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The use of natural fiber composites is growing at a fast rate in terms of industrial applications due to their eco-friendly, recyclable, renewable nature, and low density/costs. Recently, jute fiber is being used as a reinforcement material in the development of natural fiber reinforced plastics for engineering applications. Drilling is an essential machining operation that is frequently performed for making of holes in composite structures to facilitate assembly of several components into a complex part. The literature reviews indicate that only a few of research articles investigated drilling of natural fiber reinforced composites. Hence, in the present research, drilling of woven jute fiber reinforced polymer composites has been examined. This study aimed at evaluation of cutting parameters and drill bit types effect on thrust force, delamination size, and surface roughness in the jute fiber reinforced polymer composites drilling using an experimental design based on full factorial technique. The percentage contribution of the cutting parameters and drill bit types were determined through the analysis of variance. The optimal setting of these parameters was found through observation. The experimental results indicated that the most significant effect was the drill bit type influencing both delamination factor and surface roughness.

have successfully established. On the other hand, for low powered electronics devices, harvesting energy from the ambient vibrations seems to be an ideal solution due to the definite life span and high cost for replacement of the traditional batteries. Three methods are available for vibration energy harvesting; using electrostatic devices, electromagnetic field and utilizing piezoelectric based materials. The performance of piezoelectric vibration energy harvesters for vibration-to-electricity transduction is more often than other methods, because this method has the highest power density. In other words, it can generate the highest electrical power in the same volume. Compared to other structural forms of beams, a cantilever beam can obtain the maximum deformation and strain under the same conditions. The larger deflection leads to more stress, strain, and consequently a higher output voltage and power. Therefore the vast majority of piezoelectric vibration energy harvesting devices use a cantilever beam structure (Anderson and Sexton 2006;Beeby et al. 2006;Erturk and Inman 2011;Priya and Inman 2009). A cantilever-type energy harvester has been intensively studied and a tapered cantilever has been found to be the optimum design (Matova et al. 2013;Siddiqui 2014;Muthalif and Nordin 2015), because it ensures a large constant strain (and a large power output) in the piezoelectric layer.Most of the previous research works focused on designing a linear vibration resonator, in which the maximum system performance can be achieved when the energy harvester is tuned to match its resonance frequency with the external excitation frequency. If the excitation frequency slightly shifts, the performance of the harvester will dramatically decrease. Since in the majority of practical cases, the vibration in the environment is frequency-varying or totally random with the energy distributed in a wide spectrum, how to increase the bandwidth of mechanical Abstract Power supply is a bottle-neck problem of wireless micro-sensors, especially where the replacement of batteries is impossible or inconvenient. Now piezoelectric material is being used as an additional layer in cantilever beams to harvest vibration energy for self-powered sensors. However, the geometry of a piezoelectric cantilever beam will greatly affects its vibration energy harvesting ability. This paper deduces a remarkably precise analytical formula for calculating the fundamental resonant frequency of trapezoidal V-shaped cantilevers using Rayleigh-Ritz method. This analytical formula, which is very convenient for mechanical energy harvester design based on Piezoelectric effect, is then analyzed using MATLAB as well as finite element methods and validated by ABAQUS simulation. This formula raises a new perspective that, among all the trapezoidal V-shaped cantilevers with uniform thickness, the simplest triangular tapered cantilever, can lead to maximum resonant frequency and highest sensitivity and by increasing the ratio of the trapezoidal bases, the sensitivity dec...

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An artificial neural network (ANN) and a genetic algorithm (GA) are employed to model and optimize cell parameters to improve the performance of singular, intermediate‐temperature, solid oxide fuel cells (IT‐SOFCs). The ANN model uses a feed‐forward neural network with an error back‐propagation algorithm. The ANN is trained using experimental data as a black‐box without using physical models. The developed model is able to predict the performance of the SOFC. An optimization algorithm is utilized to select the optimal SOFC parameters. The optimal values of four cell parameters (anode support thickness, anode support porosity, electrolyte thickness, and functional layer cathode thickness) are determined by using the GA under different conditions. The results show that these optimum cell parameters deliver the highest maximum power density under different constraints on the anode support thickness, porosity, and electrolyte thickness.

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