Thermal Conductivity Of Base Fluid Research Articles

The function of nano layer in enhancing the thermal conductivity of TiO2/water nanofluids

Nanoparticles have the capability to effectively improve the thermal conductivity of base fluids, thus improving the heat transfer coefficient of heat transfer systems. In this study, a non-equilibrium molecular dynamics (NEMD) method based on the Fourier law is employed to study the thermal conductivity of TiO2 (r-TiO2)/water nanofluids with temperatures ranging between303K and 333K and volume fractions in the range of1-2%. The ordered layer structure as a shell is analyzed and its influence is surveyed by calculating the number density and radial distribution function (RDF).The results revealed that a clear, solid-like nanolayer of about 0.5 nm can be observed around the nanoparticle. In this regard, the thickness of the nanolayer is less affected by variations in volume fraction and temperature. The g(r) values and the number density decreased with the increase in temperature. Additionally, the g(r) values and the number density at the level of the nanolayer were much higher compared to those at other parts. This indicates the existence of more water molecules in the nanolayer, thereby reducing contact thermal resistance and improving thermal conductivity. Macroscopically, the thermal conductivity increases with the increase in volume fraction. It was found that the increase in the volume fraction from 1%to 2%at303Kresulted in an increase in the effective thermal conductivity from1.027 and 1.042, respectively. In other words, the thermal conductivity of the nanofluid was 2.7% and 4.2% higher than that of the base liquid under the same conditions.

Scrutiny of nanoscale heat transport with ion-slip and hall currenton ternary MHD cross nanofluid over heated rotating geometry

SignificanceThermal engineering is facing energy consumption issue, to handle this pointwe need to enhance the thermal conductivity of base fluid because low thermal conductivity causes to poor heat dissipation, insufficient temperature control, high energy consumption and Limited applications. To overcome this issue nanoparticle are added in base fluid. PurposeThis attempt examines the scrutiny of nanoscale heat transport with ion-slip and hall current on Ternary MHD Cross nanofluid over heated rotating geometry. This attempt involves three nanoparticles which are silver, copper and graphene oxide. Inclined magnetic field and chemical process effects are imposed also. MethodologyGenerated PDEs are transformed into ODEs and numerical simulations areperformed using the methodology of spectral relaxationtechnique to fetch the numerical results. FindingsAugmented values of φGO,φAg,φCu enhance the skin friction of ternary hybrid Cross nanofluid and rate of heat transport is augmented by 9%.Numerical augmented values of φGO,φAg,φCu enhanced the skin friction coefficient and Hall current parameter makes enhancement in velocity of ternary hybrid cross nanoliquid.

Numerical Approach toward Ternary Hybrid Nanofluid Flow Using Variable Diffusion and Non-Fourier's Concept.

In the current study, the pseudoplastic model is used to analyze the mass and energy transmission through trihybrid nanofluid flow across a stretched permeable surface. The Darcy–Forchheimer relation is employed in the momentum equation to examine the influence of porosity. Energy and mass diffusion expressions are obtained by employing the double diffusion theories, which were proposed by Cattaneo and Christov and is broadly used by several researchers. The thermal efficiency of the trihybrid nanocrystals is evaluated by integrating them with a pseudoplastic substrate. The study of titanium dioxide (TiO2), cobalt ferrite (CoFe2O4), and magnesium oxide (MgO) nanocomposite base hybrid nanofluids across a stretchable sheet is receiving considerable interest in innovation and research due to their extensive spectrum of applicability. For this reason, the phenomena are modeled in the form of a system of PDEs with the effects of a heat source, magnetic field, natural convection, and chemical reaction. Through resemblance substitutions, these are reduced to an ODE system. The resultant first-order differential equations are further processed using the computational approach PCM. For authenticity and reliability, the values are reviewed against the existing literature. The findings are displayed through figures. When compared to the simple nanofluid, the hybrid and trihybrid nanofluid have a greater tendency for fluid energy and velocity propagation rate. The velocity and heat transition rate enhance 11.73% by varying nanoparticles’ values from 0.01 to 0.04, while the thermal conductivity of base fluid boosts with the addition of hybrid and trihybrid nanocomposites, up to 32% and 61%, respectively.

