inherently low thermal conductivity of heat transfer fluids is a major limiting factor to build efficient, high performance cooling systems. In general, thermal conductivities of liquids are very less when compared to solids. For instance, copper has almost 700 times higher thermal conductivity than water. Hence, for more than a century, since the initiating attempt of Maxwell [1], several engineers and scientists have made lot of attempts to enhance the thermal conductivity of liquids by dispersing micro/millimeter sized solid particles. However, these micro/millimeter sized solid-liquid suspensions have many problems such as poor stability, blockage and wear of flow passages, low increase in thermal conductivity and comparatively higher increase in pressure drop, etc. Recent advancements in the field of surface technology enabled the production of solid particles in the order of nanometers. This has led to theconcept and emergence of nanofluids. S.U.S. Choi [2] revived the idea of Maxwell by suspending solid nanoparticles in liquids to increase the thermal conductivity. Nanofluids are engineered suspensions of fine nanoparticles in traditional heat transfer fluids. They are more stable than micro/millimeter suspensions and do not cause any blockage or wear in flow passages. Thus, nanofluids have emerged as a new class of nanotechnology based coolants, which possibly can enhance the heat transfer rates without much increase in pumping power.2 Motivation Despite the recent advances, there are several unsolved problems in the field of nanofluid research. This presents new opportunities and challenges for engineers and scientists. Nanofluid research could result in a major breakthrough in developing the coolants of future for several engineering applications. Better control over the heat transfer capability leads to greater energy efficiency, smaller and lighter cooling systems, lower operating costs and a cleaner environment. Two key research issues in the field of nanofluids are namely (i) uncertainties in the predictionof effective properties of nanofluids and (ii) choice of a proper numerical technique for modeling flow and heat transfer of nanofluids. 2.1 Uncertainties in effective properties of nanofluids Nanofluids are complex systems of fine nano-sized particles suspended in basefluids. Effective properties of nanofluids greatly depend on micro-structural details such as component properties, component volume fraction, particle shape and size, particle distribution, particle motion and interfacial effects. Furthermore, anomalous increase in thermal conductivity of nanofluids is attributed to novel mechanisms such as Brownian motion, interfacial layer formation and aggregation. Though several researchers have contributed to this basic research on effective properties of nanofluids and several theoretical models have been proposed, still there exists an uncertainty in prediction of nanofluid properties. Hence, more comprehensive models are required to develop better understanding and explain the altered effective properties of nanofluids.2.2 Choice of proper numerical approach to model nanofluid flow and heat transfer As we know, nanofluids are mixtures of continuous phase called basefluid and a discontinuous phase of solid particles. This heterogeneous nature of nanofluids brings in several numerical approaches to model the flow and heat transfer of nanofluids. But, majority of the numerical studies on nanofluid flow and heat transfer, available in literature, follow a Single Phase Modeling (SPM) approach, due to its simplicity. In SPM, nanofluids are assumed to be homogeneous liquids with effective properties. These effective properties are calculated using theoretical models, which already have an uncertainty in them. This leads to an uncertainty in the results of flow and heat transfer of nanofluids, obtained by SPM. There are other numerical approaches such as Multi Phase Modeling (MPM) and Discrete Phase Modeling (DPM) which consider the heterogeneous nature of the nanofluids. They are more realistic than SPM and also account for other mechanisms seen in nanofluids such as Brownian motion and thermophoresis. But, the potential of MPM and DPM to model the flow and heat transfer of nanofluids is comparatively less explored. This gives an excellent opportunity to researchers in the field of applied research of nanofluids to assess the performance of different numerical approaches in simulating nanofluid flow and heat transfer.