Felipe Bertelli

An Effective Inverse Heat Transfer Procedure Based on Evolutionary Algorithms to Determine Cooling Conditions of a Steel Continuous Casting Machine

The inverse modeling of heat transfer is a useful tool in analyzing contact heat transfer at the ingot surfaces during the continuous casting process. The determination of the boundary conditions involves an experimental work consisting in the evaluation of the thermal history, generally at the casting surface, experimentally provided by infrared pyrometers. Additionally, numerical simulations, based on the solution of the 2D transient heat conduction equation, are performed in order to be inversely solved in response to the measured thermal data furnished by the sensor. Due to computational time consumption during simulations in searching cooling conditions, this work proposes an interaction between natural inspired algorithms, called evolutionary algorithms, and the numerical model in order to speed up the searching process. The present work aims to compare three algorithms, namely genetic algorithm, improved stochastic ranking evolutionary strategy, and evolutionary strategy with Cauchy distribution. The latter develops a metaheuristic version of an evolutionary strategy workflow, using a Cauchy random number function to generate each individual, instead of the usual uniform distribution function available in almost all programming languages. The surface temperature, solid shell, and molten pool profiles from the determined cooling conditions are analyzed in terms of casting quality.

Characterization of Dendritic Microstructure, Intermetallic Phases, and Hardness of Directionally Solidified Al-Mg and Al-Mg-Si Alloys

THE authors regret that numerical errors were identified in Figures 10(a, right graph) and (b, right graph) and 12. In the calculation of the growth rate of the Al-3.0 wt pct Ni alloy, a mistake has been found. The corrected figures and their respective legends are reproduced below. The error does not change the main discussions and conclusions of the work. In addition, a sentence containing the discussion associated with Figure 12 has been rewritten as follows. As can be observed in Figure 12, the BKmodel roughly matches the experimental tendency of evolution of the secondary dendrite arm spacing with the growth rate.

Progression of plastic strain on heavy-haul railway rail under random pure rolling and its influence on crack initiation

Abstract The present work evaluates the plastic strain accumulation on railway rails for heavy-haul transportation and the effect of them on the life cycle and the stress-strain responses considering random loading passes of normal loads on the top of rail for wheel-rail pure rolling conditions. The normal pressure distribution on the contact region was estimated by the Hertz theory and applied on the surface of the rail in a tridimensional elastoplastic finite element model. Multiaxial Dang Van criterion was applied to estimate the life to crack nucleation. The results show that the level of plastic accumulation presents distinct magnitudes depending on the position analyzed, reaching similar plastic accumulation in analogous positions on the subsurface after several passes, for two different starting positions. That result is fundamental for life analyses, since indicates that, no matter the starting point, the computed life cycles always stabilizes after a few number of cycles. From that, the fatigue life to shelling can be estimated using high cycle models.

An artificial immune system algorithm applied to the solution of an inverse problem in unsteady inward solidification

Abstract The numerical simulation and optimization in solidification involving geometries beyond one dimension normally requires expensive computational approaches in memory and data processing, generating consequently high cost associated with runtime execution. When boundary conditions are unknown, such as how heat is extracted from the casting surface, which is a typical inverse heat transfer problem (IHTP), the search for such conditions by trial-and-error makes the whole process less feasible. In this sense, this work introduces the application of an artificial immune system (AIS) algorithm as a possible meta-heuristic alternative, with a view to returning acceptable objective values to converge on a set of acceptable solutions. In the present work, the search process of the heat transfer coefficient (hg) at the casting surface during two-dimensional inward solidification of Al-1.5 wt.%Fe alloy castings of Cartesian and Cylindrical geometries in chilled molds is optimized. Two water-cooled solidification apparatuses were designed to in situ melt the alloy by a set of electrical resistances, in which heat is extracted only through the chilled faces of the molds. The thermal history during solidification was obtained via thermocouples placed at different positions in the castings. A Finite Difference heat transfer model integrated to an optimized version of the artificial immune network algorithm, which uses the experimental thermal profiles as inputs, has been applied to solve the IHTP through the search for acceptable values of heat transfer coefficient. It is shown that fast convergence of the developed algorithm can be achieved for a relatively small number of iterations. The mean relative errors associated with differences between simulated and experimental temperatures are shown to be 1% and 0.07% for Cartesian and Cylindrical geometries, respectively and expressions relating hg to time have been determined for both geometries.