THE CARBON NANOTUBE-EMBEDDED BOUNDARY LAYER THEORY FOR ENERGY HARVESTING

Single-walled carbon nanotubes (SWNTs) and multi-walled nanotubes (MWNTs) are gaining appeal in mechanical engineering and industrial applications due to their direct influence on enhancing the thermal conductivity of base fluids. With such intriguing properties of carbon nanotubes in mind, our goal in this work is to investigate radiation effects on the flow of carbon nanotube suspended nanofluids in the presence of a magnetic field past a stretched sheet impacted by slip state. CNTs flow and heat transmission are frequently modelled in practice using nonlinear differential equation systems. This system has been precisely solved, and an accurate analytical expression for the fluid velocity in terms of an exponential function has been derived, while the temperature distribution is stated in terms of a confluent hypergeometric function. The impact of the radiation parameter, slip parameter, sloid volume fraction, magnetic parameter, Eckart and Prandtl numbers on the velocity, temperature, and heat transfer rate profiles are demonstrated using a parametric analysis. When compared to the two types of nanoparticles (Cooper and Silver) in earlier published articles, temperature profiles for single-walled nanotubes (SWNTs) and multi-walled nanotubes (MWNTs) are revealed to be particularly sensitive to radiation, solid volume fraction, and slip parameters. Nanomechanical gears, nanosensors, nanocomposite materials, resonators, and thermal materials are only a few of the present problem's technical applications.

Bioconvection attribution for effective thermal transportation of upper convicted Maxwell nanofluid flow due to an extending cylindrical surface

The enhancement of thermal conductivity of base fluids is desirable with the inclusion of nano-entities and bioconvection of microorganisms. The influence of the multi-slips on magnetohydrodynamic bio-convection streamline of micropolar based nanofluid across a sponge medium owing to expanding sheet is investigated in this work. The mass transpiration and activation energy with Fourier-Fick diffusion is taken into account. The leading partial differential equations are transformed into ordinary differential equations by using similarity transformations. The graphs were created by using the RK-4th order method with the shooting technique. Nusselt number, Sherwood number, skin friction factor, and motile density function are enumerated and analyzed with the variance of influenced parameters. It is observed the magnitude of the skin friction factor is enhanced with higher inputs of magnetic field and porosity parameters. Also observed that fluid speed is higher for injection than that of suction.

Insight into significance of thermal stratification and radiation on dynamics of micropolar water based TiO2 nanoparticle via finite element simulation

The evolution of nanofluids is important for improving the thermal conductivity of base fluids. The influence of thermal radiation and thermal stratification on the magnetohydrodynamic micropolar nanofluid flow through a shrinking sheet with a prescribed heat flux on the surface has been examined. The most important parts of this study are the effects of magnetohydrodynamic microrotation, thermal radiation, the magnetic field, and the Cattaneo-Christov heat flux model. The efficiency of nanoparticles, heat, and mass transference rates are influenced by the magnetic field pattern, the characteristics of the source of heat, thermal radiation, and the dispersion of volume fraction. The partial differentials are transformed into the set of nonlinear differential equations through boundary layer estimations and similarity substitutions and then computed with the use of a variational finite element procedure. A MATLAB code has been developed to assess parametric simulations for reduced skin friction factor, micro-rotation, fluid velocity, heat transfer rate, and thermal properties for the Glariken formulation. The temperature field declined due to increasing values of the thermal stratification parameter and the heat transfer rate accelerated. There is a strong link between the two sets of results, which shows that the finite element method used here is accurate.

Modeling thermal conductivity of nanofluids using advanced correlative approaches: Group method of data handling and gene expression programming

Accurate estimation of thermal conductivity (TC) of nanofluids is essential in thermophysical studies of nanofluids. In this study, more than 3200 data of thermal conductivity of nanofluids were collected from literature to develop simple-to-use and accurate correlations for predicting relative thermal conductivity of nanofluids. The dataset includes 13 different nanofluids with temperature from −30.00 to 149.15 °C, particle size from 5.00 to 150.00 nm, particle thermal conductivity from 1.20 to 1000.00 W/mk, particle volume fractions from 0.01 to11.22%, and base fluid thermal conductivity from 0.11 to 0.69 W/mk. Group method of data handling (GMDH) and gene expression programming (GEP) as two white-box powerful models were used for modeling. The results of proposed models were compared to 23 well-known theoretical and empirical models. The statistical and graphical results showed that the proposed models are more precise and reliable than the existing ones in literature. The GMDH model showed a better performance compared to GEP, and could predict all data with an average absolute relative error of 2.27% in training and 2.44% in testing data set. In addition, it was found that the proposed models could capture the physically expected trends with variation of temperature, size of nanoparticles, and volume fraction. The sensitivity analysis illustrated that temperature has the highest effect on the relative TC followed by base fluid TC and particle volume fraction

