残余应力
图像扭曲
融合
残余物
航空航天
材料科学
计算机科学
质量(理念)
过程(计算)
块(置换群论)
机械工程
工艺工程
工程制图
复合材料
人工智能
工程类
算法
数学
航空航天工程
哲学
操作系统
认识论
语言学
几何学
作者
Antonios Dimopoulos,Mohamad Salimi,Tat‐Hean Gan,Panagiotis Chatzakos
出处
期刊:Materials
[MDPI AG]
日期:2023-11-14
卷期号:16 (22): 7164-7164
被引量:7
摘要
This study focuses on Metal Additive Manufacturing (AM), an emerging method known for its ability to create lightweight components and intricate designs. However, Laser Powder Bed Fusion (LPBF), a prominent AM technique, faces a major challenge due to the development of high residual stress, resulting in flawed parts and printing failures. The study’s goal was to assess the thermal behaviour of different support structures and optimised designs to reduce the support volume and residual stress while ensuring high-quality prints. To explore this, L-shaped specimens were printed using block-type support structures through an LPBF machine. This process was subsequently validated through numerical simulations, which were in alignment with experimental observations. In addition to block-type support structures, line, contour, and cone supports were examined numerically to identify the optimal solutions that minimise the support volume and residual stress while maintaining high-quality prints. The optimisation approach was based on the Design of Experiments (DOE) methodology and multi-objective optimisation. The findings revealed that block supports exhibited excellent thermal behaviour. High-density supports outperformed low-density alternatives in temperature distribution, while cone-type supports were more susceptible to warping. These insights provide valuable guidance for improving the metal AM and LPBF processes, enabling their broader use in industries like aerospace, medical, defence, and automotive.
科研通智能强力驱动
Strongly Powered by AbleSci AI