Multi-laser beam selective laser melting (SLM) technology based on a powder bed has been used to manufacture AlSi10Mg samples. The AlSi10Mg alloy was used as research material to systematically study the performance consistency of both the laser overlap areas and the isolated areas of the multi-laser beam SLM manufactured parts. The microstructures and mechanical properties of all isolated and overlap processing areas were compared under optimized process parameters. It was discovered that there is a raised platform at the junction of the overlap areas and the isolated areas of the multi-laser SLM samples. The roughness is significantly reduced after two scans. However, the surface roughness of the samples is highest after four scans. As the number of laser scans increases, the relative density of the overlap areas of the samples improves, and there is no significant change in hardness. The tensile properties of the tensile samples are poor when the overlap area width is 0, 0.1, or 0.2 mm. When the widths of the overlap areas are equal to or greater than 0.3 mm, there is no significant difference in the tensile strength between the overlap and the isolated areas.

In this paper, considering the porosity defects of Additive Manufacturing (AM), a level set topology optimization method for AM with porosity constraints is proposed. The concept of topological sensitivity is used to formulate a global porosity constraint function in the proposed method, and a level set topology optimization model considering porosity defects is obtained. To improve the robustness of the algorithm, the topology optimization model is solved in two phases. At first, the classical level set method without the porosity constraint is used to initially optimize the structure. During this process, the hole nucleation method combining bi-directional evolutionary structural optimization (BESO) and the topological sensitivity is used. Secondly, the topology optimization considering the effects of porosity is implemented on the preliminary optimization results. After performing the two-step optimization, a robust structure that alleviates the harmful impact of porosity defects is obtained. Finally, the robustness and effectiveness of the proposed method are validated by several two-dimensional numerical examples.

In harsh environments, the corrosion damage of steel structures and equipment is a serious threat to the operational safety of service. In this paper, a Zn-Al diffusion layer was fabricated on 45 steel by the Mechanical Energy Aided Diffusion Method (MEADM) at 450 °C. The microstructure and composition, the surface topography, and the electrochemical performance of the Zn-Al diffusion layer were analyzed before and after corrosion. The results show that the Zn-Al diffusion layer are composed of Al₂O₃ and Γ₁ phase (Fe11Zn40) and δ₁ phase (FeZn_6.67, FeZn_8.87, and FeZn_10.98) Zn-Fe alloy. There is a transition zone with the thickness of about 5 μm at the interface between the Zn-Al diffusion layer and the substrate, and a carbon-rich layer exists in this zone. The full immersion test and electrochemical test show that the compact corrosion products produced by the initial corrosion of the Zn-Al diffusion layer will firmly bond to the Zn-Al diffusion layer surface and fill the crack, which plays a role in preventing corrosion of the corrosive medium and reducing the corrosion rate of the Zn-Al diffusion layer. The salt spray test reveals that the initial corrosion products of the Zn-Al diffusion layer are mainly ZnO and Zn₅(OH)₈Cl₂H₂O. New corrosion products such as ZnAl₂O₄, FeOCl appear at the middle corrosion stage. The corrosion product ZnAl₂O₄ disappears, and the corrosion products Zn(OH)₂ and Al(OH)₃ appear at the later corrosion stage.

As is known to all, the incapacity to nucleate holes automatically in the design domain is one of the main issues of the classical level set topology optimization method. To solve the issue of hole nucleation, this paper employs the bi-directional evolutionary structural optimization (BESO) method based on the material removal scheme and the frequently used topological sensitivity and proposes the combining BESO and topological sensitivity (CBT) method for level set topology optimization. This method can replace the existing hole nucleation method for level set topology optimization. First, the topological sensitivity is combined with BESO, and the BESO method based on topological sensitivity is proposed. Second, the method is integrated into level set topology optimization to solve the issue of hole nucleation. Two sensitivity thresholds are defined depending on the evolutionary volume ratio and boundary topological sensitivity, respectively, and the smaller one is used as the sensitivity threshold for hole nucleation. The material is removed from the design domain to nucleate holes based on this threshold. Three classical two-dimensional numerical examples are used to validate the proposed hole nucleation method.