Experimental Investigation of Double Pipe Heat Exchanger Performance based on Alumina and Copper Oxide Working Nanofluids

The heat transfer performance of heat exchanger is greatly depending on the thermal conductivity and heat transfer capacity of the working fluid. One of the important methods to improve the thermal conductivity of the heat transfer fluid is by adding nano particles of materials with high thermal conductivity. In the present study, an experimental work was conducted to investigate the performance enhancement of double pipe heat exchanger using Alumina (Al2O3) and Copper oxide (CuO) nano particles mixed with engine oil as a working fluid. The thermal performance of heat exchanger was investigated at particles concentrations 0.05% and 0.1% of Al2O3 and CuO nano particles to determine the most effective factors on heat transfer enhancement. The results revealed that, the enhancement percentage in Nusselt number (Nu) for nanofluid at 0.05% particles concentration compared to pure oil was 9% and 6% for CuO and Al2O3 nanofluids respectively. While at 0.1% concentration, the enhancement percentage in Nu was about 17% and 15% for CuO and Al2O3 nanofluids respectively. The enhancement percentage in value of overall heat transfer coefficient for CuO nanofluid was 6.5% compared to Al2O3 nanofluid at 0.1% concentration. The enhancement percentage in the heat exchanger effectiveness was about 12% for CuO nanofluid compared with that for Al2O3 at 0.1% concentration. Adding the CuO and Al2O3 nano particles has improved the thermal conductivity of base fluid (oil) and led to a significant enhancement in heat transfer rate and thermal performance of the heat exchanger.

Electroosmosis augmented MHD peristaltic transport of SWCNTs suspension in aqueous media

This article analyzes the flow of single-walled carbon nanotubes (SWCNTs) suspended water-based ionic solution driven by combined effects of electroosmosis and peristalsis mechanisms. The analysis is performed in the presence of the transverse magnetic field, thermal radiation, mixed convection, and the slip boundary condition imposed on the channel walls. Poisson–Boltzmann ionic distribution is linearized by employing the Debye–Huckel approximation. The scaling analysis of the problem is rendered subject to the lubrication approach. The resulting nonlinear system of equations is executed to obtain approximate solutions using regular perturbation techniques and the graphical results are computed for various flow properties. Pumping and trapping phenomena are also discussed under the effects of pertinent parameters. Computed results show that a reduction in EDL thickness intensifies the fluid velocity as well as temperature. Improvement in thermal conductivity of base fluid is noticed with increasing SWCNTs volume fraction. It is further examined that axial velocity magnifies with Helmholtz–Smoluchowski velocity.

HEAT TRANSFER ENHANCEMENT USING PASSIVE TECHNIQUE: REVIEW

Preserving and saving energy have never been more important, thus the requirement for more effective and efficient heat exchangers has never been more important. However, in order to pave the way for the proposal of a truly efficient technique, there is a need to understand the shortcomings and strengths of various aspects of heat transfer techniques. This review aims to systematically identify these characteristics two of the most popular passive heat transfer techniques: nanofluids and helically coiled tubes. The review indicated that nanoparticles improve thermal conductivity of base fluid and that the nanoparticle size, as well as the concentrations of the nanoparticles plays a major role in the effectiveness of the nanofluids. Regarding the helically coiled tubes, it was discovered that the use of a coiled tube produces secondary flows, which ultimately improves the heat transfer enhancement. The third part of the review focused on microchannels and microtubes. This is mainly due to the growing need and requirement of smaller and more compact thermal cooling systems. Thus, ultimately the result of the review indicates that a combination of all these three techniques can lead to a compact and minimized heat exchanger that uses the benefits obtained from both nanofluids and helically coiled tubes in order to improve the heat transfer rate of the thermal systems.

