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This paper aims to present experimental and numerical analyses of fused filament fabrication (FFF) printed parts and show how mechanical characteristics of printed ABS-MG94 (acrylonitrile butadiene styrene) are influenced by the void volume fraction, cooling rate and residual thermal stresses.

Printed specimens were experimentally tested to evaluate the mechanical properties for different printing speeds, and micrographs were taken. A thermo-mechanical finite element model, able to simulate the FFF process, was developed to calculate the temperature fields in time, cooling rate and residual thermal stresses. Finally, the experimental mechanical properties and the microstructure distribution could be explained by the temperature fields in time, cooling rate and residual thermal stresses.

Micrographs revealed the increase of void volume fraction with the printing speed. The variations on voids were associated to the temperature fields in time: when the temperatures remained high for longer periods, less voids were generated. The Young's Modulus of the deposited filament varied according to the cooling rate: it decreased when the cooling rate increased. The influence of the residual thermal stresses and void volume fraction on the printed parts failure was also investigated: in the worst scenarios evaluated, the void volume fraction reduced the strength in 9 per cent, while the residual thermal stresses reduced it in 3.8 per cent.

This work explains how the temperature fields can affect the void volume fraction, Young's Modulus and failure of printed parts. Experimental and numerical results are shown. The presented research can be used to choose printing parameters to achieve desired mechanical properties of FFF printed parts.

In part I of this study a new dry coating analysis was developed relating pigment cluster voids and pigment particle distribution to the pigment cluster dispersion coefficient, C_q, and the critical pigment volume concentration (CPVC). Part II of this study has addressed a wet coating analysis to relate pigment particle size distribution and viscosity in a coating formulation to the pigment cluster dispersion coefficient.

This study introduced the relationships for the wet coating by building on the dry coating evaluations introduced in part I of this study. Part II of this study showed that the CPVC for a solvent based coating can be significantly influenced by a change in the viscosity measured interaction coefficient, σ, as influenced by a change in an additive such as the surfactant concentration in the matrix or polymer phase of the coating. The CPVC was also shown to be strongly influenced by a separate analysis of the pigment particle size distribution to modify the coating viscosity.

It was pointed out recently that an increase in flow additive increased the CPVC but decreased viscosity. Consequently, it was shown theoretically in this study that viscosities compared at the same relative viscosity, η/η₀, and at the same filler composition, f_i, using the generalized viscosity model would require decrease in the interaction coefficient, σ, to increase the global volume fraction of filler or pigment, Φ_F. This implied that a measurement of the interaction coefficient, σ, should be a direct measure of the ability of the CPVC to be modified. A minimum viscosity from the generalised viscosity model also resulted at the maximum packing fraction, which in turn was found to increase the CPVC of the coating. Consequently, part II of this study has yielded a useful relationship between the cluster dispersion coefficient, C_q, and the interaction coefficient, σ, from the generalised viscosity model.

While the experimental measurement of the parameters to isolate the clustering concepts introduced in this study may be difficult, it is expected that better quantitative measurement of clustering concepts will eventually prove to be very beneficial to providing improved suspension applications including coatings. The close relationship introduced in this study between clustering concepts and viscosity should provide an improved ability to measure the parameters to isolate clustering in coatings and other suspension applications.

The theoretical relationship developed in this study between the pigment cluster dispersion coefficient, C_q, and CPVC and the theoretical and experimental relationship between CPVC and the viscosity interaction coefficient, σ, inferred a direct relationship between C_q and the viscosity interaction coefficient, σ. Consequently, it was shown that the theoretical pigment cluster model developed in this study could be directly related to the experimental matrix additive composition controlling viscosity in a coating formulation. The practical implication is that the measurement tools introduced in this study should significantly influence future suspension formulations to provide better measurement and control of clustering and viscosity in coatings and other suspension applications.

Part II of this study has shown how a useful relationship can be generated between the interaction coefficient, σ, from the generalised viscosity model and the pigment cluster dispersion coefficient, C_q, developed in part I of this study. In addition, this study also showed that effective control of the CPVC of a coating can be modified by judicious control of the interaction coefficient using pigment particle size distribution and/or viscosity control additives in a wet coating analysis.

The tensile behavior of additively manufactured nylon-based carbon fiber-reinforced composites (CFRP) is an important criterion in aerospace and automobile structural design. So, this study aims to evaluate and validate the tensile stiffness of printed CFRP composites (low- and high-volume fraction fiber) using the volume average stiffness (VAS) model in consonance with experimental results. In specific, the tensile characterization of printed laminate composites is studied under the influence of raster orientations and process-induced defects.

