Search Results (38)

Nanoparticle additives are used to increase the cooling efficiency of cutting fluids in machining. In this study, changing dynamic viscosity values depending on the addition of nanoparticles to cutting oils was investigated. Mono nanofluids were prepared by adding hBN (hexagonal boron nitride), ZnO, MWCNT (multi-walled carbon nanotube), TiO₂, and Al₂O₃ as nanoparticles, hybrid nanofluids were prepared by using two types of nanoparticles (ZnO + MWCNT, hBN + MWCNT etc.), and ternary nanofluids were prepared by using three types of nanoparticles. GPR (Gaussian process regression) was used to estimate unmeasured dynamic viscosity values using the dynamic viscosity values measured for different temperatures. Dynamic viscosity results are a precise determination (R² = 1). An augmented dataset was obtained by adding the dynamic viscosity values estimated with high accuracy. A fitness function based on dynamic viscosity and nanoparticle unit costs was proposed for the cost analysis. With the help of the proposed fitness function, it was observed that the best performing nanoparticles were the ZnO and ZnO hybrid mixtures according to different dynamic viscosity and cost effects. The study showed that the most suitable nanofluid selection focused on performance and cost could be made without performing experiments under various operating conditions by increasing the limited experimental measurements with strong GPR estimates and using the proposed fitness function. Full article

In this work, a novel type of shell and helically coiled heat exchangers (SHCHEXs) that are used extensively in numerous applications has been numerically and experimentally studied. A low-cost and easily applicable design for enhancing the heat exchange rate in a shell and helically coiled heat exchanger has been developed within the scope of this study. In this context, a SHCHEX has been developed with an internal guiding pipe and spirally formed fins with the purpose of leading the fluid in the cold loop over the coil where hot fluid flows inside it. Numerical simulations were carried out in this study for determining how the new changes including nonporous and porous spiral fins affected heat transfer in the system. In the experimental part of the current research, a heat exchanger with a guiding pipe and nonporous spiral fins has been fabricated and its thermal behavior tested at various conditions utilizing water and MnFe₂O₄-ZnFe₂O₄/water hybrid-type nanofluid. Both numerical and experimental findings of this research exhibited positive effects of using new modifications including spiral fin integration. Overall findings of this work clearly exhibited a significant effect of the spiral fin medication and MnFe₂O₄-ZnFe₂O₄/water-hybrid magnetic nanofluid utilization on the thermal performance improvement in the heat exchanger. Experimentally determined findings showed that using MnFe₂O₄-ZnFe₂O₄/water in the hot loop of the SHCHEX improved the heat transfer coefficient of the heat exchanger by an average ratio of 16.2%. In addition, mean variation between the experimentally obtained exit temperature and numerically achieved one was 3.9%. Full article

Machining processes often face challenges such as elevated temperatures and wear, which traditional cutting fluids are insufficient to address. As a result, solutions involving nanoparticle additives are being explored to enhance cooling and lubrication performance. This study investigates the effect of thermal conductivity, an important property influenced by the densities of mono and hybrid nanofluids. To this end, various nanofluids were prepared by incorporating hexagonal boron nitride (hBN), zinc oxide (ZnO), multi-walled carbon nanotubes (MWCNTs), titanium dioxide (TiO₂), and aluminum oxide (Al₂O₃) nanoparticles into sunflower oil as the base fluid. Hybrid nanofluids were created by combining two nanoparticles, including ZnO + MWCNT, hBN + MWCNT, hBN + ZnO, hBN + TiO₂, hBN + Al₂O₃, and TiO₂ + Al₂O₃. A dataset consisting of 180 data points was generated by measuring the thermal conductivity and density of the prepared nanofluids at various temperatures (30–70 °C) in a laboratory setting. Conducting thermal conductivity measurements across different temperature ranges presents significant challenges, requiring considerable time and resources, and often resulting in high costs and potential inaccuracies. To address these issues, a feedforward artificial neural network (FFANN) method was proposed to predict thermal conductivity. Our multilayer FFANN model takes as input the temperature of the experimental environment where the measurement is made, the measured thermal conductivity of the relevant nanoparticle, and the relative density of the nanoparticle. The FFANN model predicts the thermal conductivity value linearly as output. The model demonstrated high predictive accuracy, with a reliability of R = 0.99628 and a coefficient of determination (R²) of 0.9999. The average mean absolute error (MAE) for all hybrid nanofluids was 0.001, and the mean squared error (MSE) was 1.76 × 10⁻⁶. The proposed FFANN model provides a State-of-the-Art approach for predicting thermal conductivity, offering valuable insights into selecting optimal hybrid nanofluids based on thermal conductivity values and nanoparticle density. Full article