Impact of thermal conductivity on the thermophysical properties and rheological behavior of nanofluid and hybrid nanofluid

A mathematical model is realistic to assess a comparative study of nanofluid and hybrid nanofluid flow between two eccentric pipes. Study of nanofluid has been developed recurrently over the earlier era. By taking the nanofluid study in higher level, the researchers tried to use hybrid nanofluid, which was modeled by placing different nanoparticles either in composite or mixture form. The method of using hybrid nanofluid is to get more thermal conductivity of base fluid. For this phenomena, we consider Ni and $$\gamma Al_2O_3$$ as nanoparticles and $$C_2H_6O_2$$ as a base fluid. The inner pipe is rigged and rotating with velocity (V), whereas the external pipe is sinusoidal (wave moving down to its boundaries) like the contracting and relaxation phenomena. Low Reynolds number and long wavelength approximation are used for analytic solution. The resulting nonlinear PDEs are converted into ODEs by using perturbation technique. After this, we compare graphically the behavior of friction forces on inner and outer pipes, pressure gradient, pressure rise, velocity and temperature profiles for multi-values of solid volume fractions.

Numerical simulation of squeezing flow Jeffrey nanofluid confined by two parallel disks with the help of chemical reaction: effects of activation energy and microorganisms

Abstract The utilization of nano-materials in a base fluid is a new dynamic technique to improve the thermal conductivity of base fluids. The suspension of tiny nanoparticles in base fluids is referred to the nano-materials. Nanofluids play a beneficial contribution in the field of nanotechnology, heat treatment enhancement, cooling facilities, biomedicine, bioengineering, radiation therapy and in military fields. The analysis of bioconvection characteristics for unsteady squeezing flow of non-Newtonian Jeffery nanofluid with swimming microorganisms over parallel disks with thermal radiation and activation energy has been studied in this continuation. The motivations for performing current analysis are to inspect the heat transfer enhancement in Jeffrey nanofluid in presence of multiple thermal features. The Jeffrey nanofluid contains motile microorganisms which convey dynamic applications in bio-technology and medical sciences and agricultural engineering. The system comprising differential equations of derivative is restricted to an ordinary one by means of a sufficient dimensionless similarity vector, and then implemented numerically by means of a famous shooting scheme with MATLAB tools. The effect of the significant parameters over the fluid flow is investigated from a physical point of view. The numerical findings of the modeled system are explored in detail using tabular data.

Magneto-Burgers Nanofluid Stratified Flow with Swimming Motile Microorganisms and Dual Variables Conductivity Configured by a Stretching Cylinder/Plate

Background. The study of nanofluid gains interest of researchers because of its uses in treatment of cancer, wound treatment, fuel reserves, and elevating the particles in the bloodstream to a tumour. This artefact investigates the magnetohydrodynamic flow of Burgers nanofluid with the interaction of nonlinear thermal radiation, activation energy, and motile microorganisms across a stretching cylinder. Method. The developed partial differential equations (PDEs) are transformed into a structure of ODEs with the help of similarity transformation. The extracted problem is rectified numerically by using the bvp4c program in computational software MATLAB. The novelty of analysis lies in the fact that the impacts of bioconvection with magnetic effects on Burgers nanofluid are taken into account. Moreover, the behaviours of thermal conductivity and diffusivity are discussed in detail. The impacts of activation energy and motile microorganism are also explored. No work has been published yet in the literature survey according to the authors’ knowledge. The current observation is the extension of Khan et al.’s work [51]. Results. The consequences of the relevant parameters, namely, thermophoresis parameter, Brownian motion parameter, the reaction parameter, temperature difference parameter, activation energy, bioconvection Lewis number and Peclet number against the velocity of Burgers nanofluid, temperature profile for nanoliquid, the concentration of nanoparticles, and microorganisms field, have been explored in depth. The reports had major impacts in the development of medications for the treatment of arterial diseases including atherosclerosis without any need for surgery, which may reduce spending on cardiovascular and postsurgical problems in patients. Conclusions. The current investigation depicts that fluid velocity increases for uplifting values of mixed convection parameter. Furthermore, it is analyzed that flow of fluid is risen by varying the amount of Burgers fluid parameter. The temperature distribution is escalated by escalating the values of temperature ratio parameter and thermal conductivity parameter. The concentration field turns down for elevated values of Lewis number and Brownian motion parameter, while conflicting circumstances are observed for the thermophoresis parameter and solutal Biot number. Larger values of Peclet number reduce the microorganism’s field. Physically the current model is more significant in the field of applied mathematics. Furthermore, the current model is more helpful to improve the thermal conductivity of base fluids and heat transfer rate.