CFRP composite laminates of low- and high-volume fraction carbon fiber of different raster orientations (0°, ± 45° and 0/90°) were fabricated using the continuous fiber 3D printing technique, and tensile characteristics of laminates were done on a universal testing machine with the crosshead speed of 2 mm/min. The induced fracture surface of laminates due to tensile load was examined using the scanning electron microscopy technique.

The VAS model can predict the tensile stiffness of printed CFRP composites with different raster orientations at an average prediction error of 5.94% and 10.58% for low- and high-volume fiber fractions, respectively. The unidirectional CFRP laminate composite with a high-volume fraction (50%) of carbon fiber showed 50.79% more tensile stiffness and 63.12% more tensile strength than the low-volume fraction (26%) unidirectional composite. Fiber pullout, fiber fracture and ply delamination are the major failure appearances observed in fracture surfaces of laminates under tensile load using scanning electron microscopy.

This investigation demonstrates the novel methodology to study specific tensile characteristics of low- and high-volume fraction 3D printed CFRP composite.

The purpose of this paper is to numerically simulate the nanofluid boiling inside a tube in turbulent flow regime and to investigate the effect of adding volume faction of CuO nanoparticles on the boiling process.

To make sure the accuracy of the obtained numerical results, the results of this paper have been compared with the experimental results and an acceptable coincidence has been achieved. In the current paper, by Euler–Euler method, the phase change of boiling phenomenon has been modeled. The presented results are the local Nusselt number distribution, temperature distribution of wall, the distribution of volume fraction of vapor phase and fluid temperature at the center of the tube.

The obtained results indicate that using nanofluid is very effective in the postponement of the boiling process. Hence, by change the amount of volume fraction of nanoparticles in base fluid, the location of phase change and bubble creation are changed. Also, at the Reynolds numbers of 50,000, 100,000 and 150,000 with the volume fraction of 2 per cent, the beginning locations of phase change process are, respectively, 2D, 10D and 13D, and for the volume fraction of 4 per cent, the beginning locations of phase change are 4D, 18D and 19D, respectively. These results indicate that, as the volume fraction of nanoparticles increases, the location of the start of the phase change process is postponed that this issue causes the increment of heat transfer from wall to fluid and the reduction of wall temperature. In general, it can be stated that, in boiling flows, using nanofluid because of the delay in boiling phenomenon has a good effect on heat transfer enhancement of heated walls. Also, the obtained results show that, by increasing Reynolds number, the created vapor phase reduces that leads to increase of the Nusselt number.

The paper investigates the effect of using nanofluid in phase change process of cooling fluid.

This study aims to investigate the insights of soot formation such as rate of soot coagulation, rate of soot nucleation, rate of soot surface growth and soot surface oxidation in ethylene/hydrogen/nitrogen diffusion jet flame at standard atmospheric conditions, which is very challenging to capture even with highly sophisticated measuring systems such as Laser Induced Incandescence and Planar laser-induced fluorescence. The study also aims to investigate the volume of soot in the flame using soot volume fraction and to understand the global correlation effect in the formation of soot in ethylene/hydrogen/nitrogen diffusion jet flame.

A large eddy simulation (LES) was performed using box filtered subgrid-scale tensor. A filtered and residual component of the governing equations such as continuity, momentum, energy and species are resolved and modeled, respectively. All the filtered and residual components are numerically solved using the ILU method by considering PISO pressure–velocity solver. All the hyperbolic flux uses the QUICK algorithm, and an elliptic flux uses SOU to evaluate face values. In all the cases, Courant–Friedrichs–Lewy (CFL) conditions are maintained unity.

The findings are as follows: soot volume fraction (SVF) as a function of a flame-normalized length for three different Reynolds number configurations (Re = 15,000, Re = 8,000 and Re = 5,000) using LES; soot gas phase and particulate phase insights such as rate of soot nucleation, rate of soot coagulation, rate of soot surface growth and soot surface oxidation for three different Reynolds number configurations (Re = 15,000, Re = 8,000 and Re = 5,000); and soot global correction using total soot volume in the flame volume as a function of Reynolds number and Froude number.

The originality of this study includes the following: coupling LES turbulent model with chemical equilibrium diffusion combustion conjunction with semi-empirical Brookes Moss Hall (BMH) soot model by choosing C6H6 as a soot precursor kinetic pathway; insights of soot formations such as rate of soot nucleation, soot coagulation rate, soot surface growth rate and soot oxidation rate for ethylene/hydrogen/nitrogen co-flow flame; and SVF and its insights study for three inlet fuel port configurations having the three different Reynolds number (Re = 15,000, Re = 8,000 and Re = 5,000).

