The present investigation is concerned with the reflection in thermo-microstretch elastic solid in the presence of a transverse magnetic field, at the boundary surface. The generalized theories of thermoelasticity developed by Lord and Shulman (L-S) and Green and Lindsay (G-L) theories have been used to investigate the problem. The variations of amplitude ratios with angle of incidence have been shown graphically. It is noticed that the amplitude ratios of the reflected waves are affected by magnetic field, stretch and thermal properties of the medium.
The present investigation aims at fabricating a functionally graded Al-6Cr-Y2O3 composite and its microstructural and property characterization. Al-6Cr-alloys with varying percentage of Y2O3 (5-10 vol. %) have been used to fabricate FGM by powder metallurgy route. The samples were subsequently subjected to solution treatment at 610°C for 4 h followed by artificially aged at 310°C for 4 h. The microstructure, hardness and wear behavior of these FGM have been evaluated. FGM exhibited superior hardness (360 ± 5 VHN) as compared to the unprocessed composites (220 ± 5 VHN) due to the uniform dispersion of Y2O3 particles. Wear resistance of Al-6Cr-10 Y2O3 FGM were compared that of with pure Al-6Cr alloy by dry abrasive wear test. Al-6Cr-10 Y2O3 FGM composites were found to exhibit higher wear resistance with the minimum wear rate of 0.009 mm3/m compared to the Al- 6Cr alloy wear rate 0.02 mm3/m.
In the era of humanoid robotics, navigation and path planning of humanoids in complex environments have always remained as one of the most promising area of research. In this paper, a novel hybridized navigational controller is proposed using the logic of both classical technique and computational intelligence for path planning of humanoids. The proposed navigational controller is a hybridization of regression analysis with adaptive particle swarm optimization. The inputs given to the regression controller are in the forms of obstacle distances, and the output of the regression controller is interim turning angle. The output interim turning angle is again fed to the adaptive particle swarm optimization controller along with other inputs. The output of the adaptive particle swarm optimization controller termed as final turning angle acts as the directing factor for smooth navigation of humanoids in a complex environment. The proposed navigational controller is tested for single as well as multiple humanoids in both simulation and experimental environments. The results obtained from both the environments are compared against each other, and a good agreement between them is observed. Finally, the proposed hybridization technique is also tested against other existing navigational approaches for validation of better efficiency.
Currently, the distribution system has been adapted to include a variety of Distributed Energy Resources (DERs). Maximum benefits can be extracted from the distribution system with high penetration of DERs by transforming it into a sustainable, isolated microgrid. The key aspects to be addressed for this transformation are the determination of the slack bus and assurance of reliable supply to the prioritized loads even during contingency. This paper explores the possibilities of transforming the existing distribution system into a sustainable isolated network by determining the slack bus and the optimal locations and capacity of Distributed Generators (DGs) in the isolated network, taking into account the contingencies due to faults in the network. A combined sensitivity index is formulated to determine the most sensitive buses for DG placement. Further, the reliability based on the loss of load in the isolated system when a fault occurs is evaluated, and the modifications required in for reliability improvement are discussed. The supremacy of the transformed isolated network with distributed generators is comprehended by comparing the results from conventional IEEE 33-bus grid connected test system and modified IEEE 33-bus isolated test system having no interconnection with the main grid.
The microscale deformation behaviour of the Al-4.5Cu-2Mg alloy has been studied to understand the influence of various processing routes and conditions, i.e. the gravity casting with and without grain refiner, the rheocast process and the strain induced melt activation (SIMA) process. The micromechanics based simulations have been carried out on the optical microstructures of the alloy by 2D representative volume elements (RVEs) employing two different boundary conditions. Microstructural morphology, such as the grain size, the shape and the volume fraction of α-Al and binary eutectic phases have a significant effect on the stress and strain distribution and the plastic strain localization of the alloy. It is found that the stress and strain distribution became more uniform with increasing the globularity of the α-Al grain and the α-Al phase volume fraction. The simulated RVEs also reveals that the eutectic phase carries more load, but least ductility with respect to the α-Al phase. The SIMA processed alloy contains more uniform stress distribution with less stress localization which ensures better mechanical property than the gravity cast, grain refined and rheocast alloy.
Abstract An autonomous mobile robot is a robot which can move and act autonomously without the help of human assistance. Navigation problem of mobile robot in unknown environment is an interesting research area. This is a problem of deducing a path for the robot from its initial position to a given goal position without collision with the obstacles. Different methods such as fuzzy logic, neural networks etc. are used to find collision free path for mobile robot. This paper examines behavior of path planning of mobile robot using three activation functions of wavelet neural network i.e. Mexican Hat, Gaussian and Morlet wavelet functions by MATLAB. The simulation result shows that WNN has faster learning speed with respect to traditional artificial neural network.