Entropy generation optimization of unsteady radiative hybrid nanofluid flow over a slippery spinning disk

Entropy generation investigation of hybrid nanofluidic transport over an unsteady spinning disk is reported in this analysis. The magnetic influence, velocity slips, and thermal radiative effects are included within the flow. Ferrous oxide (Fe3O4) and graphene oxide (GO) are used as tiny nano ingredients, and water (H2O) is the base medium. The dimensional leading equations are settled to dimensionless nonlinear ordinary differential equations (ODEs) by significant similarity transformations. Then, classical RK-4 scheme with a shooting process has been initiated to execute the numerical simulation. The software MAPLE-18 is used to run the entire simulation with an indispensable accuracy rate. Several streamlines, graphs, and requisite tables are executed to divulge the parametric impact on the nanofluidic stream. Entropy generation–related figures are depicted for diverse parameters, and parametric effects on Bejan number are also analyzed. Moreover, the corresponding physical consignments like the measure of the frictional hindrance, heat transport are calculated and reviewed. The entropy generation augments for higher magnetic value but reduces for velocity slip, radiation, and nanoparticle concentration. Hybrid nanofluid gives a lower magnitude in entropy production as compared to the usual nanofluid. Magnetic parameter reduces the Bejan number, while slip factor and nanoparticle concentration amplify such effects. Heat transfer ultimately seems to increase for nanoparticle volume fraction, and the increase rate is 4.01685 for usual nanofluid, but it is 6.7557 for hybrid nanofluid. Also, the numerical fallouts address the possibility of using magnetized spinning disks in space engines and nuclear propulsion, and such a model conveys significant applications in heat transport improvement in so many industrial thermal management equipment and renewable energy systems.

The Impact of Alumina Nanofluids on Pool Boiling Performance on Biphilic Surfaces for Cooling Applications

This work aims to study the impact of nanofluids with alumina particles on pool boiling performance. Unlike most studies, which use a trial-and-error approach to improve boiling performance parameters, this study details the possible effects of nanoparticles on the effective mechanisms of boiling and heat transfer. For this purpose, biphilic surfaces (hydrophilic surfaces with superhydrophobic spots) were used, which allow the individual analysis of bubbles. Surfaces with different configurations of superhydrophobic regions were used. The thermophysical properties of fluids only vary slightly with increasing nanoparticle concentration. The evolution of the dissipated heat flux and temperature profiles for a nucleation time frame is independent of the fluid and imposed heat flux. It can be concluded that the optimal concentration of nanoparticles is 3 wt%. Using this nanoparticle concentration leads to lower surface temperature values than those obtained with water, the reference fluid. This is due to the changes in the balance of forces in the triple line, induced by increased wettability as a consequence of the deposited particles. Wherefore, smaller and more frequent bubbles are formed, resulting in higher heat transfer coefficients. This effect, although relevant, is still of minor importance when compared to that of the use of biphilic surfaces.

Experimental study and computational intelligence on dynamic viscosity and thermal conductivity of HNTs based nanolubricant

Purpose This paper aims to evaluate the dynamic viscosity and thermal conductivity of halloysite nanotubes (HNTs) suspended in SAE 5W40 using machine learning methods (MLMs). Design/methodology/approach A two-step method with surfactant was selected to prepare nanolubricants in concentrations of 0.025, 0.05, 0.1 and 0.5 wt%. Thermal conductivity and dynamic viscosity of nanofluids were ascertained over the temperature range of 25–70 °C, with an increment step of 5 °C, using a KD2-Pro analyser device and a digital viscometer MRC VIS-8. Additionally, four different MLMs, including Gaussian process regression (GPR), artificial neural network (ANN), support vector machine (SVM) and decision tree (DT), were used for predicting dynamic viscosity and thermal conductivity by using nanoparticle concentration and temperature as input parameters. Findings According to the achieved results, the dynamic viscosity and thermal conductivity of nanolubricants mostly increased with the rise of nanoparticle concentration in the base oil. All the proposed models, especially GPR with root mean square error mean values of 0.0047 for dynamic viscosity and 0.0016 for thermal conductivity, basically showed superior ability and stability to estimate the viscosity and thermal conductivity of nanolubricants. Practical implications The results of this paper could contribute to optimising the cost and time required for modelling the thermophysical properties of lubricants. Originality/value To the best of the author’s knowledge, in this available literature, there is no paper dealing with experimental study and prediction of dynamic viscosity and thermal conductivity of HNTs-based nanolubricant using GPR, ANN, SVM and DT.

Characterisation, Performance and Optimisation of Nanocellulose Metalworking Fluid (MWF) for Green Machining Process

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour.

Effect of Temperature and Nanoparticle Concentration on the Viscosity of Glycerine-water based SiO2 Nanofluids

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.

