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2017 Physical Metallurgy Gordon Research Conference and Seminar

2017 Physical Metallurgy Gordon Research Conference and Seminar
2017年物理冶金戈登研究会议暨研讨会
批准号:
1742171
负责人:
Ji-Cheng Zhao
金额:
$1.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-06-01 至 2018-05-31

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中文摘要
翻译
2017年戈登物理冶金研究会议(GRC)的副标题是:物理冶金量化和预测能力的前沿。GRC是物理冶金领域最受欢迎的专题会议之一。它每两年举办一次,为深入讨论该领域的前沿进展和通往未来的途径提供了一个独特的论坛。相关的戈登研究研讨会(GRS)为早期职业研究人员和学生提供了一个展示他们的工作和参与职业讨论的论坛。GRS将于2017年7月22日至23日举行,grc将于2017年7月23日至28日举行,地点均在缅因州比德福德的新英格兰大学。物理冶金领域的研究目标正在发生重大变化,从定性的认识到定量的预测能力。这在很大程度上是由于我们能够处理描述材料结构的大量3d数据,局部评估材料特性,并在高通量实验中获得系统的数据系列。随着3D成像从技术开发到应用的过渡,它允许人们在不同的复杂性和空间分辨率水平上测试建模方法。在这里,实验的直接建模和仿真以及实验结果的逆建模才刚刚开始展示它们的分析能力和提高测量精度的能力。与此同时,该领域的经典核心——材料行为和结构-性能关系的建模,仍然面临着从原子到材料缺陷再到连续介质场方程的不同建模范围之间无缝过渡的困难。因此,该领域的前沿涉及材料信息的系统化和量化,以及建模和仿真预测能力的评估和提高。建模和仿真开始提供复杂环境下材料的热力学信息。小规模的实验可以推进到单个缺陷的规模,并且可以挑战建模,特别是关于材料的机械性能:断裂,疲劳,摩擦和磨损。增材制造对建模提出了新的挑战,同时也为合金开发开辟了全新的途径。这次戈登会议的目的是评估当前该领域的前沿,并概述社区必须解决的核心问题,以促进物理冶金领域的发展,从理解飞秒时间尺度上的原子过程到评估结构部件在服务多年的行为。
英文摘要
Non-Technical AbstractThe 2017 Gordon Research Conference (GRC) on Physical Metallurgy has a subtitle: Frontiers ofQuantification and Predictive Capability in Physical Metallurgy. The GRC is one of the most highlyacclaimed topical conferences in the field of physical metallurgy. Held every two years, it provides aunique forum for in-depth discussion of cut-edging advances in the field and pathways to the future. Theassociated Gordon Research Seminar (GRS) provides a forum for early career researchers and students toshowcase their work and to participate at career discussions. The GRS will be held on July 22-23, and the GRCwill be on July 23-28, 2017, both at University of New England, Biddeford, Maine.Technical AbstractThe field of Physical Metallurgy is currently seeing major changes in its research aims from qualitativeunderstanding to quantitative predictive capability. This is largely driven by our ability to handle massive3D data describing the structure of materials, to locally evaluate materials properties, and to acquiresystematic data series in high-throughput experiments. As 3D imaging is transitioning from techniquedevelopment to application, it permits one to test modeling approaches at different levels of complexityand spatial resolution. Here, the direct modeling and simulation of experiments and the inverse modelingof the experimental results just begin to demonstrate their analytic power and their power to increase theaccuracy of the measurements. Meanwhile, the classical core of the field, modeling of materials behaviorand of structure-property relations, is still challenged by the difficulties to seamlessly transition betweendifferent modeling scopes from atoms to materials defects to continuum field equations. The frontiers ofthe field therefore are concerned with the systematization and the quantification of information onmaterials and with the assessment and increase of the predictive capability of the modeling andsimulation. Modeling and simulation is beginning to provide thermodynamic information on materials incomplex environments. Small scale experiments can be pushed to the scale of individual defects and canchallenge modeling particularly concerning the mechanical properties of materials: fracture, fatigue,friction and wear. Additive manufacturing is posing new challenges to modeling and at the same timeopens entirely new avenues to alloy development. The aim of this Gordon Conference is to assess thesecurrent frontiers of the field and to sketch central questions which the community will have to solve forPhysical Metallurgy to advance as a field that spans from understanding atomistic processes onfemtosecond time scales to assessing the behavior of structural components for years in service.
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会议论文
A New Method to Efficiently and Reliably Measure Ternary Diffusion Coefficients
Collaborative Research: Accurate Prediction of Phase Stability for Chemistry and Process Design of Ni-based Superalloys
  • 批准号:
    2004979
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.96万
  • 财政年份:
    2019
  • 负责人:
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  • 依托单位:
Collaborative Research: Accurate Prediction of Phase Stability for Chemistry and Process Design of Ni-based Superalloys
  • 批准号:
    1825560
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.96万
  • 财政年份:
    2018
  • 负责人:
    Ji-Cheng Zhao
  • 依托单位:
High-Throughput Measurements for High-Fidelity Thermodynamic Databases
国内基金
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面向智能电网基础设施Cyber-Physical安全的自治愈基础理论研究
  • 批准号:
    61300132
  • 项目类别:
    青年科学基金项目
  • 资助金额:
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  • 批准年份:
    2013
  • 负责人:
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