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Manipulating Nanoparticle-Modified Melt Pool Dynamics in Additive Manufacturing

增材制造中纳米颗粒改性熔池动力学的操控

基本信息

批准号：
1934367
负责人：
Wing Liu
金额：
$ 77.74万
依托单位：
Northwestern University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-12-01 至 2024-11-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1934367&HistoricalAwards=false
关键词：
Manipulating Nanoparticle Modified Melt Pool

项目摘要

Metal additive manufacturing (AM), the layer-by-layer printing of 3D shapes, is an emerging and potentially disruptive technology that allows the efficient fabrication of intricate parts that cannot be made using other manufacturing methods. However, because of the high temperature and repeated melting and solidification to which the metal is exposed as it is printed, structural flaws such as pores and cracks are common in AM parts, and only a small number of metals have been successfully used in the process. This research will study the benefits of adding nano-sized ceramic particles to the material during the AM process. Early experiments have shown that the presence of nanoparticles can favorably affect the flow of the molten metal and the formation of microscale structures, eliminating cracking and improving part quality. In many cases, however, the causes of these experimental results are not well understood. Through the development of predictive theory and models for these phenomena, the current work aims to provide scientific understanding of nanoparticle effects, and yield new strategies for controlling and optimizing AM part quality. Broadening the use of AM will advance the competitiveness of U.S. manufacturing and significantly impact U.S. industry by enabling the rapid production of highly customizable parts. The main technical objective of the researched work is to cultivate a physical theory and computational simulations for the dynamics of a nanoparticle-modified melt pool in metallic AM. The research will be undertaken through three interrelated tasks. First, thermophysical behavior of liquid metal with dilute and dense nanoparticles will be investigated by combining spatially inhomogeneous population balance equations (PBEs) and computational thermal fluid dynamics (CTFD). The effects of nanoparticles on thermophysical properties in liquid metal will be characterized and validated. Second, transport and aggregation of nanoparticles will be predicted by building a mechanistic model of aggregation and breakage processes; the model will be validated against measurements of particle distributions in solidified material. Finally, to unravel mechanisms of nanoparticle-induced grain refinement and hot cracking reduction, the thermal and particle information obtained from previous thrust areas will be coupled with a detailed solidification model, in which a cellular automaton (CA) grain growth simulation and an intergranular flow model will predict cracking susceptibility. Effects of nanoparticles will be included via a physics-based nucleation model to elucidate nanoparticle-affected hot cracking mechanics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

金属增材制造（AM），即3D形状的逐层打印，是一种新兴的和潜在的颠覆性技术，可以有效地制造使用其他制造方法无法制造的复杂零件。然而，由于金属在打印时暴露于高温和反复熔化和固化，AM部件中常见孔隙和裂纹等结构缺陷，只有少数金属成功用于该过程。本研究将研究在AM过程中向材料中添加纳米尺寸的陶瓷颗粒的益处。早期的实验已经表明，纳米颗粒的存在可以有利地影响熔融金属的流动和微尺度结构的形成，从而消除裂纹并提高零件质量。然而，在许多情况下，这些实验结果的原因并没有得到很好的理解。通过对这些现象的预测理论和模型的发展，目前的工作旨在提供对纳米颗粒效应的科学理解，并产生控制和优化AM部件质量的新策略。扩大AM的使用将提高美国制造业的竞争力，并通过快速生产高度可定制的零件来显着影响美国工业。研究工作的主要技术目标是培养一个物理理论和计算模拟的纳米粒子改性的金属AM中的熔池的动力学。这项研究将通过三项相互关联的任务进行。首先，将空间非均匀粒子数平衡方程（PBE）和计算热流体动力学（CTFD）相结合，研究了含有稀密纳米颗粒的液态金属的热物理行为。纳米颗粒对液态金属热物理性质的影响将得到表征和验证。其次，纳米颗粒的运输和聚集将通过建立聚集和破碎过程的机械模型来预测;该模型将针对固化材料中颗粒分布的测量进行验证。最后，解开纳米颗粒诱导的晶粒细化和热裂纹减少的机制，从以前的推力区域获得的热和颗粒信息将与详细的凝固模型，其中的元胞自动机（CA）晶粒生长模拟和晶间流动模型将预测裂纹敏感性。纳米颗粒的影响将通过基于物理的成核模型来阐明纳米颗粒影响的热裂力学。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Adaptive hyper reduction for additive manufacturing thermal fluid analysis

DOI：
10.1016/j.cma.2020.113312
发表时间：
2020-12-01
期刊：
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
影响因子：
7.2
作者：
Lu, Ye;Jones, Kevontrez Kyvon;Liu, Wing Kam
通讯作者：
Liu, Wing Kam

HiDeNN-TD: Reduced-order hierarchical deep learning neural networks

HiDeNN-TD：降阶分层深度学习神经网络

DOI：
10.1016/j.cma.2021.114414
发表时间：
2022
期刊：
Computer Methods in Applied Mechanics and Engineering
影响因子：
7.2
作者：
Zhang, Lei;Lu, Ye;Tang, Shaoqiang;Liu, Wing Kam
通讯作者：
Liu, Wing Kam

X-ray computed tomography analysis of pore deformation in IN718 made with directed energy deposition via in-situ tensile testing

DOI：
10.1016/j.ijsolstr.2022.111943
发表时间：
2022-08
期刊：
International Journal of Solids and Structures
影响因子：
3.6
作者：
O. L. Kafka;Cheng Yu;Puikei Cheng;S. Wolff;Jennifer L. Bennett;E. Garboczi;Jian Cao;Xianghui Xiao;Wing Kam Liu
通讯作者：
O. L. Kafka;Cheng Yu;Puikei Cheng;S. Wolff;Jennifer L. Bennett;E. Garboczi;Jian Cao;Xianghui Xiao;Wing Kam Liu

Linking process parameters with lack-of-fusion porosity for laser powder bed fusion metal additive manufacturing

将工艺参数与激光粉末床熔融金属增材制造的未熔合孔隙率联系起来

DOI：
10.1016/j.addma.2023.103500
发表时间：
2023
期刊：
Additive Manufacturing
影响因子：
11
作者：
Mojumder, Satyajit;Gan, Zhengtao;Li, Yangfan;Amin, Abdullah Al;Liu, Wing Kam
通讯作者：
Liu, Wing Kam

Data-driven analysis of process, structure, and properties of additively manufactured Inconel 718 thin walls