PSS). SANS and USANS patterns of the different samples containing 10, 30, and 50 wt% SWCNTs were measured. These curves were then utilized to calculate statistical two-point correlation functions of the nanostructure. These functions along with the geometrical information extracted from SANS data and scanning electron microscopy images were used to reconstruct a representative volume element (RVE) nanostructure. Generated RVEs can be used for simulations of various mechanical and physical properties. This work, therefore, introduces a framework for the reconstruction of 3D RVEs of high volume faction nanocomposites containing high aspect ratio fillers from scattering experiments.

Nanofluids consist of liquid and solid (nanoparticles), therefore, they can be classified as two-component flow, which brings up different approaches for simulation purposes. In this study, heat transfer and hydro-dynamic features of nanoparticles in a laminar nanofluid flow in a vertical tube are investigated numerically via Lagrangian and Eulerian approaches.Discrete Phase Model (DPM) in Lagrangian approach simulates the motion of particles through base flow with force balance equation, therefore, no needs empirical correlations at least for the thermo-physical properties (which they are not universal and change for different fluids and/or nanoparticles). Although, general empirical or analytical correlations are needed for some interactions between solid and liquid such as Thermophoresis, Brownian and clustering effects, but they are not that extensive and can be employed in most of the cases.Mixture model in Eulerian approach provides more reliable results, but it highly depends on the accuracy of the correlations for the thermo-physical properties of the nanofluid. In present study, three common types of nanofluids consist of Alumina, Zirconia and Silica nanoparticles (up to 2.76% of volume fraction) are studied and the results are compared with experimental works. Numerical simulations indicate that the findings are in good agreement with the measured heat transfer coefficient for DPM. Consequently, DPM can be highly recommended for simulation study due to the strength and simplicity. It has been also observed that the effects of nanoparticles in each computational cell need to be distributed to the other neighbourhood cells. Pressure losses results predicted by DPM were found reliable for volume fraction less than 3%, no matter the types of nanoparticles or diameter. DPM velocity profiles show that the slip velocity between nanoparticles and base flow is not negligible.

Carbon fibers significantly improve thermal and mechanical properties of nanocomposites, and many researchers have focused their studies on determining the effective thermal and mechanical properties of these composites. Much effort has gone into determining how mechanical loading changes the effective properties of the nanocomposite, and studying its behavior under further mechanical loading. In the present study, a computer simulation of three different volume fractions of carbon fibers in natural rubber was subjected to eight loading scenarios, each, to study the effect of loading conditions on the effective thermomechanical properties of the nanocomposites. Results suggest that mechanical loading can improve the effective thermal conductivity and increase the elastic modulus of the nanocomposite.

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It is essential to investigate the appropriate model for simulating nanofluid flow for different flow regimes because, at present, most previous studies do not agree with each other. It was, therefore, the purpose of this study to present a Computational Fluids Dynamics (CFD) investigation of heat transfer coefficients of internal forced convective flow of nanofluids in a circular tube subject to constant wall heat flux boundary conditions. A complete threedimensional (3D) cylindrical geometry was used. Laminar and turbulent flow regimes were considered. Three two-phase models (mixture model, discrete phase model (DPM) and the combined model of discrete and mixture phases) and the single-phase homogeneous model (SPM) were considered with both constant and variable properties. For the turbulent flow regime, it was found that the DPM with variable properties closely predicted the local heat transfer coefficients with an average deviation of 9%, and the SPM deviated from the DPM model by 2%. It was also found that the mixture and the combined discrete and the mixture phase model gave unrealistic results. For laminar flow, the DPM model with variable properties predicted the heat transfer coefficients with an average deviation of 9%.

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The explanation of abnormal enhancement of transported energy in colloidal nanoparticles in a liquid has sparked much interest in recent years. The complexity comes from the inter-particle phenomenon and cluster formation. The process of nanoparticle aggregation, which is caused by convective phenomena and particle-to-particle interaction energy in a flow, is investigated in this research. Therefore, the probability of collision and cohesion among clusters is modelled, as stated in this research. ANSYS-Fluent 17 CFD tools are employed to implement a new method of nanoparticle aggregation, new essential forces, new heat law and cluster drag coefficient. The importance of the interaction forces is compared to drag force, and essential forces are considered in coupling between nanoparticles and fluid flow. An important parameter is defined for the surface energy density regarding the attractive energy between the double layer and surrounding fluid to capture the cohesion of particles. Particles' random migration is also presented through their angular and radial displacement. The analyses for interactions show the significance of Brownian motion in both particles' migration and coupling effects in the fluid. However, nanoparticles are pushed away from walls due to repulsive forces, and Brownian motion is found to be effective mainly on angular displacement around the tube centreline. The attractive energy is found to be dominant when two clusters are at an equal distance. Hence, the cluster formation in convective regions should be taken into account for modelling purposes. A higher concentrated region also occurs midway between the centreline and the heated wall.

The impact of presence of nano-scale particles inside a flow between two flat plates which known as Poiseuille flow is numerically analyzed. Nanofluids have been investigated in the past few years mainly by considering the heat transfer aspect in a fully developed section of internal flows, rather than detailing the hydrodynamic and thermal developing viewpoint of nanofluid. In other words, this research will focus on the fundamental understanding of developing nanoparticles flows in hydrodynamic and thermal boundary layers in the entrance region. Therefore, flow between two flat plates is numerically studied here by injecting and tracking nanoparticles from inlet to outlet of the channel. The flow is kept in the laminar regime with uniform heat flux applied on the plates. ANSYS Fluent 19.3 is used to numerically solve the continuity and momentum equations, as well as discrete phase modeling for particles. The results showed three major stages in vorticity development in the entrance region. It was found that Brownian motion plays an important role in nanoparticles migration, and close to the wall with the involvement of Thermophoresis. Also, nanoparticles can deviate from flow layers after merging boundary layers.