Effective cooling is one of the challenges for photovoltaic thermal (PVT) systems to maintain the PV operating temperature. One of the best ways to enhance rate of heat transfer of the PVT system is using advanced working fluids such as nanofluids. The purpose of this research is to develop a numerical model for designing different form of thermal collector systems with different materials. It is concluded that PVT system operated by nanofluid is more effective than water-based PVT system.

In this research, a three-dimensional numerical model of PVT with new baffle-based thermal collector system has been developed and solved using finite element method-based COMSOL Multyphysics software. Water-based different nanofluids (Ag, Cu, Al, etc.), various solid volume fractions up to 3 per cent and variation of inlet temperature (20-40°C) have been applied to obtain high thermal efficiency of this system.

The numerical results show that increasing solid volume fraction increases the thermal performance of PVT system operated by nanofluids, and optimum solid concentration is 2 per cent. The thermal efficiency is enhanced approximately by 7.49, 7.08 and 4.97 per cent for PVT system operated by water/Ag, water/Cu and water/Al nanofluids, respectively, compared to water. The extracted thermal energy from the PVT system decreases by 53.13, 52.69, 42.37 and 38.99 W for water, water/Al, water/Cu and water/Ag nanofluids, respectively, due to each 1°C increase in inlet temperature. The heat transfer rate from heat exchanger to cooling fluid enhances by about 18.43, 27.45 and 31.37 per cent for the PVT system operated by water/Al, water/Cu, water/Ag, respectively, compared to water.

This study is original and is not being considered for publication elsewhere. This is also not currently under review with any other journal.

This study aims to numerically investigate the heat transfer and laminar forced and two-phase flow of Water/Cu nanofluid in a rectangular microchannel with oblique ribs with angle of attacks equal to 0-45°. This simulation was conducted in the range of Reynolds numbers of 5-120 in volume fractions of 0, 2 and 4 per cent of solid nanoparticles in three-dimensional space.

This study investigates the effect of the changes of angle of attack of rectangular rib on heat transfer and hydrodynamics of two-phase flow. This study was done in three-dimensional space and simulation was done with finite volume method. SIMPLEC algorithm and second-order discretization of equations were used to increase the accuracy of results. The usage of nanofluid, application of rips with different angles of attacks and using the two-phase mixture method is the distinction of this paper compared with other studies.

The results of this research revealed that the changing angle of attack of ribs is an effective factor in heat transfer enhancement. On the other hand, the existence of rib on the internal surfaces of a microchannel increases friction coefficient. By increasing the volume fraction of nanoparticles, due to the augmentation of fluid density and viscosity, the pressure drop increases significantly. For all of the angle of attacks studied in this paper, the maximum rate of performance evaluation criterion has been obtained in Reynolds number of 30 and the minimum amount of performance evaluation criterion was been obtained in Reynolds numbers of 5 and 120.

Many studies have been done in the field of heat transfer in ribbed microchannel. In this paper, the laminar flow in the ribbed microchannel Water/Cu nanofluid in a rectangular microchannel by using two-phase mixture method is numerically investigated with different volume fractions (0-4 per cent), Reynolds numbers (5-120) and angle of attacks of rectangular rib in the indented microchannel (0-45°).

The well-known discrete methods of computational fluid dynamics (CFD), lattice Boltzmann method (LBM), cellular automata (CA), volume-of-fluid (VoF) and others rely on several parameters describing the boundary or the surface. Some of them are vector normal to the surface, coordinates of the point on the surface and the curvature. They are necessary for the reconstruction of the real surface (boundary) based on the values of the volume fractions of several cells. However, the simple methods commonly used for calculations of the vector normal to the surface are of unsatisfactory accuracy. In light of this, the purpose of this paper is to demonstrate a more accurate method for determining the vector normal to the surface.

Based on the thesis that information about the volume fractions of the 3 × 3 cell block should be enough for normal vector determination, a neural network (NN) was proposed for use in the paper. The normal vector and the volume fractions of the cells themselves can be defined on the basis of such variables as the location of the center and the radius of the circumference. Therefore, the NN is proposed to solve the inverse problem – to determine the normal vector based on known values of volume fractions. Volume fractions are inputs of NNs, while the normal vector is their output. Over a thousand variants of the surface location, orientations of the normal vector and curvatures were prepared for volume fraction calculations; their results were used for training, validating and testing the NNs.

