CAREER: Understanding Dynamic Recrystallization Mechanisms in Hybrid In-situ Rolled Additive Manufacturing

职业:了解混合原位轧制增材制造中的动态再结晶机制

基本信息

  • 批准号:
    2237401
  • 负责人:
  • 金额:
    $ 50.36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-06-01 至 2028-05-31
  • 项目状态:
    未结题

项目摘要

This Faculty Early Career Development (CAREER) project aims to generate new knowledge necessary for establishing a novel, hybrid in-situ rolled additive manufacturing (HI-RAM) process. Fusion-based metal additive manufacturing employs a high-energy heat source to fabricate three-dimensional (3D) metal and metal-based parts through a layer-by-layer process. Despite the high density, additive parts have inherent limitations in mechanical properties such as anisotropy and low ductility, which will significantly hinder their use in critical structural applications. To address these limitations, this project will perform fundamental research to enable a transformative manufacturing process—HI-RAM. This new process incorporates an in-situ thermomechanical hot rolling process in the additive manufacturing process, in which a micro-roller trails the heat source and rolls the deposited metal bead. The high-performance structural parts fabricated by HI-RAM could increase the adoption of 3D printed metal parts by many industries, and thus HI-RAM could significantly enhance U.S. manufacturing leadership. This project will build partnerships with colleges, high schools, local manufacturers, and manufacturing organizations to deliver professional training related to HI-RAM, aimed at motivating and preparing a high-quality manufacturing workforce. The project involves multiple disciplines, including advanced manufacturing, materials science, structural mechanics, and applied mathematics, and also expects to broaden the participation of women and underrepresented minorities and strengthen education in STEM. The HI-RAM technology could drastically improve the mechanical properties of additive metals by eliminating anisotropy, improving ductility, and increasing strength, through the mechanism of recrystallization-induced texture elimination and grain refinement. A new 3D multi-physics simulation platform will be established to study the dynamic recrystallization mechanisms, which will be the first model to accurately and efficiently capture the thermal-mechanical-metallurgical relationship in deformation-enhanced 3D printing. The project will address gaps in knowledge about the relationships between dynamic recrystallization and additive manufacturing’s non-equilibrium features and in-situ plastic deformation. It will explore strategies to obtain homogeneous recrystallization in the as-printed textured microstructure, using rolling parameters, roller profiles, and the cyclic and accumulative process conditions. Additionally, this project will investigate the critical multi-physics phenomena to guarantee process performance, such as laser–material interaction, solidification, crystal plasticity, and recrystallization. While this research focuses on the promising in-situ hot rolling and laser-directed energy deposition process, the research outcomes and manufacturing methodology will inform different metal additive manufacturing processes and microscopic forming processes. This project is jointly funded by the Advanced Manufacturing Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.
该教师早期职业发展 (CAREER) 项目旨在产生建立新型混合原位轧制增材制造 (HI-RAM) 工艺所需的新知识,该工艺采用高能热源来制造三种材料。通过逐层工艺生产三维(3D)金属和金属基零件尽管密度高,但增材零件在机械性能方面存在固有的局限性,例如各向异性和低延展性,这将严重阻碍它们在关键结构应用中的使用。 .为了解决这些为了克服这些限制,该项目将进行基础研究,以实现变革性的制造工艺——HI-RAM。这种新工艺在增材制造工艺中采用了原位热机械热轧工艺,其中微型辊跟踪热源并滚动。 HI-RAM 制造的高性能结构部件可以增加许多行业对 3D 打印金属部件的采用,因此 HI-RAM 可以显着增强美国的制造业领导地位。该项目将与大学、高等院校建立合作伙伴关系。该项目涉及先进制造、材料科学、结构力学、应用数学等多个学科,还期望扩大女性和代表性不足的少数族裔的参与,并加强 STEM 教育。HI-RAM 技术可以通过消除各向异性、提高延展性和增加强度来显着提高添加剂金属的机械性能。再结晶引起的织构消除和晶粒细化将建立一个新的3D多物理模拟平台来研究动态再结晶机制,这将是第一个准确有效地捕获变形增强3D中的热-机械-冶金关系的模型。该项目将解决动态再结晶与增材制造的非平衡特征和原位塑性变形之间关系的知识空白。此外,该项目还将研究关键的多物理现象,以保证工艺性能,例如激光材料。虽然这项研究的重点是有前景的原位热轧和激光定向能量沉积工艺,但研究成果和制造方法将为不同的金属增材制造工艺和技术提供参考。该项目由先进制造计划和刺激竞争研究既定计划 (EPSCoR) 联合资助。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查进行评估,认为值得支持。标准。

项目成果

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Shunyu Liu其他文献

Rapid detection method for insulation performance of vacuum glass based on ensemble learning
基于集成学习的真空玻璃隔热性能快速检测方法
  • DOI:
    10.1016/j.engappai.2024.108106
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Xiaoling Li;Shunyu Liu;Yuanqi Wang;Fuquan Zhou;Lei Wang
  • 通讯作者:
    Lei Wang
Prediction of 3D microstructure and phase distributions of Ti6Al4V built by the directed energy deposition process via combined multi-physics models
通过组合多物理模型预测定向能量沉积工艺构建的 Ti6Al4V 的 3D 微观结构和相分布
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shunyu Liu;Y. Shin
  • 通讯作者:
    Y. Shin
Framework: the Meaning of Securitization and the Method of JST
框架:证券化的含义和JST的方法
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shunyu Liu;Y. Shin
  • 通讯作者:
    Y. Shin
Temporal Prototype-Aware Learning for Active Voltage Control on Power Distribution Networks
配电网络有源电压控制的时间原型感知学习
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Feiyang Xu;Shunyu Liu;Yunpeng Qing;Yihe Zhou;Yuwen Wang;Mingli Song
  • 通讯作者:
    Mingli Song

Shunyu Liu的其他文献

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