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In this paper, the optimal reactive power problem has been solved by the cultivation of soil optimization (CSO) algorithm. The reduction of real power loss is a key objective of this work. The projected CSO algorithm has been modeled based on the quality of soil which has been used in the cultivation of various crops season to season. With respect to the quality of the soil in the cultivation land, there will be a change in the poor-quality soil since there will up the gradation of the poor soil is done through by adding the nutrient contents. Depend upon the needs and about the type of cultivation farmers will improve the quality of the soil by adding valuable and various types of fertilizers (natural and artificial) such that it will enhance the fertile and growth (green) of the crops. Time to time farmers will choose appropriate nutrient contents that will be mixed with the soil in order to enhance the fertility of the soil. In standard IEEE 14, 30, 57 bus test systems Cultivation of Soil Optimization (CSO) algorithm has been tested. The CSO algorithm reduced the real power loss and control variables are within the limits.

The sustainability of Electrical Discharge Machining (EDM) is a green technology which is able to produce a green environmental condition and healthy human condition. The characteristics of hydro-carbon based dielectrics are identified to have disturb the machining performance due to their carbon properties, more debris formation, recast formation and formation of oxide on processed surface.To achieve the green technology in machining, decrease the environmental impact, reduce the machining cost and save energy, neem oil is employed as a bio-dielectric fluid. Hence, the circular holes have been carried out on AA8011/SiC/Si3N4 composites in EDD using a neem oil. The responses, Rate of Material Removal (MRR), Rate of Electrode Wear (EWR) and Surface Roughness (Ra) produced results with neem oil are analyzed to virgin kerosene and Cu-Si in kerosene dielectric. The XRD report produced that the Mg2Si and MgAl2 intermetallic phases have been formed in composites. The higher improvement in 67.5% MRR, 26% EWR and 24% Ra has been achieved using neem oil. The pulse duration has highly contributed for improving the selected responses and identified by using an Analysis of variance (ANOVA). The ELimination Et Choix Traduisant la REalite (ELECTRE) has found an optimum factor value of 500 µs pulse duration, 55 µs pulse interval, 4 A current and 45 V gap voltage. [ABSTRACT FROM AUTHOR]

Compared with other machining processes, laser machining is seen as one of the time and cost effective processes in machining of metal matrix composites (MMCs). Hence, this work more focuses on analysis of laser machining parameters, namely, laser trepanning speed, laser power and standoff distance, various weight percentages of SiC and ZrSiO4 are selected for investigation. Laser machining experiments were performed on SiC and ZrSiO4 reinforced with Aluminium Alloy (AA7475). The performance measures, hole size at entry, surface roughness and taper angle of MMCs were evaluated. Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE II) was used for finding optimum process parameters. PROMETHEE II based Adaptive Network Based Fuzzy Inference System (ANFIS) was used for modelling the responses. The main contribution of this work is the analysis of the impact of reinforcement particles of the composites and laser machining parameters on the responses. The results showed that hole size at entry, surface roughness and taper angle of unreinforced alloy was less than the composite for all the processing conditions. PROMETHEE II algorithm produced a consistent result. PROMETHEE II based ANFIS model produces closer predicted value to experimental value. Scanning electron microscope is used to identify the machined defects such as recast layer, spatter and dross. [ABSTRACT FROM AUTHOR]

The influence of friction stir welding (FSW) in automotive applications is significantly high in recent days as it can boast beneficial factors such as less distortion, minimized residual stresses and enhanced mechanical properties. Since there is no emission of harmful gases, it is regarded as a green technology, which has an energy efficient clean environmental solid-state welding process. In this research work, the FSW technique is employed to weld the AA8011-AZ31B alloy. In addition, the L16 orthogonal array is employed to conduct the experiments. The influences of parameters on the factors such as microstructure, hardness and tensile strength are determined. Microstructure images have shown tunnel formation at low rotational speed and vortex occurrence at high rotational speed. To attain high quality welding, the process parameters are optimized by using a hybrid method called an artificial neural network based genetic algorithm (ANN-GA). The confirmation tests are carried out under optimal welding conditions. The results obtained are highly reliable, which exhibits the optimal features of the hybrid method. [ABSTRACT FROM AUTHOR]