Potentials of boiling heat transfer in advanced thermal energy systems

Journal of Thermal Analysis and Calorimetry - Boiling process is a highly efficient mechanism of heat transfer, which has an important role in industrial and domestic sectors. In this process, a...     

Simulation of conjugate radiation–forced convection heat transfer in a porous medium using the lattice Boltzmann method

In this paper, a lattice Boltzmann method is employed to simulate the conjugate radiation–forced convection heat transfer in a porous medium. The absorbing, emitting, and scattering phenomena are fully included in the model. The effects of different parameters of a silicon carbide porous medium including porosity, pore size, conduction–radiation ratio, extinction coefficient and kinematic viscosity ratio on the temperature and velocity distributions are investigated. The convergence times of modified and regular LBMs for this problem are 15 s and 94 s, respectively, indicating a considerable reduction in the solution time through using the modified LBM. Further, the thermal plume formed behind the porous cylinder elongates as the porosity and pore size increase. This result reveals that the thermal penetration of the porous cylinder increases with increasing the porosity and pore size. Finally, the mean temperature at the channel output increases by about 22% as the extinction coefficient of fluid increases in the range of 0–0.03.

     

Inventory control and pricing for perishable products under age and price dependent stochastic demand

Multistage stochastic programming (SP) with both endogenous and exogenous uncertainties is a novel problem in which some uncertain parameters are decision-dependent and others are independent of decisions. The main difficulty of this problem is that nonanticipativity constraints (NACs) make up a significantly large constraint set, growing very fast with the number of scenarios and leading to an intractable model. Usually, a lot of these constraints are redundant and hence, identification and elimination of redundant NACs can cause a significant reduction in the problem size. Recently, a polynomial time algorithm has been proposed in the literature which is able to identify all redundant NACs in an SP problem with only endogenous uncertainty. In this paper, however, we extend the algorithm proposed in the literature and present a new method which is able to make the upper most possible reduction in the number of NACs in any SP with both exogenous and endogenous uncertain parameters. Proving the validity of this method is another innovation of this study. Computational results confirm that the proposed approach can significantly reduce the problem size within a reasonable computation time.     

Determination of the Heat Transfer Coefficient of Metal Oxide Based Water Nanofluids in a Laminar Flow Regime Using an Adaptive Neuro-Fuzzy Inference System

In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al₂O₃, and TiO₂) are loaded into the TO. To measure the thermal performance of nanoparticle-based TO nanofluids at laminar flow and under constant heat flux boundary conditions, an experimental setup was applied. The obtained data clearly demonstrate the positive effect of all nanoparticles on the heat transfer rate of TO. As the most important factor, the heat transfer coefficient of the abovementioned two-phase systems is increased upon increasing both the volume concentration and the flow rate. An adaptive neuro-fuzzy inference system (ANFIS) is applied for modeling the effect of critical parameters on the heat transfer coefficient of nanoparticle-TO based nanofluids numerically. The results are compared with experimental ones for training and test data. The results suggest that the developed model is valid enough and promising for predicting the extant of the heat transfer coefficient. R² and MSE values for all data were 0.990208751 and 108.1150734, respectively. Based on the results, it is obvious that our proposed modeling by ANFIS is efficient and valid, which can be expanded for more general states.     

Offline estimation of 2D crystal lattice parameters by processing the electron diffraction image

