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采用桥曲率法通过选择性激光熔化技术制造的铝部件中的残余应力累积

Residual Stress Build-Up in Aluminum Parts Fabricated with SLM Technology Using the Bridge Curvature Method.

作者信息

Ma Quoc-Phu, Mesicek Jakub, Fojtik Frantisek, Hajnys Jiri, Krpec Pavel, Pagac Marek, Petru Jana

机构信息

Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70833 Ostrava, Czech Republic.

Department of Applied Mechanics, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70833 Ostrava, Czech Republic.

出版信息

Materials (Basel). 2022 Sep 1;15(17):6057. doi: 10.3390/ma15176057.

DOI:10.3390/ma15176057
PMID:36079438
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9457910/
Abstract

In metal 3D printing with Selective Laser Melting (SLM) technology, due to large thermal gradients, the residual stress (RS) distribution is complicated to predict and control. RS can distort the shape of the components, causing severe failures in fabrication or functionality. Thus, several research papers have attempted to quantify the RS by designing geometries that distort in a predictable manner, including the Bridge Curvature Method (BCM). Being different from the existing literature, this paper provides a new perspective of the RS build-up in aluminum parts produced with SLM using a combination of experiments and simulations. In particular, the bridge samples are printed with AlSi10Mg, of which the printing process and the RS distribution are experimentally assessed with the Hole Drilling Method (HDM) and simulated using ANSYS and Simufact Additive. Subsequently, on the basis of the findings, suggestions for improvements to the BCM are made. Throughout the assessment of BCM, readers can gain insights on how RS is built-up in metallic 3D-printed components, some available tools, and their suitability for RS prediction. These are essential for practitioners to improve the precision and functionality of SLM parts should any post-subtractive or additive manufacturing processes be employed.

摘要

在采用选择性激光熔化(SLM)技术的金属3D打印中,由于热梯度较大,残余应力(RS)分布难以预测和控制。残余应力会使部件形状变形,导致制造过程或功能出现严重故障。因此,一些研究论文试图通过设计以可预测方式变形的几何形状来量化残余应力,包括桥曲率法(BCM)。与现有文献不同,本文结合实验和模拟,为采用SLM生产的铝部件中残余应力的形成提供了新的视角。具体而言,使用AlSi10Mg打印桥形样品,采用盲孔法(HDM)对其打印过程和残余应力分布进行实验评估,并使用ANSYS和Simufact Additive进行模拟。随后,基于这些发现,对桥曲率法提出改进建议。在对桥曲率法的整个评估过程中,读者可以深入了解残余应力在金属3D打印部件中是如何形成的、一些可用工具以及它们对残余应力预测的适用性。对于从业者来说,如果采用任何后续减材或增材制造工艺来提高SLM部件的精度和功能,这些都是至关重要的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/de5700fc3554/materials-15-06057-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/fc82ce34a96e/materials-15-06057-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/536502d7eeab/materials-15-06057-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/322f76965327/materials-15-06057-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/2a9c0cb5e51a/materials-15-06057-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/e512ccc1e341/materials-15-06057-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/5cadc5d3b78c/materials-15-06057-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/8b5400d3aa51/materials-15-06057-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/f236810e4b44/materials-15-06057-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/281b9dc8cec0/materials-15-06057-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/de5700fc3554/materials-15-06057-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/fc82ce34a96e/materials-15-06057-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/536502d7eeab/materials-15-06057-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/322f76965327/materials-15-06057-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/2a9c0cb5e51a/materials-15-06057-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/e512ccc1e341/materials-15-06057-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/5cadc5d3b78c/materials-15-06057-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/8b5400d3aa51/materials-15-06057-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/f236810e4b44/materials-15-06057-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/281b9dc8cec0/materials-15-06057-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce14/9457910/de5700fc3554/materials-15-06057-g009.jpg

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