In the study conducted for the cooling systems of MALE class unmanned aerial vehicles using internal combustion engines, new type radiators were designed using spring-structure fins. Among the radiators formed with spring structures acting as fins, the radiator developed using springs with a pitch of 2.25 mm was named Radiator-Y1, the radiator developed using springs with a pitch of 4.25 mm was named Radiator-Y2, and the radiator developed using springs with a pitch of 8.25 mm was named Radiator-Y3. This design change is seen as an innovative method that can increase heat transfer on the radiator surface and increase cooling performance by increasing the turbulence effect of the air affecting the radiator. Experimental studies were carried out using single type (Al₂O₃ and ZnO) and hybrid (ZnO-CuO) nanofluids in addition to pure water. Experiments were carried out using different air speeds (8–10–12 m/s) and different coolant flow rates (20–22 L/min) and radiator performance was investigated. The effects of the surface area created by the spring structure and the turbulence effect on heat transfer were evaluated. As a result of the studies, Radiator-Y1 showed the best cooling performance among the radiators developed with spring structures, followed by Radiator-Y2 and Radiator-Y3. It was observed that the nanofluids used had a positive effect on the cooling performance compared with pure water, as did the hybrid nanofluid compared when compared with single type nanofluids. Full article

This study investigates the potential of a hybrid nanofluid composed of MoS₂ and ZnO nanoparticles dispersed in engine oil, aiming to enhance the properties of a lubricant’s chemical reaction with the Soret effect on a stretching sheet under the influence of an applied magnetic field. With the growing demand for efficient lubrication systems in various industrial applications, including automotive engines, the development of novel nanofluid-based lubricants presents a promising avenue for improving engine performance and longevity. However, the synergistic effects of hybrid nanoparticles in engine oil remain relatively unexplored. The present research addresses this gap by examining the thermal conductivity, viscosity, and wear resistance of the hybrid nanofluid, shedding light on its potential as an advanced lubrication solution. Overall, the objectives of studying the hybrid nanolubricant MoS₂ + ZnO with engine oil aim to advance the development of more efficient and durable lubrication solutions for automotive engines, contributing to improved reliability, fuel efficiency, and environmental sustainability. In the present study, the heat and mass transformation of a Casson hybrid nanofluid (MoS₂ + ZnO) based on engine oil over a stretched wall with chemical reaction and thermo-diffusion effect is analyzed. The governing nonlinear partial differential equations are simplified as ordinary differential equations (ODEs) by utilizing the relevant similarity variables. The MATLAB Bvp4c technique is used to solve the obtained linear ODE equations. The results are presented through graphs and tables for various parameters, namely, M, Q, β, Pr, Ec, Sc, Sr, Kp, Kr, and ${\varphi }_2*$ (hybrid nanolubricant parameters) and various state variables. A comparative survey of all the graphs is presented for the nanofluid (MoS₂/engine oil) and the hybrid nanofluid (MoS₂ + ZnO/engine oil). The results reveal that the velocity profile diminished against the values of M, Kp, and β, and the temperature profile rises with Ec and Q, whereas Pr decreases. The concentration profile is incremented (decremented) with the value of Sr (Sc and Kr). A comparison of the nanofluid and hybrid nanofluid suggests that the velocity f′ (η) becomes slower with the augmentation of ${\varphi }_2*$ whereas the temperature increases when ${\varphi }_2*$ = 0.6 become slower. Full article

