Effect of the Electrodeposition Frequency,Wave Form,and Thermal Annealing on Magnetic Properties of [Co0.975Cr0.025]0.99Cu0.01 Nanowire Arrays

Highly ordered [Co _0.975Cr _0.025]_0.99Cu _0.01 nanowire arrays were electrodeposited by conducting alternating current (AC) conditions from sulfate-based electrolyte into nanopores of anodic aluminum oxide (AAO) template with 37 nm pore diameter and the interpore distances of almost 50 nm. Fabricated nanowire arrays were characterized using scanning electron microscopy, alternating gradient force magnetometer, and X-ray diffraction. The results illustrated that varying frequency, wave form, and annealing procedure had influence on magnetic properties of as deposited nanowires. The nanowire arrays electrodeposited at different electrodeposition frequencies show remarkably different magnetic behaviors. Due to increasing of the electrodeposition frequency, the rate of ions for reduction was decreased. The nanowires prepared at various wave form illustrated insignificant impact on magnetic properties. X-ray diffraction patterns display that both as-deposited and annealed nanowire arrays expose the same structure. The raised value of coercivity has been determined in annealed nanowire arrays. Magnetization measurements show that the maximum value of coercivity for [Co _0.975]_0.99Cu _0.01 nanowires is observed at high temperature.     

Combined Use of Geostatistics and Multi-Criteria Decision Analysis to Determine New Pumping Well Locations in the Gol-Gohar Open Pit Mine,Iran

Groundwater seepage into open pit mines must be controlled carefully. Slope instability, dewatering of blast holes, and mining operations below the groundwater table are important issues caused by groundwater seepage into the Gol-Gohar open pit mine, Iran. There are several methods to overcome these problems, such as construction of cut-off walls, ditches and sumps, horizontal drains, and pumping wells. Drilling of a new pumping well has several difficulties in which the determination of its location is a major issue. In this study, a stochastic simulation approach called simulated annealing was used to determine the best possible locations for new pumping wells. Three major groundwater variables, including the groundwater level, electrical conductivity, and transmissivity were selected for the geostatistical study. The results of simulations showed reliable correlation (Pearson) between the variables. Comparison of the variograms at different depths of the Gol-Gohar pit mine revealed that the effect of faults intensified with increasing depth. The best potential locations for drilling of new pumping wells were identified by the use of multi-criteria decision analysis performed on the simulation results. This method can be used in other regions with similar hydrogeological settings.     

Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran

This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based on population, GDP (gross domestic product), import and export data. Oil consumption in Iran from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1981–1999) and partly for testing the models (2000–2005). For the best results of GA, the average relative errors on testing data were 2.83% and 1.72% for GA–DEM_exponential and GA–DEM_linear, respectively. The corresponding values for PSO were 1.40% and 1.36% for PSO–DEM_exponential and PSO–DEM_linear, respectively. Oil demand in Iran is forecasted up to year 2030.