Sürdürülebilir Kalkınma Amaçları

• 1

• MakaleYalnız künye2026/r/gumushane/13798
  Electromechanical characterization and deep learning-based force prediction in 3D-printed PLA core–shell composites

  Ekmekci, Dursun; Kaplan, Emrah

  In this study, composite samples were produced using fused deposition modeling to contain an outer layer of red insulating polylactic acid and an inner core of black conductive polylactic acid. The mechanical properties of the samples were determined using three-point bending experiments, and their electro-mechanical impedance responses during loading were monitored using impedance experiments. To examine the effects of physical aging and crystallization, the composites were heat-treated at 50 °C for 2, 4, and 6 hours. The insulating polylactic acid exhibited brittle fracture with a sharp post-peak force drop, whereas the conductive polylactic acid showed a ductile fracture mode accompanied by substantial energy dissipation. The physically aged composites were stiffer and less ductile, which was attributed to the presence of partially crystallized and partially relaxed molecules, especially around the glass transition region. In support of the observed properties, scanning electron microscopy images confirmed that the fractured layers were smoother compared to the ductile conductive layers, which had surface roughness patterns resembling fibrillated or lamellar structures. Additionally, the impedance signals obtained during the bending experiments were linked with the corresponding mechanical properties using an advanced deep learning model that could model the electric signals to accurately provide the corresponding real-time force values.

  • 
  İncele
• MakaleYalnız künye2025/r/gumushane/14118
  Optimization of steel diffusion bonding processes using the Taguchi method

  Serkan Yıldırım, Mehmet; Aydın, Kemal; Kalyon, Ali; Kaya, Yakup

  This study examines the diffusion bonding behavior between 316L stainless steel and H13 tool steel, focusing on the effects of key process parameters. Specifically, the influence of bonding pressure, bonding temperature, and holding time on joint quality and mechanical performance is systematically investigated. The Taguchi optimization method was employed to determine the optimal bonding conditions, with shear strength serving as the primary performance indicator. The bonding interfaces were characterized through scanning electron microscopy to analyze microstructural evolution and diffusion behavior. Analysis of variance was conducted to assess the influence of process parameters on shear strength, identifying temperature as the most significant factor. The optimum shear strength was experimentally validated, and a confidence interval was calculated to ensure statistical reliability. The results demonstrated that higher bonding temperatures and moderate pressures led to improved diffusion at the interface, enhancing joint integrity. The findings contribute to a better understanding of the diffusion bonding process and its potential for high-performance applications in aerospace, biomedical, and tooling industries.

  İncele
• MakaleYalnız künye2025/r/gumushane/14112
  The effect of welding parameters on weld bead geometry in gas tungsten arc welding applications by response surface methodology model

  Yildirim, Mehmet Serkan; Ayhan, Emre; Aydin, Kemal; Durgutlu, Ahmet

  This study examines the effects of tungsten electrode sharpening angle, torch angle, and arc length on weld bead geometry in gas tungsten arc welding (GTAW). Low-carbon steel plates (4 mm thickness) were welded using ER70S-6 filler wires (2 mm diameter). Experimental analyses and response surface methodology (RSM) revealed that increasing the electrode sharpening angle enhances penetration depth, while reducing the torch angle widens the bead. Longer arc lengths decrease penetration but increase bead width. Validation tests confirmed the accuracy of the RSM models, showing an average deviation of 1.14%. Analysis of variance highlighted the statistical significance of linear, quadratic, and interaction terms in the models. The findings provide critical insights for optimizing GTAW parameters, improving weld quality, and advancing process control, thereby contributing both practical and academic value to welding research.

  İncele