Renewable solar energy storage facilities are attracting scientists’ attention since they can overcome the key issues affecting the shortage of energy. A nanofluid phase change material (PCM) is introduced as a new sort of PCM is settled by suspending small proportions of nanoparticles in melting paraffin. ZnO/α-Fe₂O₃ nanocrystals were prepared by a simple co-precipitation route and ultrasonically dispersed in the paraffin to be a nanofluid-PCM. The behaviors of the ZnO/α-Fe₂O₃ nanocrystals were verified by X-ray diffraction (XRD) analysis, and the average particle size and the morphology of the nanoparticles were explored by transmission electron microscopy (TEM). For the object of industrial ecology concept, aluminum-based waste derived from water-works plants alum sludge (AS) is dried and augmented with the ZnO/α-Fe₂O₃ nanocrystals as a source of multimetals such as aluminum to the composite, and it is named AS-ZnO/α-Fe₂O₃. The melting and freezing cycles were checked to evaluate the PCM at different weight proportions of AS-ZnO/α-Fe₂O₃ nanocrystals, which confirmed that their presence enhanced the heat transfer rate of paraffin. The nanofluids with AS-ZnO/α-Fe₂O₃ nanoparticles revealed good stability in melting paraffin. Additionally, the melting and freezing cycles of nanofluid-PCM (PCM- ZnO/α-Fe₂O₃ nanoparticles) were significantly superior upon supplementing ZnO/α-Fe₂O₃ nanoparticles. Nanofluid-PCM contained the AS-ZnO/α-Fe₂O₃ nanocrystals in the range of 0.25, 0.5, 1.0, and 1.5 wt%. The results showed that 1.0 wt% AS-ZnO/α-Fe₂O₃ nanocrystals contained in the nanofluid-PCM could enhance the performance with 93% with a heat gained reached 47 kJ. Full article

Titanium alloys are difficult to machine and have poor tribological properties. This paper investigates the lubricating performance of γ-Al₂O₃/ZnO hybrid nanofluids for Ti-6Al-4V. Pure and hybrid nanofluids are compared, and the effects of γ-Al₂O₃/ZnO ratios are studied. The results show that γ-Al₂O₃/ZnO hybrid nanofluids outperform pure nanofluids in terms of lower friction coefficients and better surface quality. Moreover, the hybrid nanofluid with a mass ratio of Al₂O₃ to ZnO of 2:1 demonstrates the best lubrication performance with a reduced friction coefficient of up to 22.1% compared to the base solution, resulting in improved surface quality. Al₂O₃ nanoparticles can adhere to the surface of ZnO nanoparticles and work as a coating, which further enhances the lubrication performance of the water-based nanofluid. Full article

Hard turning is an emerging machining technology that evolved as a substitute for grinding in the production of precision parts from hardened steel. It offers advantages such as reduced cycle times, lower costs, and environmental benefits over grinding. Hard turning is stated to be difficult because of the high hardness of the workpiece material, which causes higher tool wear, cutting temperature, surface roughness, and cutting force. In this work, a dual-nozzle minimum quantity lubrication (MQL) system’s performance assessment of ZnO nano-cutting fluid in the hard turning of AISI 52100 bearing steel is examined. The objective is to evaluate the ZnO nano-cutting fluid’s impacts on flank wear, surface roughness, cutting temperature, cutting power consumption, and cutting noise. The tool flank wear was traced to be very low (0.027 mm to 0.095 mm) as per the hard turning concern. Additionally, the data acquired are statistically analyzed using main effects plots, interaction plots, and analysis of variance (ANOVA). Moreover, a novel Weighted Aggregated Sum Product Assessment (WASPAS) optimization tool was implemented to select the optimal combination of input parameters. The following optimal input variables were found: depth of cut = 0.3 mm, feed = 0.05 mm/rev, cutting speed = 210 m/min, and flow rate = 50 mL/hr. Full article

