This work presents the operational optimization of a welding operation involving using genetic algorithms. The welding curves correspond to the profile of a blade-shaped Pelton turbine. The procedure involved the development of a series of tests and observation of the parameters that will be controlled during the welding process. After the tests were performed, the samples were prepared for chemical attack, which allowed observation of the penetration, weld area, and dilution. After that, mathematical models were developed that correlate the controllable welding parameters with the aforementioned bead parameters. In those mathematical models, the optimization of the process parameters was performed using genetic algorithms. Specially programmed functions for mutation, reproduction, and initialization processes were written and used in the implemented model. After the optimization process was completed, the results were evaluated through new tests to verify whether the obtained objective functions properly describe the characteristics of the weld. The comparisons showed errors of less than 6%.

In this work, a blend of Ti, Nb, and Mn powders, with a nominal composition of 15 wt.% of Mn, and balanced Ti and Nb wt.%, was selected to be mechanically alloyed by the following two alternative high-energy milling devices: a vibratory 8000D mixer/mill^® and a PM400 Retsch^® planetary ball mill. Two ball-to-powder ratio (BPR) conditions (10:1 and 20:1) were applied, to study the evolution of the synthesized phases under each of the two mechanical alloying conditions. The main findings observed include the following: (1) the sequence conversion evolved from raw elements to a transitory bcc-TiNbMn alloy, and subsequently to an fcc-TiNb15Mn alloy, independent of the milling conditions; (2) the total full conversion to the fcc-TiNb15Mn alloy was only reached by the planetary mill at a minimum of 12 h of milling time, for either of the BPR employed; (3) the planetary mill produced a non-negligible Fe contamination from the milling media, when the highest BPR and milling time were applied; and (4) the final fcc-TiNb15Mn alloy synthesized presents a nanocrystalline nature and a partial degree of amorphization.

The effect of space holder particles (SHP) fractal distribution on the porosity of aluminum foams manufactured by infiltration is studied in the present work. Physical models were used to estimate aluminum foam porosity, simulating SHP distribution for bimodal mixtures with different particle sizes and relative quantities. Results of these models were compared with mathematical models and the results obtained for experimental aluminum foams manufactured using a 332 Al-alloy base material and NaCl grains as SHP. Experimental foam structural characterization was carried out using image analysis to obtain porosity, density, wall thickness and fractal dimension, while mechanical characterization focused on the compressive Young modulus. Results show that it was possible to manufacture foams with different fractal porosities and a wide variety of unit cells, reaching a maximum of ? 68%. It was also found that pore wall thicknesses significantly decreased with the increase in the fine particles fraction. Besides, all the models presented a peak with a maximum porosity, whose values increased and shifted to low fine particles fraction with the increase in the sizes ratio. This behavior was also observed for the experimental foams with low particle size ratio. Nevertheless, for higher size ratios porosity showed an irregular behavior attributed to the mixing process.

An alternative meshless finite‐point method (FPM) technique for the numerical solution of the Regularized long wave (RLW) equation is presented. In this context, we derive the discretized system by combining finite difference (FD) techniques for the time derivative and FPM for the spatial derivatives. The accuracy of this alternative approach is tested with L₂, L_∞ error norms and the conservation properties of mass, energy, and momentum under the RLW equation.