Predictive modeling of laser and electron beam powder bed fusion additive manufacturing of metals at the mesoscale

材料科学 热导率 惯性约束聚变 金属粉末 融合 激光器 蒙特卡罗方法 中尺度气象学 光学 复合材料 金属 冶金 物理 哲学 地质学 统计 气候学 语言学 数学
作者
Andrey Zakirov,Sergei Belousov,М. В. Богданова,Boris Korneev,A. Stepanov,Anastasia Perepelkina,Vadim Levchenko,Andrey Meshkov,Б. В. Потапкин
出处
期刊:Additive manufacturing [Elsevier]
卷期号:35: 101236-101236 被引量:58
标识
DOI:10.1016/j.addma.2020.101236
摘要

We present the results of 3D modeling of the laser and electron beam powder bed fusion process at the mesoscale with an in-house developed advanced multiphysical numerical tool. The hydrodynamics and thermal conductivity core of the tool is based on the lattice Boltzmann method. The numerical tool takes into account the random distributions of powder particles by size in a layer and the propagation of the laser (electron beam) with a full ray tracing (Monte Carlo) model that includes multiple reflections, phase transitions, thermal conductivity, and detailed liquid dynamics of the molten metal, influenced by evaporation of the metal and the recoil pressure. The model has been validated by a number of physical tests. We numerically demonstrate a strong dependence of the net energy absorption of the incoming heat source beam by the powder bed and melt pool on the beam power. We show the ability of our model to predict the measurable properties of a single track on a bare substrate as well as on a powder layer. We obtain good agreement with experimental data for the depth, width and shape of a track for a number of materials and a wide range of energy source parameters. We further apply our model to the simulation of the entire layer formation and demonstrate the strong dependence of the resulting layer morphology on the hatch spacing. The presented model could be very helpful for optimizing the additive process without carrying out a large number of experiments in a common trial-and-error method, developing process parameters for new materials, and assessing novel modalities of powder bed fusion additive manufacturing.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
yuky完成签到 ,获得积分10
2秒前
乐易完成签到 ,获得积分10
3秒前
orixero应助tk采纳,获得10
3秒前
3秒前
4秒前
华仔应助橘络采纳,获得10
4秒前
QAQ完成签到,获得积分10
4秒前
李雩完成签到,获得积分10
5秒前
多肉葡萄发布了新的文献求助10
5秒前
5秒前
6秒前
聪明勇敢有力气完成签到 ,获得积分10
6秒前
jjjj发布了新的文献求助10
7秒前
zcz完成签到,获得积分10
7秒前
TaoJ发布了新的文献求助10
8秒前
orixero应助猪肉水饺采纳,获得10
8秒前
卷卷516发布了新的文献求助10
8秒前
9秒前
9秒前
Hello应助独特的易形采纳,获得10
11秒前
JamesPei应助JWZhang采纳,获得10
11秒前
chenyan完成签到,获得积分10
11秒前
13秒前
14秒前
14秒前
南风平发布了新的文献求助10
14秒前
15秒前
纸鹤完成签到,获得积分10
16秒前
16秒前
愤怒的水壶完成签到,获得积分10
18秒前
18秒前
纸鹤发布了新的文献求助10
18秒前
杨飞完成签到,获得积分10
18秒前
小蘑菇应助快乐友易采纳,获得10
18秒前
lvben发布了新的文献求助10
19秒前
19秒前
19秒前
20秒前
傲娇梦旋发布了新的文献求助10
20秒前
21秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2500
Востребованный временем 2500
Aspects of Babylonian celestial divination : the lunar eclipse tablets of enuma anu enlil 1500
Agaricales of New Zealand 1: Pluteaceae - Entolomataceae 1040
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 1000
Classics in Total Synthesis IV: New Targets, Strategies, Methods 1000
지식생태학: 생태학, 죽은 지식을 깨우다 600
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3458818
求助须知:如何正确求助?哪些是违规求助? 3053567
关于积分的说明 9036986
捐赠科研通 2742746
什么是DOI,文献DOI怎么找? 1504524
科研通“疑难数据库(出版商)”最低求助积分说明 695334
邀请新用户注册赠送积分活动 694537