20.500.12556/RUL-137540 Contour maps for simultaneous increase in yield strength and elongation of hot extruded aluminum alloy 6082 In this paper, the Conditional Average Estimator artificial neural network (CAE ANN) was used to analyze the influence of chemical composition in conjunction with selected process parameters on the yield strength and elongation of an extruded 6082 aluminum alloy (AA6082) profile. Analysis focused on the optimization of mechanical properties as a function of casting temperature, casting speed, addition rate of alloy wire, ram speed, extrusion ratio, and number of extrusion strands on one side, and different contents of chemical elements, i.e., Si, Mn, Mg, and Fe, on the other side. The obtained results revealed very complex non-linear relationships between all of these parameters. Using the proposed approach, it was possible to identify the combinations of chemical composition and process parameters as well as their values for a simultaneous increase of yield strength and elongation of extruded profiles. These results are a contribution of the presented study in comparison with published research results of similar studies in this field. Application of the proposed approach, either in the research and/or in industrial aluminum production, suggests a further increase in the relevant mechanical properties. AA6082 hot extrusion mechanical properties yield strength elongation artificial neural networks analysis true false true Angleški jezik Ni določen Članek v reviji 2022-06-21 12:30:45 2022-06-21 12:30:46 2022-09-15 04:15:21 0000-00-00 00:00:00 2022 0 0 14 str. iss. 3, art. 461 Vol. 12 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 669 2075-4701 10.3390/met12030461 100364035 metals-12-00461.pdf metals-12-00461.pdf 1 6CA3903471E7BFCCBEDC3A4D8DFDB68D b70c93c33e7ebcb65ca207c8c3c11bd31b9c993c45418c060c2ed749c16097ca 4b90f87a-f14d-11ec-8aca-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=157528 https://www.mdpi.com/2075-4701/12/3/461 0 19de8716-f14d-11ec-8aca-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=157527 Naravoslovnotehniška fakulteta 0 0 0