Electrical discharge machining (EDM) is a non-conventional machining process that is used for machining of hard-to-machine materials, components in which length to diameter ratio is very high or products with a very complicated shape. The process is commonly used in automobile, chemical, aerospace, biomedical, and tool and die industries. It is very important to select optimum values of input process parameters to maximize the machining performance. In this paper, an attempt has been made to carry out multi-objective optimization of the material removal rate (MRR) and roughness parameter (Ra) for the EDM process of EN31 on a CNC EDM machine using copper electrode through evolutionary optimization techniques like particle swarm optimization (PSO) technique and biogeography based optimization (BBO) technique. The input parameter considered for the optimization are Pulse Current (A), Pulse on time (µs), Pulse off time (µs), and Gap Voltage (V). PSO and BBO techniques were used to obtain maximum MRR and minimize the Ra. It was found that MRR and SR increased linearly when discharge current was in mid-range however non-linear increment of MRR and Ra was found when current was too small or too large. Scanning Electron Microscope (SEM) images also indicated a decreased Ra. In addition, obtained optimized values were validated for testing the significance of the PSO and BBO technique and a very small error value of MRR and Ra was found. BBO outperformed PSO in every aspect like computational time, less percentage error, and better optimized values.
This work assesses the impact of the presence of Nano scaled silicon carbide on the Mechanical & Tribological behavior of aluminium matrix composites. Aluminium matrix composites containing 0, 0.5, 1, 1.5, 2 and 2.5 wt.%-nano scaled silicon carbide was set up by a mechanical stirrer. The trial comes about to demonstrate that the inclusion of Nano silicon carbide brings about materials with progressively high elastic modulus and likewise brings about expanded brittle behavior, fundamentally lessening failure strain. Shear modulus and flexural shear modulus likewise increases with silicon carbide increase. The presence of Nano scaled silicon carbide in the aluminium matrix diminishes subsurface fatigue wear and increases wear resistance, because of silicon carbide lubricant activity. Wear testing, microstructure & morphological, density & void testing, hardness, flexural and tensile test of the readied composites were investigated and outcomes were analyzed which demonstrated that including nano-SiC in aluminum (Al) matrix increased wear resistance, tensile strength, and 2 wt. % of nano scaled SiC for Al MMC indicated maximum wear resistance, tensile strength, and an optimum balanced mix of both Tribological and Mechanical properties. Microstructural observation uncovered uniformand homogeneous distribution of SiC particles in the Al matrix.
We compare the Autler–Townes (AT)-splitting in E u 3 + : Y P O 4 , P r 3 + : Y P O 4 , and P r 3 + : Y 2 S i O 5 crystals. The AT-splitting in P r 3 + : Y 2 S i O 5 is stronger than other two-doped crystals, while the P r 3 + ion has a stronger dressing than the E u 3 + ion in a host material of YPO. The stronger dressing in YSO is attributed to the C 2 h symmetry of the YSO crystal and its nondegeneracy, making the dressing sensitive to doped material. By investigating the relationship between spectral AT-splitting (SAT-splitting) and temporal AT-splitting (TAT-splitting), we observed that TAT-splitting depends upon the dressing effect and phonon-assisted nonradiative transition whereas SAT-splitting results only from the dressing effect. Based on our results, we proposed a model for an optical router and transistor (amplifier and switch). The router action results from the SAT- and TAT-splitting while the transistor was realized by a switch from bright to dark dressed states.
A 3D ray tracing model is used to simulate optical reinjection in a nonresonant optical cavity, for off-axis integrated cavity output spectroscopy. The optical cavities are optimized for maximum intensity enhancement factors via a grid search and a genetic algorithm. Intensity enhancement factors up to 1400 are found for short cavities (3 cm) and up to 101 for long cavities (50 cm). The model predicts that short absorption cells can be used, having a long effective path length and a high throughput power. This opens new opportunities in the field of ultrasensitive absorption spectroscopy and allows the design of compact optical gas sensors.
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