当前位置: X-MOL 学术Addit. Manuf. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An analytical method for powder flow characterisation in direct energy deposition
Additive Manufacturing ( IF 11.0 ) Pub Date : 2021-04-20 , DOI: 10.1016/j.addma.2021.101991
Adrien Mouchard , Michael Pomeroy , Jeremy Robinson , Bryan McAuliffe , Simon Donovan , David Tanner

In Direct Energy Deposition, manufacturers require a simple and economical technique to simulate a given powder flux. This study proposes a novel analytical method based on a straightforward measurement technique to reverse engineer the powder flow distribution of a coaxial annular nozzle up to its focus position. Different axial profiles of powder concentration were obtained by blowing powder over a coated plate at different working distances. The observed marks were then discretised into a mixture of Gaussian density of probabilities. A predictive model correlating information between the powder flow profiles to reproduce the powder flow as a sum of continuous statistical functions, each associated to an individual trajectory was developed. This method is assessed on a random nozzle to prove its reliability. The model was trained using data from seven low working distance profiles. It was then tested on two horizontal planes closer to the powder focus and one tilted plane taken at a low working distance. The model shows good predictability with an average R2 of 0.874 for the profiles of the plane nearest to the powder focus, which is very similar to the training phase R2. Regarding the tilted plane, the model was able to predict expected variations on the dispersion and the centroids’ positions, which demonstrates the validity of an application to complex surfaces.



中文翻译:

直接能量沉积中粉末流动特性的分析方法

在直接能量沉积中,制造商需要一种简单且经济的技术来模拟给定的粉末通量。这项研究提出了一种基于直接测量技术的新颖分析方法,可对同轴环形喷嘴直至其焦点位置的粉末流量分布进行逆向工程。通过以不同的工作距离将粉末吹到涂层板上可以得到不同的粉末浓度轴向分布图。然后将观察到的标记离散为高斯概率密度的混合物。建立了一个预测模型,该模型将粉末流动曲线之间的信息相关联,以将粉末流动作为连续统计函数的总和进行再现,每个统计函数都与一个单独的轨迹相关联。在随机喷嘴上对该方法进行了评估,以证明其可靠性。使用来自七个低工作距离剖面的数据对模型进行了训练。然后在更靠近粉末焦点的两个水平面和一个低工作距离的倾斜平面上进行了测试。该模型显示出良好的可预测性,平均R最接近粉末焦点的平面轮廓的0.82中的2,非常类似于训练阶段R 2。关于倾斜平面,该模型能够预测色散和质心位置的预期变化,从而证明了在复杂表面上应用的有效性。

更新日期:2021-04-23
down
wechat
bug