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The Nusselt number, overall heat transfer, and convective heat transfer coefficients of glycerol-water-based Cu nanofluids flowing in a parallel flow double pipe heat exchanger are estimated using CFD analysis. Single-phase fluid approach technique is used in the analysis. Ansys 19.0 workbench was used to create the heat exchanger model. Heat transfer tests with nanofluids at three flow rates (680

Dynamic viscosity of SiO2/22nm nanofluids prepared in a glycerine-water (30:70 by volume) mixture base liquid, referred to as GW70, is measured experimentally. Nanofluids with concentrations of 0.2, 0.6, and 1.0 percent are produced, and viscosity measurements are carried out at temperatures ranging from 20 to 80 oC using a LVDV-2T model Brookfield Viscometer. The particle size and elemental composition of nanoparticles are determined using FESEM and EDX. XRD images confirm the SiO2 peaks in the crystalline structure. The rheology of nanofluids is influenced by the nanoparticle’s concentration. In the experimental temperature and concentration range, nanofluids show Newtonian behavior. The viscosity of nanofluids enhanced as particle concentration increased and reduced as temperature increased. For 1.0 percent vol. concentration at 20oC, the maximum viscosity value is achieved, and for 0.2 percent vol. concentration at 80oC, the lowest viscosity value is observed. The viscosity of the glycerine-water base fluid was also determined at 20, 40, 60, and 80 degrees Celsius. The viscosity ratio of nanofluids to the base liquid is found to be more than one for all the nanofluids. This viscosity data is useful to estimate HTC of glycerine-water-based silica nanofluids.

The hybrid nanofluids were used as absorber fluids in solar energy applications, which could further increase the efficiency of solar devices. The use of nanofluids in solar devices with the laminar and turbulent flow has received much attention. Presently, the effect of temperature and concentration on thermal conductivity and viscosity of fly ash-copper (80:20% by volume) hybrid nanofluid is investigated. The thermal conductivity and viscosity measurements were carried in the temperature range of 30–60 °C for a concentration range of 0–4.0 vol%. The nanoparticles and nanofluids were characterized by XRF, XRD, SEM, TEM, zeta potential, and DLS techniques. The maximum augmentation in the hybrid nanofluid's dynamic viscosity and thermal conductivity at a concentration of 4 vol% is 45.18% and 49.8%, respectively, at 30 and 60 °C. Correlations to estimate the hybrid nanofluid's dynamic viscosity and thermal conductivity have been proposed considering the results obtained from the present study. A radial basis function-based neural network is used to model nanofluids' effective thermal conductivity and relative viscosity. The outcomes of the experiments were used to calculate the Mouromtseff number and heat transfer efficiency for solar energy applications.

The study is aimed to understand the heat transfer coefficient and thermal entropy generation analyses of plate heat exchanger by using water-based nanodiamond nanofluids. The experiments were conducted in the volume concentration range: 0 ≤ ϕ ≤ 1.0%, the Reynolds number range: 140 ≤ Re ≤ 610, the mass flow rate range: 0.05 ≤ m ≤ 0.183 kg / s , and the Peclet number range from 895.78 ≤ Pe ≤ 3882.72, respectively. The effect of Reynolds number, Peclet number and particle volume loadings of nanodiamond nanofluids on heat transfer characteristics and entropy generation has been investigated. Water and nanodiamond nanofluids were considered as hot and cold medium in the plate heat exchanger, respectively, for the experimental study. The study reveals considerable augmentation in heat transfer coefficient and Nusselt number with an increase of nanofluid particle loadings. The study showed 32.50%, 55.47%, 35.11%, 22.80%, and 18.93% enhancements in overall heat transfer coefficient, heat transfer coefficient, Nusselt number, pressure drop and pumping power compared to base fluid at a Reynolds number of 526.37 at ϕ = 1.0%. Improved effectiveness, number of transfer units and exergy efficiency of 14.41%, 32.81% and 19.72% was observed at ϕ = 1.0% and at a Reynolds number of 526.37 against base fluid data. The thermal entropy and friction entropy generation was showed decreasing and increasing trends respectively, in the measured particle volume loadings. The Bejan number and entropy generation number demonstrated the roles of heat transfer and friction factor in the entropy generation. From the experimental results a new Nusselt number and friction factor correlations were proposed.

The purpose of the current research work is to investigate the various properties like thermal conductivity, stability and viscosity of copper and a mixture of fly ash-Copper (FA:Cu) nanoparticles (NP) suspended in water. The research experiments were conducted for a concentration of 1.0 vol% of FA:Cu hybrid nanofluid (HNF) with various mixture ratios. The measurements of thermal conductivity and viscosity were performed in the 30–60 °C temperature range. The highest thermal conductivity and viscosity values for HNF with a mixture ratio of 20:80 were obtained with a maximum amplification exceeding 83.2% and 65% than the base fluid, respectively. The properties enhancement ratio (PER) reveals that HNF with 1.0 vol% concentration enhances heat transfer for all defined mixture ratios in the reported research work. Finally, the predictability potential of an ensemble-based machine learning technique called Boosted Regression Tree (BRT), based on nanofluids temperature (T) and mixture ratio (R), were compared with the classical regression approach to simulate the thermo-physical properties of HNF. The outcomes of the BRT model in terms of (r(viscosity) = 0.9953 and r(thermal conductivity) = 0.9991) superior to the regression method with (r(viscosity) = 0.9695 and r(thermal conductivity) = 0.9539) over the viscosity and thermal conductivity prediction process.

Convective and overall heat transfer coefficients of SiO2 nanofluid flowing in a concentric DTHE are determined experimentally. The tests are carried out in the 8002/22nm nanofluids prepared in 0.2, 0.6 and 1.0% volume concentrations in 30:70 ratio glycerol-water mixture base liquid. The thermal and physical properties of silica nanofluids are determined in the range of 20-80°C. Viscosity, thermal conductivity, and density of nanofluids increased with particle concentration whereas specific heat decreased. Thermal conductivity and specific heat of nanofluids increased with temperature while viscosity and density decreased. Heat transfer experiments are conducted using nanofluids at a bulk temperature of 35°C in a laminar developing flow region. Overall heat transfer coefficient and convective HTC of 1.0% silica nanofluids are increased by 21.2 and 36.3% compared to base liquid.