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 SiO_2. Full article

In order to address the issue of a solar utilization system with low efficiency, this paper designs a new solar conversion system based on photovoltaic concentration and spectral splitting. The system concentrates sunlight through a Fresnel lens and uses a hollow concave cavity to evenly distribute the incident energy flow. The spectral splitting medium separates the useful irradiance for the PV cell from those wavelengths that are more suited to heat generation. By considering the available wavelength of photovoltaic cells, the GaAs cell and a ZnO nanofluid were selected for this paper. It was found that installing the hollow concave cavity improved the spot uniformity of the PV cell surface by 17%. The output efficiency of the system under various circumstances was analyzed. The results show that at a concentration ratio of 50 and a light intensity of 1000 W/m², photoelectric conversion efficiency increased by 0.81%. When compared to direct concentration, the photoelectric conversion efficiency increased by at least 7%. Meanwhile, the comprehensive electrical efficiency was 36.7%, which is higher than that of the normal concentration PV and comprehensive thermal system. Full article

All living organisms depend on water for their survival. Therefore, sufficient water availability is necessary for health. During the last few years, considerable progress has been made in the production of clean drinking water—particularly in the desalination industry. Various methods have been explored to boost the productivity of solar stills. The present review focuses on recent enhancement techniques aimed at boosting their performance—particularly those incorporating non-metallic nanofluids into the base fluid. The nanomaterials examined in this review include Al₂O₃, CuO, ZnO, and TiO₂. Several studies adding Al₂O₃ in a solar-still desalination system resulted in an increase in distillate yield, better efficiency, reduced energy consumption, reduced thermal loss, and better productivity. The incorporation of CuO in a solar-still desalination system led to major improvements in performance. These included enhanced daily efficiency, better productivity, improved production of freshwater, and higher energy and exergy efficiency. The incorporation of TiO₂ in a solar-still desalination system resulted in increased productivity, better thermal conductivity, better thermal efficiency, higher daily distillate output, and high levels of water temperature. It was also evident that the incorporation of ZnO in a solar-still desalination system resulted in a substantial increase in the output of clean water and occasioned improvements in productivity and overall efficiency. Together, these findings demonstrate the potential of these nanomaterials to significantly enhance the performance of solar-still desalination systems. Other nanomaterials that are yet to gain increased use, such as SiO₂ and SnO₂, have also been discussed. The collective results in this paper demonstrate the potential of nanofluids to enhance the performance and effectiveness of solar-still desalination systems. This review provides conclusive evidence of the positive effects of different nanofluids on the yield, productivity, energy, and efficiency of diverse types of solar stills, offering promising advancements in the sustainable production of water. Full article

The mass fraction of 0.01 wt% ZnO nanofluid was prepared via the two-step method. The measurement verifies that ZnO nanofluids have better transmission characteristics in the frequency division window range of 400–1200 nm. At the same time, it has good absorption characteristics in ultraviolet and near-infrared bands, which meets the application conditions of the spectral beam-splitting module of the PV/T system. A spectral beam-splitting module of the PV/T system was designed. The simplified physical model was established in ANSYS 14.0. The flow field and convective heat transfer were simulated for different arrangements of the interlayer inlet to obtain a more ideal and uniform temperature distribution to improve the system’s comprehensive efficiency. The results show that the fluid flow in the interlayer under case II is more uniform, and the temperature field distribution is better than other arrangements. Hence, this work could provide a reference for optimising nanofluid flow within a spectral beam-splitting module. Full article