The simplest NN with one neuron in the hidden layer shows better results than other commonly used methods, and an NN with four neurons produces results with errors below 1° relative to the orientation of the normal vector; for several cases, it proven to be more accurate by an order of magnitude.

The method can be used in the CFD, LBM, CA, VoF and other discrete computational methods. The more precise normal vector allows for a more accurate determination of the points on the surface and curvature in further calculations via the surface or interface tracking method. The paper contains the data for the practical application of developed NNs. The method is limited to regular square or cuboid lattices.

The paper presents an original implementation of NNs for normal vector calculation connected with CFD, LBM and other application for fluid flow with free surface or phase transformation.

Carbon nanotubes (CNTs) with exceptional mechanical, thermal and electrical properties are considered to be ideal for reinforcing high-performance structures. The interfacial stresses between the CNTs and surrounding matrix are important phenomena which critically govern the mechanical properties of CNTs-reinforced nanocomposites. A number of methods have been proposed to investigate the stress transfer across the CNT/matrix interface, such as experimental measurement and molecular dynamics (MDs). Experimental tests are difficulty and expensive. MDs simulations, on the other hand, are computationally inefficient. The purpose of this paper is to present a reasonably simplified model. Incorporating the simplified model, the analytical expressions of the interface stresses including the shear stress and longitudinal normal stress are obtained.

The analytical model consists of two concentric cylinders, namely a single-walled carbon nanotube (SWCNT) cylinder and a matrix cylinder, as the representative volume element (RVE). The interfacial stress analysis is performed using the shear lag model for the axisymmetric RVE. Analytical solutions for the normal stresses in the SWCNT and matrix, and the interfacial shear stress across the SWCNT/matrix interface are obtained. The proposed model has a great ability to theoretical prediction of the stress transfer between the matrix and CNTs.

In order to demonstrate the simulation capabilities of the proposed model, parametric studies are conducted to investigate the effects of the volume fraction of SWCNT and matrix modulus on the stress transfer. The axial stress in the matrix is decreasing with the increase of the volume fraction and decrease of the matrix modulus. As a result of more loads can be transferred to the SWCNT for a large volume fraction and small matrix modulus. These results show that using a large volume fraction and a small matrix modulus improves the efficiency of the stress transfer from the matrix to the CNTs.

A simple but accurate model using a simplified 2D RVE for characterizing the stress transfer in CNT-reinforced nanocomposites is presented. The predictions from the current method compare favourably with those by existing experimental, analytical and computational studies. The simple and explicit expressions of the interfacial stresses provide valuable analysis tools accessible to practical users.

The importance of maximizing the particle packing fraction in a suspension by maximizing average particle size ratio of D₅/D₁ has been adequately shown to be important as previously reported in the literature. This study aims to extend that analysis to include the best formulation approach to maximize the packing fraction with a minimum number of monodisperse particle sizes.

An existing model previously developed by this author was modified theoretically to optimize the ratio used between consecutive monodisperse particle sizes. This process was found to apply to a broad range of particle configurations and applications. In addition, five different approaches for maximizing average particle size ratio D̅₅/D̅₁ were addressed for blending several different particle size distributions. Maximizing average particle size ratio D̅₅/D̅₁ has been found to result in an optimization of the packing fraction. Several new concepts were also introduced in the process of maximizing the packing fraction for these different approaches.

The critical part of the analysis to maximize the packing fraction with a minimum number of particles was the theoretical optimization of the ratio used between consecutive monodisperse particle sizes. This analysis was also found to be effectively independent of the maximum starting particle size. This study also clarified the recent incorrect claim in the literature that Furnas in 1931 was the first to generate the maximum theoretical packing fraction possible for n different particles that was actually originally developed in conjunction with the Sudduth generalized viscosity equation. In addition, the Furnas generated equation was also shown to give significantly different results from the Sudduth generated equation.

Experimental data involving monodisperse particles of different blends with a minimum number of particle sizes that are truly monodisperse are often extremely difficult to obtain. However, the theoretical general concepts can still be applicable.

The expanded model presented in this article provides practical guidelines for blending pigments using a minimum number of monodisperse particle sizes that can yield much higher ratios of the particle size averages D̅₅/D̅₁ and thus potentially achieve significantly improved properties such as viscosity.

The model presented in this article provides the first apparent guidelines to control the blending of pigments in coatings by the optimization of the ratio used between consecutive monodisperse particle sizes. This analysis was also found to be effectively independent of the maximum starting particle size.