Electron diffraction provides useful information about the internal composition of materials and has been in the use of material scientists for more than fifty years. In order to extract useful information from offline diffraction images, they are manually analyzed by using some photometric technique. Manual analysis is however a cumbersome, laborious and difficult task. To reduce the labors of material scientists one can employ image processing techniques to perform automated analysis, due to the well established popularity and clear evidence of widely used image processing techniques. In this work an image processing technique is being proposed for the extraction of 2D unit cell information from diffraction images on one hand and finding the 2D point group contained by the lattices on the other. The technique employs a morphological shrinking operation to find the center of each spot in the underlying preprocessed diffraction image. This is followed by the extraction of eight points with reference to the spot produced by the transmitted electron beam. The resultant nine points, i.e. the extracted eight plus the reference spot generated by the transmitted electron beam, are then subjected to symmetry operations, rotation symmetry and mirror symmetry, in polar coordinate system, to classify the point group of the lattice produced by the electron diffraction. One of the difficult task, even in manual analysis, is to ascertain the exact spot where the transmitted electron beam hit the sample at the time of realization of the image. This has been accurately and intuitively done by employing the notion that the transmitted spot must have greater number of pixels, with the highest gray value, among the diffracted spots. The proposed strategy has been applied to a sample set of various images and the results shows that the technique is efficient in determining the unit cell in 2D and classify the point group with good accuracy.     

Analytical solution of three-dimensional Navier–Stokes equations for the flow near an infinite rotating disk

In this letter, we will consider variational iteration method (VIM) and Padé approximant, for finding analytical solutions of three-dimensional viscous flow near an infinite rotating disk. The solutions is compared with the numerical (fourth-order Runge–Kutta) solution. The results illustrate that VIM–Padé is an appropriate method in solving the systems of nonlinear equations. It is predicted that VIM–Padé can have wide application in engineering problems (especially for boundary-layer and natural convection problems).     

Fabrication and Optimization of Poly(vinyl alcohol)/Zirconium Acetate Electrospun Nanofibers Using Taguchi Experimental Design

This paper presents an investigation regarding poly(vinyl alcohol)/zirconium acetate (organic–inorganic) (PVA/Zrace) nanofibers prepared by electrospinning which could be used as a precursor for fabricating ceramic metal oxide nanofibers. The effect of some processing variables, including polymer solution concentration, tip to collector distance and applied voltage of electrospinning, and the amount of Zrace and their interactions, on the diameter of the nanofibers were studied. Taguchi experimental design and a statistical analysis (ANOVA) were employed and the relationship between experimental conditions and yield levels determined. It was concluded that to obtain a narrow diameter distribution as well as maximum fiber fineness, a polymer concentration of 10 wt%, tip to collector distance of 18 cm and applied voltage of 20 kV variables were the optimum. Furthermore, it was also concluded that the ratio of Zrace (6 g) to PVA solution (10% wt) played an important role for achieving the minimum fiber diameter. Under these optimum conditions, the diameters of the electrospun composite fibers ranged from 86 nm to 381 nm with a diameter average of 193 nm. The experiments were done with Qualitek-4 software with “smaller is better” as the quality characteristics. The optimized conditions showed an improvement in the fibers diameter distribution and the average fibers diameter showed good resemblance with the result predicted using the Taguchi method and the Qualitek-4 software. The ANOVA results showed that all factors had significant effects on the fibers diameter and distribution, but the effect of PVA concentration and zirconium acetate were more significant than the other factors.     

SMFs-supported Pd nanocatalysts in selective acetylene hydrogenation:Pore structure-dependent deactivation mechanism

In the present study,CNFs,ZnO and Al2O3 were deposited on the SMFs panels to investigate the deactivation mechanism of Pd-based catalysts in selective acetylene hydrogenation reaction.The examined supports were characterized by SEM,NH3-TPD and N2adsorption-desorption isotherms to indicate their intrinsic characteristics.Furthermore,in order to understand the mechanism of deactivation,the resulted green oil was characterized using FTIR and SIM DIS.FTIR results confirmed the presence of more unsaturated constituents and then,more branched hydrocarbons formed upon the reaction over alumina-supported catalyst in comparison with the ones supported on CNFs and ZnO,which in turn,could block the pores mouths.Besides the limited hydrogen transfer,N2 adsorption-desorption isotherms results supported that the lowest pore diameters of Al2O3/SMFs close to the surface led to fast deactivation,compared with the other catalysts,especially at higher temperatures.