Surfactant-based viscoelastic (SBVE) fluids have recently gained interest from many oil industry researchers due to their polymer-like viscoelastic behaviour and ability to mitigate problems of polymeric fluids by replacing them during various operations. This study investigates an alternative SBVE fluid system for hydraulic fracturing with comparable rheological characteristics to conventional polymeric guar gum fluid. In this study, low and high surfactant concentration SBVE fluid and nanofluid systems were synthesized, optimized, and compared. Cetyltrimethylammonium bromide and counterion inorganic sodium nitrate salt, with and without 1 wt% ZnO nano-dispersion additives, were used; these are entangled wormlike micellar solutions of cationic surfactant. The fluids were divided into the categories of type 1, type 2, type 3, and type 4, and were optimized by comparing the rheological characteristics of different concentration fluids in each category at 25 °C. The authors have reported recently that ZnO NPs can improve the rheological characteristics of fluids with a low surfactant concentration of 0.1 M cetyltrimethylammonium bromide by proposing fluids and nanofluids of type 1 and type 2. In addition, conventional polymeric guar gum gel fluid is prepared in this study and analyzed for its rheological characteristics. The rheology of all SBVE fluids and the guar gum fluid was analyzed using a rotational rheometer at varying shear rate conditions from 0.1 to 500 s⁻¹ under 25 °C, 35 °C, 45 °C, 55 °C, 65 °C, and 75 °C temperature conditions. The comparative analysis section compares the rheology of the optimal SBVE fluids and nanofluids in each category to the rheology of polymeric guar gum fluid for the entire range of shear rates and temperature conditions. The type 3 optimum fluid with high surfactant concentration of 0.2 M cetyltrimethylammonium bromide and 1.2 M sodium nitrate was the best of all the optimum fluids and nanofluids. This fluid shows comparative rheology to guar gum fluid even at elevated shear rate and temperature conditions. The comparison of average viscosity values under a different group of shear rate conditions suggests that the overall optimum SBVE fluid prepared in this study is a potential nonpolymeric viscoelastic fluid candidate for hydraulic fracturing operation that could replace polymeric guar gum fluids. Full article

The driving motor is one of the most crucial components of an electric vehicle (EV). The most commonly used type of motor in EVs is the induction motor. These motors generate heat during operation due to the flow of electrical current through the motor’s coils, as well as friction and other factors. For long-run and high efficiency of the motor, cooling becomes more important. This article utilized ANSYS Motor-CAD to map the temperature signature of an induction motor and investigated the thermal efficiency of using nanofluids as a cooling medium. The thermal conductivity of nanofluids has been found to be superior to that of more conventional cooling fluids such as air and water. This research explores the effect of using Al₂O₃, ZnO, and CuO concentrations in nanofluids (water as a base fluid) on the thermal efficacy and performance of motor. According to the findings, using nanofluids may considerably increase the efficiency of the motor, thereby lowering temperature rise and boosting system effectiveness. Based on the simulation analysis using ANSYS Motor-CAD, the results demonstrate that the utilization of CuO nanofluid as a cooling medium in the induction motor led to a reduction of 10% in the temperature of the motor housing. The maximum reduction in the temperature was found up to 10% when nanofluids were used, which confirms CuO as an excellent option of nanofluids for use as motor cooling and other applications where effective heat transmission is crucial. Full article

As a promising new power source, the proton exchange membrane fuel cell (PEMFC) has attracted extensive attention. The PEMFC engine produces a large amount of waste heat during operation. The excessive temperature will reduce the efficiency and lifespan of PEMFC engine and even cause irreversible damage if not taken away in time. The thermal management system of the PEMFC plays a critical role in efficiency optimization, longevity and operational safety. To solve the problem of high heat production in the operation of the PEMFC, two approaches are proposed to improve the heat dissipation performance of the radiators in thermal management systems. Three kinds of nanofluids with excellent electrical and thermal conductivity–Al₂O₃, SiO₂ and ZnO– are employed as the cooling medium. The radiator parameters are optimized to improve the heat transfer capability. A typical 1D thermal management system and an isotropic 3D porous medium model replacing the wavy fin are constructed to reveal the effects of the nanofluid and the parameters of the radiator performance and the thermal management system. The results show that all three kinds of nanofluids can effectively improve the heat transfer capacity of the coolant, among which the comprehensive performance of the Al₂O₃ nanofluid is best. When the mass flow rate is 0.04 kg/s and the concentration is 0.5 vol%, the amount of heat transfer of the Al₂O₃ nanofluid increases by 12.7% when compared with pure water. Under the same conditions, it can reduce the frontal area of the radiator by 12%. For the radiator, appropriate reduction of the fin pitch and wavy length and increase of wave amplitude can effectively improve the spread of heat. The use of fin parameters with higher heat dissipation power results in lower coolant temperatures at the inlet and outlet of the stack. The performance of the radiator is predicted by the two model-based approaches described above which provide a reliable theoretical basis for the optimization of the thermal management system and the matching of the components. Full article