Rachid AMRAOUI

Systems based on artificial intelligence, such as particle swarm optimization and geneticalgorithm have received increased attention in many research areas. One of the main objectives inthe gas metal arc welding (GMAW) process is to achieve maximum depth of penetration (DP) as acharacteristic of quality and stiffness. This article has examined the application of particle swarmoptimization algorithm to obtain a better DP in a GMAW and compare the results obtained with thetechnique of genetic algorithms. The effect of four main welding variables in GMAW process whichare the welding voltage, the welding speed, the wire feed speed and the nozzle-to-plate distanceon the DP have been studied. For the implementation of optimization, a source code has beendeveloped in MATLAB 8.3. The results showed that, in order to obtain the upper penetration depth,it is necessary that: the welding voltage, the welding speed and the nozzle-to-plate distance must beat their lowest levels; the wire feed speed at its highest level

In this work, FeTiO2 and FeTiO3 nanocomposites were synthesized using mechanical alloying, and their structural, morphological, and magnetic properties were systematically examined. Phase evolution, crystallite size refinement, and magnetic performance were investigated through X-ray diffraction (XRD), scanning electron microscopy (SEM), and vibrating sample magnetometry (VSM). XRD confirmed the successful formation of targeted phases along with a noticeable reduction in crystallite size. SEM analysis revealed distinct morphological features, with FeTiO2 presenting a more homogeneous and finer microstructure compared to FeTiO3. Magnetic measurements indicated that FeTiO2 exhibited higher saturation magnetization and coercivity, primarily due to its finer grain structure and enhanced refinement. These results highlight FeTiO2 as a promising material for advanced technological applications …

Nanostructured FeSi and FeSiO₂ nanocomposites were synthesized via mechanical alloying to investigate the effects of milling time (0–30 h) on their structural, morphological, and magnetic properties. Comprehensive characterization was performed using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and vibrating sample magnetometry (VSM). XRD analysis revealed a transition to a disordered FeSi solid solution with a body-centered cubic structure after prolonged milling, alongside a crystallite size reduction and increasing lattice strain. For FeSi, the lattice parameter increased from 0.2861 nm (unmilled) to 0.452 nm after 30 h, with an average crystallite size of 22 nm. In contrast, the FeSiO₂ nanocomposite exhibited crystallite sizes ranging from 79–28 nm, with Fe/SiO₂ showing a lattice parameter decrease from 0.286 nm to 0.283 nm. Morphological evolution was evident through SEM. Magnetic properties improved with extended milling, with FeSi attaining its highest coercivity, saturation magnetization, and remanent magnetization at 30 h. Similarly, FeSiO₂ exhibited notable coercivity and remanence values, with Fe/SiO₂ achieving the highest saturation magnetization of 177.08 emu/g. These results emphasize the potential of FeSi and FeSiO₂ nanocomposites for high-frequency magnetic applications.