Performance analysis of direct absorption-based parabolic trough solar collector using hybrid nanofluids

Addition of a small amount of nanoparticles to the working fluids of a parabolic trough collector does not only enhance the heat transfer properties and thermal conductivity of basefluid but also improves the thermal efficiency of the system. The current investigation presents a comparative analysis of experimental performance of a conventional parabolic trough collector and direct absorption parabolic trough collector for capturing solar thermal energy. Two separate nanomaterials, Al2O3 (with high scattering properties) and CuO (with high absorption properties), were selected for the preparation of the hybrid nanofluids. A customized experimental setup was developed to evaluate their photothermal performance. The nanofluid samples in the concentration range of 0.01–0.5 wt% were investigated under a natural solar flux. Thermal efficiency of conventional parabolic trough collector was increased by 31% using hybrid nanofluid as compared to basefluid. The thermal efficiency enhancement of direct absorption parabolic trough collector was observed as 19% higher than that of conventional parabolic trough collector due to higher heat transfer rate, solar trapping and volumetric absorption. These binary nanofluids can be potential working fluids in various applications based on solar thermal energy.

Nanofluids thermal conductivity prediction applying a novel hybrid data-driven model validated using Monte Carlo-based sensitivity analysis

Accurate estimation of the thermal conductivity of nanofluids plays a key role in industrial heat transfer applications. Currently available experimental and empirical relationships can be used to estimate thermal conductivity. However, since the environmental conditions and properties of the nanofluids constituents are not considered these models cannot provide the expected accuracy and reliability for researchers. In this research, a robust hybrid artificial intelligence model was developed to accurately predict wide variety of relative thermal conductivity of nanofluids. In the new approach, the improved simulated annealing (ISA) was used to optimize the parameters of the least-squares support vector machine (LSSVM-ISA). The predictive model was developed using a data bank, consist of 1800 experimental data points for nanofluids from 32 references. The volume fraction, average size and thermal conductivity of nanoparticles, temperature and thermal conductivity of base fluid were selected as influent parameters and relative thermal conductivity was chosen as the output variable. In addition, the obtained results from the LSSVM-ISA were compared with the results of the radial basis function neural network (RBF-NN), K-nearest neighbors (KNN), and various existing experimental correlations models. The statistical analysis shows that the performance of the proposed hybrid predictor model for testing stage (R = 0.993, RMSE = 0.0207) is more reliable and efficient than those of the RBF-NN (R = 0.970, RMSE = 0.0416 W/m K), KNN (R = 0.931, RMSE = 0.068 W/m K) and all of the existing empirical correlations for estimating thermal conductivity of wide variety types of nanofluids. Finally, robustness and convergence analysis were conducted to evaluate the model reliability. A comprehensive sensitivity analysis using Monte Carlo simulation was carried out to identify the most significant variables of the developed models affecting the thermal conductivity predictions of nanofluids.

Potential energy and atomic stability of H2O/CuO nanoparticles flow and heat transfer in non-ideal microchannel via molecular dynamic approach: the Green–Kubo method

It is interesting to investigate the number of nanoparticle (NP) and temperature effects on H2O/CuO nanofluid thermal conductivity and the atomic manner in a non-ideal microchannel. The outcomes of the physical features of these structures were supposed using molecular dynamic (MD) method and LAMMPS simulation package. For the study of dynamic properties of nanofluid microchannel system, parameters such as temperature profiles, velocity, density, and potential energy of H2O/CuO atomic structures were calculated. Furthermore, the thermal conductivity of these structures was estimated by the Green–Kubo method in the final step. This simulation shows that nanoparticle number is a crucial parameter in nanofluid movement in a microchannel. Theoretically, via adding CuO nanoparticle to H2O fluid, the maximum rate of velocity, density, temperature, and thermal conductivity of base fluid increases to 0.106 g cm−3, 29.810 A ps−1, 549.217 K, and 0.81 W mK−1 rates, respectively. Moreover, the temperature increase of Cu microchannel increases the rate of density, velocity, temperature, and thermal conductivity of CuO nanofluids.

