Manufacturing by Design

设计制造

• 批准号: EP/W003333/1
• 负责人: Philip Withers
• 金额: $ 205.47万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW003333%2F1
• 关键词: Manufacturing; Design

In highly engineered materials, microscale defects can determine failure modes at the compo-nent/system scale. While X-ray CT is unique in being able to image, find, and follow defects non-destructively at the microscale, currently it can only do so for mm sized samples. This currently presents a significant limitation for manufacturing design and safe life prediction where the nature and location of the defects are a direct consequence of the manufacturing process. For example, in additive manufacturing, the defects made when manufacturing a test-piece may be quite different from those in a three dimensionally complex additively manufactured engineering component. Similarly, for composite materials, small-scale samples are commonly not large enough to properly represent all the hierarchical scales that control structural behaviour. This collaboration between the European Research Radiation Facility (ESRF) and the National Research Facility for laboratory CT (NRF) will lead to a million-fold increase in the volume of material that can be X-ray imaged at micrometre resolution through the development and exploitation of a new beamline (BM18). Further, this unparalleled resolution for X-rays at energies up to 400keV enables high Z materials to be probed as well as complex environmental stages. This represents a paradigm shift allowing us to move from defects in sub-scale test-pieces, to those in manufactured components and devices. This will be complemented by a better understanding of how such defects are introduced during manufacture and assembly. It will also allow us to scout and zoom manufactured structures to identify the broader defect distribution and then to follow the evolution of specific defects in a time-lapse manner as a function of mechanical or environmental loads, to learn how they lead to rapid failure in service. This will help to steer the design of smarter manufacturing processes tailored to the individual part geometry/architecture and help to establish a digital twin of additive and composite manufacturing processes.Secondly, we will exploit high frame rate imaging on ID19 exploiting the increased flux available due to the new ESRF-extremely bright source upgrade to study the mechanisms by which defects are introduced during additive manufacture and how defects can lead to very rapid failures, such as thermal runaway in batteriesIn this project, we will specifically focus on additive manufacturing, composite materials manufacturing and battery manufacturing and the in situ and operando performance and degradation of such manufactured articles, with the capabilities being disseminated and made more widely available to UK academics and industry through the NRF. The collaboration will also lead to the development of new data handling and analysis processes able to handle the very significant uplift in data that will be obtained and will lead to multiple site collaboration on experiments in real-time. This will enable us to work together as a multisite team on projects thereby involving less travelling and off-setting some of the constraints on demanding experiments posed by COVID-19.

在高度工程化的材料中，微尺度缺陷可以决定组件/系统尺度的失效模式。虽然X射线CT是唯一能够成像，发现和跟踪缺陷的非破坏性的微观尺度，目前它只能这样做毫米大小的样品。这目前对制造设计和安全寿命预测提出了重大限制，其中缺陷的性质和位置是制造过程的直接结果。例如，在增材制造中，在制造测试件时产生的缺陷可能与三维复杂的增材制造工程部件中的缺陷完全不同。类似地，对于复合材料，小尺度样本通常不足以适当地代表控制结构行为的所有层次尺度。欧洲研究辐射设施（ESRF）和国家实验室CT研究设施（NRF）之间的合作将导致通过开发和利用新的光束线（BM 18）以微米分辨率进行X射线成像的材料数量增加一百万倍。此外，对于能量高达400 keV的X射线，这种无与伦比的分辨率使高Z材料能够被探测以及复杂的环境阶段。这代表了一种范式转变，使我们能够从子尺度测试件中的缺陷转移到制造组件和设备中的缺陷。这将通过更好地了解这些缺陷是如何在制造和组装过程中引入的来补充。它还将使我们能够侦察和缩放制造的结构，以识别更广泛的缺陷分布，然后以随机械或环境负载变化的时间推移方式跟踪特定缺陷的演变，以了解它们如何导致服务中的快速故障。这将有助于引导针对单个零件几何形状/架构量身定制的更智能制造工艺的设计，并有助于建立增材和复合材料制造工艺的数字孪生模型。其次，我们将在ID 19上利用高帧率成像，利用新ESRF增加的可用通量-极亮光源升级以研究在增材制造期间引入缺陷的机制以及缺陷如何导致非常快速的故障，在这个项目中，我们将特别关注增材制造、复合材料制造和电池制造，以及这些制品的原位和操作性能和降解，并通过NRF向英国学术界和工业界传播和更广泛地提供这些能力。该合作还将导致开发新的数据处理和分析流程，能够处理将获得的数据中非常重要的提升，并将导致实时实验的多个站点合作。这将使我们能够作为一个多地点团队共同开展项目，从而减少差旅，并抵消COVID-19对高要求实验的一些限制。

项目成果

Additively manufactured high-energy-absorption metamaterials with artificially engineered distribution of bio-inspired hierarchical microstructures

增材制造的高能量吸收超材料，具有人工设计的仿生分层微结构分布

• DOI: 10.1016/j.compositesb.2022.110345
• 发表时间: 2022
• 期刊: Engineering
• 影响因子: 12.8
• 作者: Gao Z

Hardness variation in inconel 718 produced by laser directed energy deposition

• DOI: 10.1016/j.mtla.2022.101643
• 发表时间: 2022-12-01
• 期刊: MATERIALIA
• 影响因子: 3.4
• 作者: Chechik, Lova;Christofidou, Katerina A.;Todd, Iain
• 通讯作者: Todd, Iain

3D Correlative Imaging of Lithium Ion Concentration in a Vertically Oriented Electrode Microstructure with a Density Gradient.

• DOI: 10.1002/advs.202105723
• 发表时间: 2022-05
• 期刊: Advanced science (Weinheim, Baden-Wurttemberg, Germany)

Quantification of Interdependent Dynamics during Laser Additive Manufacturing Using X-Ray Imaging Informed Multi-Physics and Multiphase Simulation.

• DOI: 10.1002/advs.202203546
• 发表时间: 2022-12
• 期刊: ADVANCED SCIENCE
• 影响因子: 15.1
• 作者: Leung, Chu Lun Alex;Luczyniec, Dawid;Guo, Enyu;Marussi, Sebastian;Atwood, Robert C.;Meisnar, Martina;Saunders, Ben;Lee, Peter D.
• 通讯作者: Lee, Peter D.

In situ characterisation of surface roughness and its amplification during multilayer single-track laser powder bed fusion additive manufacturing

• DOI: 10.1016/j.addma.2023.103809
• 发表时间: 2023-10
• 期刊: Additive Manufacturing
• 影响因子: 11
• 作者: Alisha Bhatt;Yuze Huang;C. L. Leung;Gowtham Soundarapandiyan;S. Marussi;Saurabh Shah;Robert C. Atwood-Robe