Effective Spiral Laser Path for Minimizing Local Heating and Anisotropic Microstructures in Powder Bed Fusion Additive Manufacturing.

Heat accumulation due to repetitive simple laser processing paths during building up a three-dimensional structure is a well-known issue that needs to be settled to reduce the excessively high residual stress and thermal deformation in a powder bed fusion (PBF) additive manufacturing process. Because of the dependency of laser path on the thermal dispersion, it is essential to analyze the heat accumulation phenomenon during laser processing. A computational fluid dynamics (CFD) analysis based on the volume of fraction method is used to optimize the laser path for minimizing the local heating up in the PBF process.

Optimization of Friction Stir Spot Welding Process Using Bonding Criterion and Artificial Neural Network.

The objectives of this study were to analyze the bonding criteria for friction stir spot welding (FSSW) using a finite element analysis (FEA) and to determine the optimal process parameters using artificial neural networks. Pressure-time and pressure-time-flow criteria are the bonding criteria used to confirm the degree of bonding in solid-state bonding processes such as porthole die extrusion and roll bonding. The FEA of the FSSW process was performed with ABAQUS-3D Explicit, with the results applied to the bonding criteria.

Neural Network-Based Multi-Objective Optimization of Adjustable Drawbead Movement for Deep Drawing of Tailor-Welded Blanks.

To improve the formability in the deep drawing of tailor-welded blanks, an adjustable drawbead was introduced. Drawbead movement was obtained using the multi-objective optimization of the conflicting objective functions of the fracture and centerline deviation simultaneously. Finite element simulations of the deep drawing processes were conducted to generate observations for optimization.

A multi-objective optimization using response surface model coupled with particle swarm algorithm on FSW process parameters.

In this study, multi-objective optimization of mechanical properties in friction-stir-welding of AH12 1050 aluminum alloy is performed using a combination of the response surface method and multi-objective particle swarm optimization algorithm. The process parameters are considered as tool pin diameter, shoulder diameter, rotational speed, feed speed, and tool tilt angle. The heat-affected zone's yield strength, fracture strain, impact toughness, and hardness on the advancing and retreating sides are selected as the objective functions.

Crack growth pattern analysis of monolithic glass ceramic on a titanium abutment for single crown implant restorations using smooth particle hydrodynamics algorithm.

Background: Glass ceramic materials have multiple applications in various prosthetic fields. Despite the many advantages of these materials, they still have limitations such as fragility and surface machining and ease of repairing. Crack propagation has been a typical concern in fullceramic crowns, for which many successful numerical simulations have been carried out using the extended finite element method (XFEM).