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Nanofluids have gained attention for their potential to solve overheating problems in various industries. They are a mixture of a base fluid and nanoparticles dispersed on the nanoscale. The nanoparticles can be metallic, ceramic, or carbon based, depending on the desired properties. While nanofluids offer advantages, challenges such as nanoparticle agglomeration, stability, and cost effectiveness remain. Nonetheless, ongoing research aims to fully harness the potential of nanofluids in addressing overheating issues and improving thermal management in different applications. The current study is concerned with the fluid flow and heat transfer characteristics of different nanofluids using different types of nanoparticles such as Al2O3, SiO2, and ZnO mixed with different base fluids. Pure water and ethylene glycol–water (EG–H2O) mixtures at different EG–H2O ratios (ψ = 0%, 10%, 30%, 40%) are used as the base fluid. Furthermore, a rectangular microchannel heat sink is used. Mesh independent study and validation are performed to investigate the current model, and a good agreement is achieved. The numerical analysis evaluates the influence on the heat transfer coefficient and flow characteristics of nanofluids for Reynolds numbers 500 to 1200 at a 288 K inlet flow temperature. The results show that ZnO nanofluid and 40% EG–H2O increase the heat transfer coefficient by 63% compared to ZnO–H2O nanofluid obtained at Re = 1200 and φ = 5%. Conversely, the pressure drop by ZnO is nearly double that obtained by Al2O3 and SiO2. [ABSTRACT FROM AUTHOR]

Nanofluid, the fluid suspensions of a metallic nanoparticle, became a coolant fluid that is used when a promising enhancement in heat transfer is required. In the current study, the characteristics of fluid flow and heat transfer are numerically investigated using different nanofluids (Al2O3–H2O, TiO2–H2O, and SiO2–H2O) and different micro-channel heat sink (MCHS) configurations (rectangular, triangular, trapezoidal, and circular). In this numerical investigation, the effect of Re number ranged from 890 to 1500, and the effect of nanoparticle concentration ranged from 1% to 7% at constant heat flux q = 106 W/m2, and constant fluid inlet temperature of 288 K, were studied. The average heat transfer coefficient, h, and pressure drop, Δ p , are used to quantify the fluid flow and heat transfer characteristics in each MCHS configuration and for each nanoparticle concentration. It is revealed that a better heat transfer coefficient is obtained for Al2O–H2O compared with other types of nanoparticles and pure water, such as 8.58% heat transfer coefficient improvement obtained at Re = 1500 and φ = 7 % more than that of pure water. It is also inferred that the maximum heat transfer coefficient is obtained by the triangular MCHS; however, it has the highest pressure drop because of the lowest hydraulic diameter. [ABSTRACT FROM AUTHOR]

There is no denial that renewable energy is considered to be the most cost-competitive source of clean power in many parts of the world. Saudi Arabia's vision 2030 aims at achieving the best by using different sources of renewable energy such as solar energy, wind energy, and others. The use of solar energy in particular for power generation will decrease the dependency on oil, and thus, decrease the greenhouse gasses. Solar panels efficiency tends to decrease with the accumulation of dust on their surface. Thus, a cleaning process requires assigning and employing labor, which increases the cost of running as well as high cost of machinery. The current study focuses on assessing and designing a simple auto self-cleaning system in order to improve the efficiency of the solar panel. The results showed that for the Al-Khobar region, Eastern Province, Kingdom of Saudi Arabia, the efficiency of the solar panels after cleaning was increased from 6% to an average of 12% at nominal temperature of 27 °C. In addition, the average power output was increased by 35% during the day time. In addition, the normal efficiency of the solar panels before cooling was between 10% to 15% at 42 °C. After cooling, the temperature of solar cells decreased to 20 °C and the efficiency increased by 7%. Moreover, the output power was increased by 31% with maximum efficiency of 32% at noon time. [ABSTRACT FROM AUTHOR]