فهرست مطالب

Transport Phenomena in Nano and Micro Scales - Volume:4 Issue:2, 2016
  • Volume:4 Issue:2, 2016
  • تاریخ انتشار: 1395/05/03
  • تعداد عناوین: 7
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  • R. Ansari, M.K. Hassanzadeh Aghdam Pages 1-8
    A three-dimensional micromechanics-based analytical model is developed to study thermo mechanical properties of polymer composites reinforced with randomly distributed silica nanoparticles. Two important factors in nanocomposites modeling using micromechanical models are nanoparticle arrangement in matrix and interphase effects. In order to study these cases, representative volume element (RVE) of nanocomposites is extended to c×r×h nano-cells in three dimensions and consists of three phases including nanoparticles, polymer matrix and interphase between the nanoparticles and matrix. Nanoparticles are surrounded by the interphase in all composites. Effects of volume fraction, aspect ratio and size of nanoparticle on the effective thermo-mechanical response of the nanocomposite are studied. Also, the effects of polymer matrix properties and interphase including its elastic modulus and thickness are theoretically investigated in detail. It is revealed that when nanoparticles are randomly distributed in the matrix and interphase effects are considered, the results of present micromechanical model are in very good agreement with experimental data.
    Keywords: Interphase, Micromechanics, Nanocomposite, Random distribution, Thermo, mechanical properties
  • H. Safikhani, A.R. Zare Mehrjardi, M. Safari Pages 9-16
    In the present study, numerical study of Al2O3-water nanofluid flow in different coiled wire inserted tubes are performed to investigate the effects of inserting coiled wires in tubes on the fluid dynamic and heat transfer performance ofv nanofluids. The numerical simulations of nanofluids are performed using two phase mixture model. The flow regime and the wall boundary conditions are assumed to be laminar and constant heat flux respectively. The effects of inserting coiled wires in tubes on different parameters such as heat transfer coefficient, pressure drop, temperature distribution, velocity distribution and secondary flows are presented and discussed. The results show that using coiled wire in tubes leading to increase in ℎ about 13.44% but increase the Δp about 14.66% with respect to the flow without nanofluid and coiled wire. Similarly, using nanofluid leading to increase in ℎ about 5.52% but increase the Δp about 8.92%. Finally, using both of the mentioned heat transfer enhancement mechanisms leading to increase in ℎ about 17.51% but increase the value of Δp about 22.86%.
    Keywords: CFD, Coiled wires, Mixture model, Nanofluid, Two phase model
  • E. Sattari, M. Aghajani Delavar, K. Sedighi Pages 17-27
    In present paper acombination of three-dimensional isothermal and two-dimensional non isothermal Lattice Boltzmann Method have been used to simulate the motion of bubble and effect of wetting properties of the surface on bubble separation. By combining these models, three-dimensional model has been used in two-dimension for decreasing the computational cost. Firstly, it has been ensured that the surface tension effect and Laplace law for two-density ratio 50 and 1000 have been properly implemented. Secondly, by simulation of static droplet in different conditions wettability, integrity applied equations has been investigated.Thirdly, effect of governing dimensionless numbers such as Etvos number and Morton number on Reynolds number and terminal shape of bubble have been investigated.Different flow patterns in various dimensionless numbers have been obtained and by changing the dimensionless number, terminal change of bubble’s shape has been seen. Finally, the impact of wettability of surface on departure of bubble from wall under buoyancy force in different dimensionless numbers has been studied.
    Keywords: Etvos Number, Inamuro Model, Lattice Boltzmann Method, Morton Number, Two Phase Flow, Wettability
  • P. Elyasi, A. R. Shateri Pages 28-40
    Laminar boundary layer flow and heat transfer of Newtonian nanofluid over a stretching sheet with the sheet velocity distribution of the form (UW=cXβ) and the wall temperature distribution of the form (TW=T∞楺 ) for the steady magnetohydrodynamic (MHD) is studied numerically. The governing momentum and energy equations are transformed to the local non-similarity equations using the appropriate transformations. The set of ODEs are solved using Keller–Box implicit finite-difference method. The effects of several parameters, such as magnetic parameter, volume fraction of different nanoparticles (Ag, Cu, CuO, Al2O3 and TiO2), velocity parameter, Prandtl number and temperature parameter on the velocity and temperature distributions, local Nusselt number and skin friction coefficient are examined. The analysis reveals that the temperature profile increases with increasing magnetic parameter and volume fraction of nanofluid. Furthermore, it is found that the thermal boundary layer increases and momentum boundary layer decreases with the use of water based nanofluids as compared to pure water. At constant volume fraction of nanoparticles, it is also illustrated that the role of magnetic parameter on dimensionless temperature becomes more effective in lower value.
    Keywords: Boundary Layer Flow, MHD, Nanofluid, Stretching Sheet
  • A. Hosseinian Naeini, J. Baghbani Arani, A. Narooei, R. Aghayari, H. Maddah Pages 41-46
    Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally conductive solids into liquids. In this study, new model to predict nanofluid thermal conductivity based on Artificial Neural Network. A two-layer perceptron feedforward neural network and backpropagation Levenberg-Marquardt (BP-LM) training algorithm were used to predict the thermal conductivity of the nanofluid. To avoid the preprocess of network and investigate the final efficiency of it, 70% data are used for network training, while the remaining 30% data are used for network test and validation. Fe2O3 nanoparticles dispersed in waster/glycol liquid was used as working fluid in experiments. Volume fraction, temperature, nano particles and base fluid thermal conductivities are used as inputs to the network. The results show that ANN modeling is capable of predicting nanofluid thermal conductivity with good precision. The use of nanotechnology to enhance and improve the heat transfer fluid and the cost is exorbitant.It can play a major role in various industries, particularly industries that are involved in that heat.
    Keywords: Nanofluid, Neural Network, Thermal Conductivity
  • N. Hedayati, A. Ramiar Pages 47-53
    In this paper, unsteady two phase simulation of nanofluid flow and heat transfer between moving parallel plates, in presence of the magnetic field is studied. The significant effects of thermophoresis and Brownian motion have been contained in the model of nanofluid flow. The three governing equations are solved simultaneously via Galerkin method (GM). Comparison with other works indicates that this method is very applicable to solve these problems. The semi analytical analysis is accomplished for different governing parameters in the equations e.g. the squeeze number, Eckert number and Hartmann number. The results showed that skin friction coefficient value increases with increasing Hartmann number and squeeze number in a constant Reynolds number. Also, it is shown that the Nusselt number is an incrementing function of Hartmann number while Eckert number is a reducing function of squeeze number .This type of results can help the engineers to make better and researchers to investigate faster and easier.
    Keywords: Brownian, Eckert number, Galerkin method (GM), Hartmann number, Nanofluid, Thermophoresis
  • A. Pourasghar, A. Ghorbanpour Arani, S. Kamarian Pages 54-58
    The present paper deals with the dynamic behavior of nano-column subjected to follower force using the nonlocal elasticity theory. The nonlocal elasticity theory is used to analyze the mechanical behavior of nanoscale materials. The used method of solution is the Differential Quadrature Method (DQM). It is shown that the nonlocal effect plays an important role in the vibrational behavior of nano-columns. The results can provide useful guidance for the study and design of the next generation of nanodevices and could be useful in biomedical and bioengineering applications as well as in other fields related with the nanotechnology.
    Keywords: differential quadrature method (DQM), nano, column, nonlocal elasticity, Vibration