This experimental study was carried out based on the nanotechnology approach to enhance the efficacy of engine oil. Atomic and surface structures of graphene oxide (GO) nanoparticles were investigated by using a field emission scanning electron microscope and X-ray diffraction. The nano lubricant was produced by using a two-step method. The stability of nano lubricant was analyzed through dynamic light scattering. Various properties such as thermal conductivity, dynamic viscosity, flash point, cloud point and freezing point were investigated and the results were compared with the base oil (Oil- SAE-50). The results show that the thermal conductivity of nano lubricant was improved compared to the base fluid. This increase was correlated with progressing temperature. The dynamic viscosity was increased by variations in the volume fraction and reached its highest value of 36% compared to the base oil. The cloud point and freezing point are critical factors for oils, especially in cold seasons, so the efficacy of nano lubricant was improved maximally by 13.3% and 12.9%, respectively, compared to the base oil. The flash point was enhanced by 8%, which remarkably enhances the usability of the oil. It is ultimately assumed that this nano lubricant to be applied as an efficient alternative in industrial systems.

A new algorithm based on the lattice Boltzmann method (LBM) and the Control Volume Finite Element Method (CVFEM) is proposed as an hybrid solver for two dimensional transient conduction and radiation heat transfer problems in an optically emitting, absorbing and scattering medium. The LBM was used to solve the energy equation and the CVFEM was used to compute the radiative information. The advantages of the proposed methodology is to avoid problems that confronted when previous techniques are used to predict radiative heat transfer, essentially, in complex geometries and when there is scattering and/or non-black boundaries surfaces. This method combination, which is applied for the first time to solve this unsteady combined mode of heat transfer, has been found to accurately predict the effects of various thermo-physical parameters such as the scattering albedo, the conduction-radiation parameter and the extinction coefficient on temperature distribution. The results of the LBM-CVFEM combination were found to be in excellent agreement with the LBM-CDM (Collapsed Dimension Method)this proposed numerical approach include, among others, simple implementation on a computer, accurate CPU time, and capability of stable simulation.

In recent decades, research utilizing numerical schemes dealing with fluid and nanoparticle interaction has been relatively intensive. It is known that CuO nanofluid with a volume fraction of 0.1 and a special thermal boundary condition with heat supplied to part of the wall increases the average Nusselt number for different aspect ratios ranges and for high Rayleigh numbers. Due to its simplicity, stability, accuracy, efficiency, and ease of parallelization, we use the thermal single relaxation time Bhatnagar-Gross-Krook (SRT BGK) mesoscopic approach D₂Q₉ scheme lattice Boltzmann method in order to solve the coupled Navier–Stokes equations. Convection of CuO nanofluid in a square enclosure with a moderate Rayleigh number of 10⁵ and with new boundary conditions is highlighted. After a successful validation with a simple partial Dirichlet boundary condition, this paper extends the study to deal with linear and sinusoidal thermal boundary conditions applied to part of the wall.