Influence of polymer washing on thermal conductivity enhancement of Cu nanofluids

AbstractThis work aims at enhancing the thermal conductivity of base fluids (water and methanol) through successive washing of polymers from the surface of polyvinylpyrollidone (PVP)‐stabilized copper (Cu) nanoparticles. Cu nanofluids were successfully synthesized and characterized using transmission electron microscope and UV–vis spectrophotometer. Thermal conductivity of freshly prepared Cu nanofluid shows ~10% enhancements. The poor enhancement in thermal conductivity is due to the presence of thick polymer coating on the surface of nanoparticles. A new technique has been developed to erode the polymers from the nanoparticle surface by repeated washing and redispersion. After one‐time washing and redispersion, the thermal conductivity of nanofluid has been increased to 0.732 W/mK (~22% enhancements). Greater enhancement (~30.34%) has been achieved after three times continuous washing and redispersion. Finally, the experimental values of thermal conductivity were compared and validated against the existing Maxwell effective model.

Model Konduktivitas Termal Nanofluida Berdasarkan Grup Tak-Berdimensi dengan Parameter Termofisika Kompleks

This article presents a model of thermal conductivity of nanofluids based on dimensionless-group methods. In addition to the thermal conductivity of base fluids and nanoparticles, nanoparticle diameter, temperature, and volume fraction of nanoparticles, the proposed model involves several thermophysical parameters such as specific heat, density, and viscosity. The reason for the development of the model requires complex thermophysical parameters because, based on the experiments, these parameters determine the thermal conductivity of nanofluids. Validation of the model through comparison of the model with the experimental results shows that the models that have non-linear correlation have good accuracy in predicting the thermal conductivity of nanofluids.

Thermal Conductivity Modeling of Nanofluids Contain MgO Particles by Employing Different Approaches

The existence of solid-phase nanoparticles remarkably improves the thermal conductivity of the fluids. The enhancement in this property of the nanofluids is affected by different items such as the solid-phase volume fraction and dimensions, temperature, etc. In the current paper, three different mathematical models, including polynomial correlation, Multivariate Adaptive Regression Spline (MARS), and Group Method of Data Handling (GMDH), are applied to forecast the thermal conductivity of nanofluids containing MgO particles. The inputs of the model are the base fluid thermal conductivity, volume concentration, and average dimension of solid-phase, and nanofluids’ temperature. Comparing the proposed models revealed higher confidence of GMDH in estimating the thermal conductivity, which is attributed to its complicated structure and more appropriate consideration of the input’s interaction. The values of R-squared for the correlation, MARS, and GMDH are 0.9949, 0.9952, and 0.9991, respectively. In addition, based on the sensitivity analysis, the effect of thermal conductivity of the base fluid on the overall thermal conductivity of nanofluids is more remarkable compared with the other inputs such as volume fraction, temperature, and dimensions of the particles which are used as the inputs of the models.

Effect of TiO2 and Al2O3-ethylene glycol-based nanofluids on cutting temperature and surface roughness during turning process of AISI 1018

This paper presents the effect of TiO2 and Al2O3-ethylene glycol based nanofluids on cutting temperature and surface roughness during turning process of AISI 1018. Minimum quantity lubrication (MQL) method has been recognized in minimizing the usage of cutting fluid, as a step to achieve cleaner environment and sustainable machining. However, the low thermal conductivity of base fluid in minimum quantity lubrication system caused the insufficient removal of heat generated in cutting zone. Addition of nanoparticles to the base fluid was then introduced to enhance the performance of cutting fluids. In this study, the machinability of AISI 1018 (mild steel) was investigated under dry machining and nanofluid minimum quantity lubrication method. Two types of nanofluids (TiO2 and Al2O3 nanofluid) with concentration 0.05, 0.15 and 0.3 wt.% were used in this study. The experiments were conducted on lathe machine, using tungsten carbide as cutting tool. Three cutting speed (350, 550 and 750 m/min), three depth of cut (0.5, 1.0 and 1.5 mm) and fixed minimum quantity lubrication system nozzle pressure (5 bar) were applied throughout turning operation. To determine the relationship between machining parameters and cutting temperature and surface roughness values were measured. Based on results obtained, the cutting temperature of workpieces with usage of nanofluids in MQL system gave lower value compared to dry machining. The surface roughness of machined parts was also improved under NFMQL methods. In conclusion, when the nanofluid-MQL method was employed, the amount of cutting fluid was reduced and machining performance improved.