Production of Open-Cell Metal Foams by Recycling of Aluminum Alloy Chips.

In this paper, an innovative sustainable method of producing metal foams was presented. The base material was aluminum alloy waste in the form of chips obtained by machining process. The leachable agent, used to create pores in the metal foams, was natrium chloride, which was later removed by leaching, resulting in metal foams with open cells. Open-cell metal foams were produced with three different input parameters: volume percentage of natrium chloride, compaction temperature, and force. The obtained samples were subjected to compression tests during which displacements and compression forces were measured to obtain the necessary data for further analysis. To determine the influence of the input factors on the selected response values such as relative density, stress and energy absorption at 50% deformation, an analysis of variance was performed. As expected, the volume percentage of natrium chloride was shown to be the most influential input factor because it has a direct impact on the obtained metal foam porosity and thus on the density. The optimal values of the input parameters with which the metal foams will have the "most desirable" performances are a 61.44% volume percentage of natrium chloride, a compaction temperature of 300 °C and a compaction force of 495 kN.

Orthogonal cutting simulation of EN AW 6082 T6 alloy using a coupled Eulerian-Lagrangian approach.

The latest trends in machining research show that great efforts are being made to simulate machining processes. This paper presents the results of cutting force, feed force and temperatures when the orthogonal cutting of EN AW 6082 T6 alloy. Appropriate material model and damage model were investigated in order to perform finite element simulation with Coupled Eulerian-Lagrangian (CEL) approach. In the next step, simulations were designed based on the input parameters. The size of element in the x-direction (2 µm-10 µm), size of element in y-direction (2 µm-10 µm) and width of the workpiece (2 µm-100 µm) are considered as controllable variables The Genetic Algorithm was used to identify the optimal process parameters by which the minimum value of cutting force error, the minimum value of feed force error and minimum simulation time will be achieved. The optimal combination of the process parameters is size of elements at x-direction 8 µm, y-direction 10 µm and width of workpiece 84 µm. By utilizing the optimal input parameters cutting force error was reduced from 6.5% to 1.07% and feed force error was reduced from 6.15% to 3.12%. The results showed that the optimum size and orientation of the finite element mesh can significantly reduce the error in the prediction of cutting forces and reduce processing simulation time. In addition, it was concluded that with the CEL approach, temperatures in the cutting zone can be successfully predicted.