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不同初始形貌对Ti6Al4V激光抛光中熔体流体动力学影响的数值模拟

Numerical Simulation of Effect of Different Initial Morphologies on Melt Hydrodynamics in Laser Polishing of Ti6Al4V.

作者信息

Li Kai, Zhao Zhenyu, Zhou Houming, Zhou Hao, Yin Jie, Zhang Wei, Zhou Guiyao

机构信息

School of Intelligent Manufacturing and Equipment, Shenzhen Institute of Information Technology, Shenzhen 518172, China.

School of Mechanical Engineering, Xiangtan University, Xiangtan 411105, China.

出版信息

Micromachines (Basel). 2021 May 20;12(5):581. doi: 10.3390/mi12050581.

DOI:10.3390/mi12050581
PMID:34065273
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8160783/
Abstract

As a surface finishing technique for rapid remelting and re-solidification, laser polishing can effectively eliminate the asperities so as to approach the feature size. Nevertheless, the polished surface quality is significantly sensitive to the processing parameters, especially with respect to melt hydrodynamics. In this paper, a transient two-dimensional model was developed to demonstrate the molten flow behavior for different surface morphologies of the Ti6Al4V alloy. It is illustrated that the complex evolution of the melt hydrodynamics involving heat conduction, thermal convection, thermal radiation, melting and solidification during laser polishing. Results show that the uniformity of the distribution of surface peaks and valleys can improve the molten flow stability and obtain better smoothing effect. The high cooling rate of the molten pool resulting in a shortening of the molten lifetime, which prevents the peaks from being removed by capillary and thermocapillary forces. It is revealed that the mechanism of secondary roughness formation on polished surface. Moreover, the double spiral nest Marangoni convection extrudes the molten to the outsides. It results in the formation of expansion and depression, corresponding to nearby the starting position and at the edges of the polished surface. It is further found that the difference between the simulation and experimental depression depths is only about 2 μm. Correspondingly, the errors are approximately 8.3%, 14.3% and 13.3%, corresponding to Models 1, 2 and 3, respectively. The aforementioned results illustrated that the predicted surface profiles agree reasonably well with the experimentally measured surface height data.

摘要

作为一种用于快速重熔和再凝固的表面处理技术,激光抛光能够有效消除粗糙不平之处,从而接近特征尺寸。然而,抛光后的表面质量对加工参数极为敏感,尤其是在熔体流体动力学方面。本文建立了一个瞬态二维模型,以展示Ti6Al4V合金不同表面形貌下的熔体流动行为。结果表明,激光抛光过程中熔体流体动力学涉及热传导、热对流、热辐射、熔化和凝固等复杂的演变过程。结果显示,表面峰谷分布的均匀性可提高熔体流动稳定性并获得更好的平滑效果。熔池的高冷却速率导致熔体寿命缩短,这阻碍了峰部被毛细管力和热毛细力去除。揭示了抛光表面二次粗糙度形成的机制。此外,双螺旋巢状马兰戈尼对流将熔体挤压到外部。这导致在靠近起始位置和抛光表面边缘处形成凸起和凹陷。进一步发现,模拟和实验得到的凹陷深度之差仅约为2μm。相应地,模型1、2和3的误差分别约为8.3%、14.3%和13.3%。上述结果表明,预测的表面轮廓与实验测量的表面高度数据相当吻合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/6e16380d602d/micromachines-12-00581-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/08cb607f368b/micromachines-12-00581-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/05dedc8173fc/micromachines-12-00581-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/f475ec1a7a52/micromachines-12-00581-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/8bfdc02270c0/micromachines-12-00581-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/0fa2f6c9ff89/micromachines-12-00581-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/1c45a656ef97/micromachines-12-00581-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/2f295f34daba/micromachines-12-00581-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/d23bb5c43a63/micromachines-12-00581-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/6fae3f6627f4/micromachines-12-00581-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/2d5604a35c4c/micromachines-12-00581-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/cd284ba226d8/micromachines-12-00581-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/6e16380d602d/micromachines-12-00581-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/08cb607f368b/micromachines-12-00581-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/05dedc8173fc/micromachines-12-00581-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/f475ec1a7a52/micromachines-12-00581-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/8bfdc02270c0/micromachines-12-00581-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/0fa2f6c9ff89/micromachines-12-00581-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/1c45a656ef97/micromachines-12-00581-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/2f295f34daba/micromachines-12-00581-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/d23bb5c43a63/micromachines-12-00581-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/6fae3f6627f4/micromachines-12-00581-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/2d5604a35c4c/micromachines-12-00581-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/cd284ba226d8/micromachines-12-00581-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee6/8160783/6e16380d602d/micromachines-12-00581-g012.jpg

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