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This study presents the application of a modified single-phase method by thermal dispersion model incorporating heterogeneous distribution of nanoparticle concentration for evaluating thermal performance of a nanofluid in a circular porous metal foam tube. Numerical approach was conducted for Re = 200–1000, mean concentration of 0.5–2%, and metal foam porosity of 0.7–0.9. It is observed that the predicted data by application of the thermal dispersion approach are in satisfactory agreement with those obtained experimentally, whereas applying the general homogeneous model results in an underestimation. The results reveal that the heterogeneity of the concentration distribution is directly proportional to nanoparticle mean concentration, Reynolds number, and the metal foam porosity. The velocity and temperature profiles at a cross section have been found to be flatter in dispersion model compared to those obtained from the homogeneous model. Furthermore, it is achieved that the Nusselt number varies directly relative to mean concentration and Reynolds number, whereas it inversely alters relative to the porosity. This reduction is found to be more profound at lower porosities. [ABSTRACT FROM AUTHOR]

In this work, the evaluation of thermal conductivity of MnFe 2 O 4 /water nanofluids in attendance of magnetic field is conducted. The MnFe 2 O 4 /water is synthesized and prepared in different nanoparticles concentrations, from 0.25% to 3%. The thermal conductivity of nanofluids has been determined at various nanofluid concentrations and temperatures with and without magnetic field. It is found that the thermal conductivity of nanofluid remarkably improves with augmentation of solid volume fraction. Moreover, by incrementing the nanofluid temperature, the thermal conductivity improves under no magnetic field, while it decreases at higher temperatures in attendance of magnetic field. The highest thermal conductivity improvement is achieved 26.4% at 60 °C and 3 vol.% of nanoparticles under no magnetic field and 36.5% under 400 G magnetic field which occurs at 20 °C and 3 vol.% of nanoparticles. Furthermore, an empirical correlation is derived to estimate thermal conductivity of MnFe 2 O 4 /water nanofluid in terms of magnetic field intensity, volume concentration, and temperature. [ABSTRACT FROM AUTHOR]

Abstract It has been more than two decades since the discovery of nanofluids-mixtures of common liquids and solid nanoparticles less than 100 nm in size. As a type of colloidal suspension, nanofluids are typically employed as heat transfer fluids due to their favorable thermal and fluid properties. There have been numerous numerical studies of nanofluids in recent years (more than 1000 in both 2016 and 2017, based on Scopus statistics). Due to the small size and large numbers of nanoparticles that interact with the surrounding fluid in nanofluid flows, it has been a major challenge to capture both the macro-scale and the nano-scale effects of these systems without incurring extraordinarily high computational costs. To help understand the state of the art in modeling nanofluids and to discuss the challenges that remain in this field, the present article reviews the latest developments in modeling of nanofluid flows and heat transfer with an emphasis on 3D simulations. In part I, a brief overview of nanofluids (fabrication, applications, and their achievable thermo-physical properties) will be presented first. Next, various forces that exist in particulate flows such as drag, lift (Magnus and Saffman), Brownian, thermophoretic, van der Waals, and electrostatic double layer forces and their significance in nanofluid flows are discussed. Afterwards, the main models used to calculate the thermophysical properties of nanofluids are reviewed. This will be followed with the description of the main physical models presented for nanofluid flows and heat transfer, from single-phase to Eulerian and Lagrangian two-phase models. In part II, various computational fluid dynamics (CFD) techniques will be presented. Next, the latest studies on 3D simulation of nanofluid flow in various regimes and configurations are reviewed. The present review is expected to be helpful for researchers working on numerical simulation of nanofluids and also for scholars who work on experimental aspects of nanofluids to understand the underlying physical phenomena occurring during their experiments. [ABSTRACT FROM AUTHOR]