Iskanje po katalogu digitalne knjižnice

Opis: 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.
Ključne besede: AA6082, hot extrusion, mechanical properties, yield strength, elongation, artificial neural networks, analysis
Objavljeno v DKUM: 12.03.2025; Ogledov: 0; Prenosov: 0
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Opis: The present study reports the development of new polymer bonded magnet containing a Thermoplastic Polyurethane (TPU) – Nylon (PA12) blend as the matrix material and Nd-Fe-B magnetic particles. Two composite materials were explored: one using Nd-Fe-B atomised spherical powder (ASP) and another incorporating Nd-Fe-B melt-spun flakes (MSF). The filaments were formulated by blending TPU, PA12, and one of selected type of Nd-Fe-B particles using a mixing device. The ASP and the MSF were integrated into the matrix via a precise compounding process and 3D printing was used to produce the testing specimens. The preliminary findings indicate that both formulations exhibited promising magnetic properties while maintaining the mechanical characteristics of TPU and PA12. The atomised spherical powder formulation demonstrated worse magnetic behaviour compared to the melt-spun flake formulation. ASP particles enable better fluidity of the composite material during 3D printing. However, the close-packed arrangement of these particles is the cause of much higher porosity and consequently the poorer mechanical and magnetic properties. Optimization of the processing parameters showed significant influence on the final magnetic performance and structural integrity of the printed specimens.
Ključne besede: bonded magnets, Nd-Fe-B melt spun flakes, Nd-Fe-B atomised powders, material extrusion, additive manufacturing, fused specimen fabrication
Objavljeno v DKUM: 08.01.2025; Ogledov: 0; Prenosov: 8
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Opis: Accuracy and precision are essential in extrusion-based material handling such as three-dimensional (3D) bioprinting. However, the elasticity of components, backlash, variability of nozzle and cartridge shapes, etc. can lead to unpredictable printing results, which is further complicated by the wide range of rheologically diverse materials and complex sample designs. To address this issue, we present an algorithmic approach to compensate for the discrepancies between piston motion and material extrusion in syringe-based extrusion systems. This approach relies on cyclical, iterative optimization through rapid piston movements, which are adjusted based on extrusion analysis. In this work we establish a general theoretical framework for extrusion and link the rheological properties of prepared hydrogels with shear rates in a typical bioprinting process. The determined properties are compared with the success of the developed algorithm to modify machine instructions for precise material deposition of short, interrupted lines, as well as multi-layered scaffold structures. Overall, our approach provides a means of improving the accuracy and precision of complex extrusion-based bioprinting systems, without prior knowledge of set-up or material properties, making it highly versatile and suitable for a wide range of applications, particularly when the combined set-up and material properties are too complex for solely predictive approaches.
Ključne besede: 3D bioprinting, syringe extrusion, optimization, algorithm
Objavljeno v DKUM: 21.04.2023; Ogledov: 684; Prenosov: 109
Celotno besedilo (3,38 MB)
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Opis: The purpose of this research is the determination of the optimal cold forward extrusion parameters with the minimization of tool load as objective. This paper deals with different optimization approaches in order to determine optimal values of logarithmic strain, die angle and friction factor with the purpose to find minimal tool loading obtained by cold forward extrusion process. Two experimental plans based on factorial design of experiment and orthogonal array have been carried out. Classical optimization, according to the response model of extrusion forming force, and the Taguchi approach are presented. The obtained extrusion force model as the fitness function was used to carry out genetic algorithm optimization. Experimental verification of optimal forming parameters with their influences on the forming forces was also performed. The experimental results show an improvement in the minimization of tool loading. The results of optimal forming parameters obtained with different optimization approaches have been compared and based on that the characteristics analysis (features and limitations) of presented techniques.
Ključne besede: metal forming, forward extrusion force optimization, design of experiments, Taguchi approach, genetic algortihm
Objavljeno v DKUM: 31.05.2012; Ogledov: 2028; Prenosov: 100
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