Weakly permeable micro-tubes are employed in many applications involving heat and/or mass transfer. During these processes, either solute concentration builds up (mass transfer) or steep change in temperature (heat transfer) takes place near the permeable wall causing a change in the viscosity of the fl uid. Results of the present work suggest that such change in viscosity leads to a considerable alteration in the fl ow behavior, and the commonly assumed parabolic velocity profi le no longer exists. To solve the problem numerically, the equation of motion was simplifi ed to represent permeation of incompressible, Newtonian fl uid with changing viscosity through a micro-tube. Even after considerable simplifi cation, the accuracy of the results was the same as that obtained by previously reported results for some specifi c cases using rigorous formulation. The algorithm developed in the present work is found to be numerically robust and simple so that it can be easily integrated with other simulations.
Electrospinning process is proved to be one of the finest fabrication techniques to produce nanofibers. This research deals with the experimental study on the effect of various process parameters of electrospinning technique such as voltage, flow rate, distance (nozzle to collector distance) and concentration, on the development of nanofibers from a new polymer, namely PBAT. Taguchis experimental design was implemented to carry out this research by conducting an L-18 orthogonal array. Taguchi method and Analysis of Variance (ANOVA) were employed to examine the effect of different process parameters simultaneously on the fabrication of nanofibers. The fibers were characterized through scanning electron microscope (SEM) for the measurement of its diameter. The experimental results indicate that all the chosen process parameters had significant influence on the fiber diameter. It was inferred that the concentration and voltage had a very notable impact on the fiber diameter. Confirmation experimental run was performed on the identified optimal setting of the process parameters.
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