MHD radiative flow of Williamson nanofluid along stretching sheet in a porous medium with convective boundary conditions

Fluid heating and cooling is significant in a variety of industries, including power generation and transportation. Improvements in the thermal conductivity of the base fluid can also help in heat transmission. For this purpose, the effects of magneto hydrodynamics (MHD) and thermal radiation on mixed convection flow of Williamson nanofluid across a stretched sheet embedded in a porous medium in the presence of slip and convective boundary conditions is investigated. The Boungiorno model is adopted to analyze the impact of various dimensionless parameters on velocity, temperature, and nanoparticle concentration in the presence of slip and convective boundary conditions. The nonlinear governing equations are non-dimensionalized using similarity transformations, and the Keller box technique is utilized to solve them numerically. The current code is validated by generating numerical results for wall shear stress and compared them to previously published results. The comparison demonstrates that the outcomes are extremely similar. The results reveal that in the presence of a porous media, raising the magnetic and slip parameters reduced the nanofluid's velocity. It is also noticed that by increasing the radiation parameter, the heat and mass transfer rates on the surface of the stretching sheet are improved. In the presence of convective boundary conditions, the effect of Brownian motion and thermophoresis parameters on nanoparticle concentration was observed to be more profound.

Investigation of the laser-induced breakdown plasma, acoustic vibrations and dissociation processes of water molecules caused by laser breakdown of colloidal solutions containing Ni nanoparticles

In this work the process of optical breakdown under laser irradiation by nanosecond pulses with an energy of 650 mJ of aqueous solutions of Ni nanoparticles is investigated. A monotonic change in the number of breakdowns, the average distance between closest breakdowns, the average plasma size of an individual breakdown, the luminosity of a plasma flash, the intensity of acoustic signals, and the rate of formation of dissociation products - O2, H2, OH•, and H2O2 with an increase in the irradiation time was established. With an increase in the concentration of nanoparticles, the measured values change non-monotonically. The maximum luminosity of a plasma flash is observed at a nanoparticle concentration of 109 NP/ml and 1010 NP/ml and reaches 350 cd/m2. The maximum pressure at the shock front is 1.5–2 MPa at a nanoparticle concentration of 1010 NP/ml. The maximum rates of generation of O2, H2, OH• and H2O2 are observed at concentrations of 109 NP/ml and 1010 NP/ml. Correlation analysis of the studied physicochemical phenomena shows that the formation of molecular gases is associated with acoustic processes, and the formation of radical products and hydrogen peroxide correlates with the physicochemical properties of plasma.

Thermal and Hydraulic Performances of Porous Microchannel Heat Sink using Nanofluids

Microchannel heat sink is an effective method in compact and faster heat transfer applications. This paper numerically investigates thermal and hydraulic characteristics of a porous microchannel heat sink (PMHS) using various nanofluids. The effect of porosity, inlet velocity and nanoparticle concentration on thermal-hydraulic performance is systematically examined. The result shows a significant temperature increase (40°C) of the coolant in the porous zone. The pressure drop reduces by 35% for γ = 0.32 compared to the non-porous counterpart, and this reduction of pressure significantly continues when γ further increases. The pressure drop with win is linear for PMHS with nanofluids, and the change in pressure drop is steeper for nanofluids compared to their base fluids. The average heat transfer coefficients increases about 2.5 times for PMHS, and a further increase of 6% in is predicted with the addition of nanoparticle. The average Nusselt number increases non-linearly with Re for PMHS. The friction factor reduces by 50% when γ increases from 0.32 to 0.60, and the effect of nanofluid on friction factor is insignificant beyond the mass flow rate of 0.0004 kg/s. Whilst Cu and CuO nanoparticles help to dissipate the larger amount of heat from the microchannel, Al2O3 nanoparticle appears to have a detrimental effect on heat transfer. The thermal-hydraulic performance factor strongly depends on the nanoparticles, and it slightly decreases with the mass flow rate. The increase of nanoparticle concentration, in general, enhances both h and ΔP linearly for the range considered.

Determination of nanoparticles concentration in solution based on Pickering emulsion destabilization analyses

The dynamic development of nanotechnology research has contributed to the fact that various types of nanoparticles are increasingly used on a large scale both for medical and biological purposes, but above all in many industrial fields. Such a wide application of nanoparticles is often connected with the need to estimate their characteristic parameters, such as size, size distribution or concentration. Existing instruments are usually quite expensive and not always available. Therefore, other cheaper and simpler methods based on analytical techniques are sought. In this paper, we have proposed a method to estimate the concentration of nanoparticles in solutions based on destabilization analyses of Pickering emulsions produced with their use. The fact of mutual relationship between emulsion concentration, nanoparticle concentration and emulsion stability was used here. The study was carried out using silica nanoparticles. It was presented how to apply the method and what are its limitations. Moreover, an example of its application for the determination of nanoparticle concentration in an unknown sample, obtained after analysis of the permeability of membranes in diffusion chambers, has been presented. The method can become a useful alternative for the determination of nanoparticle concentration in solution in places where no specialized equipment is available.