研究目的
This study focuses on the high-resolution characterization of alloy 718 (UNS N07718) single struts (constitutive elements of the lattice) manufactured by SLM. Process parameters, strategy, and post-treatments remain constant while varying strut positions on the build plate and orientations.
研究成果
The build orientation significantly influences the morphology of struts, with inclined struts showing larger size, shape deviation, and waviness but lower porosity compared to vertical struts. The in-plane orientation is identified as a second-order parameter affecting strut shape, roughness, and size. The study provides a systematic methodology for characterizing strut morphology and highlights the importance of considering both build and in-plane orientations in the design and manufacturing of lattice structures.
研究不足
The study is limited to alloy 718 single struts manufactured by SLM. The influence of other materials or manufacturing techniques is not explored. Additionally, the study focuses on specific orientations and positions, which may not cover all possible variations in lattice structures.
1:Experimental Design and Method Selection:
The study utilizes selective laser melting (SLM) for manufacturing alloy 718 single struts with varying positions and orientations on the build plate. High-resolution X-ray tomography is employed for characterization.
2:Sample Selection and Data Sources:
Nineteen samples (six vertical and 13 inclined) are analyzed. The samples are designed to represent the constitutive elements of a lattice structure.
3:List of Experimental Equipment and Materials:
An EOS M290 machine is used for SLM manufacturing. X-ray tomography is performed using an RX Solutions Easytom XL equipped with a nanofocus LaB6 source and a flat panel detector.
4:Experimental Procedures and Operational Workflow:
Struts are manufactured with constant process parameters and post-treatments. X-ray tomography scans are conducted with specific settings to ensure high-resolution imaging.
5:Data Analysis Methods:
Morphological features such as size, shape, waviness, roughness, and porosity are extracted from the 3D images using ImageJ scripts and other computational methods.
独家科研数据包,助您复现前沿成果,加速创新突破
获取完整内容