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Computational Tools for Polycrystalline Materials

多晶材料的计算工具

基本信息

批准号：
1719727
负责人：
Selim Esedoglu
金额：
$ 20.19万
依托单位：
Regents of the University of Michigan - Ann Arbor
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
起止时间：
2017-07-01 至 2022-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1719727&HistoricalAwards=false
关键词：
Computational Tools Polycrystalline Materials

项目摘要

This project will develop new algorithms for computer simulation of how the internal structure (called microstructure) of many technologically essential materials, such as most metals and ceramics, change during common manufacturing processes such as heat treatment. The microstructure of such materials is known to have implications for the physical properties, such as conductivity or yield strength, of the material. Although models describing how the microstructure evolves, for example during heat treatment, have been available, their efficient numerical simulation at scales large enough to be of practical interest to materials scientists have remained a challenge. The project will address this challenge. Understanding the evolution of microstructure holds the promise of materials with more desirable characteristics. The project will also develop machine learning and computer vision algorithms for automatically extracting microstructure information from experimental measurements (microscopy images) of such materials, so that predictions of the models to be simulated can be more readily checked against experiments. One Ph.D. student's training and thesis work will be an integral part of the research.Continuum models of interfacial motion in polycrystalline materials often take the form of a system of nonlinear partial differential equations describing the geometric flow of a network of surfaces. For certain important interfacial phenomena, such as grain boundary motion, the evolution is given by second order differential equations describing motion by mean curvature of the network. For that setting, a surprisingly simple, elegant, and efficient class of algorithms known as threshold dynamics have been developed that makes large scale simulation particularly feasible. Other phenomena, such as the motion of the free surface of a thin polycrystalline film, or that of pores in a sintered metal, are described by higher order geometric evolutions, such as motion by surface diffusion, and are more challenging to simulate. This project will develop efficient algorithms for such high order multi-phase geometric evolutions. In particular, it will explore whether threshold dynamics or a combination of it with phase field methods can be devised to simulate the motion of networks of surfaces in which some of the interfaces evolve via motion by mean curvature, and others via motion by surface diffusion, coupled along free boundaries known as junctions along which appropriate boundary conditions are satisfied. Some of these models describing the multi-phase geometric motion of networks of interfaces also arise almost verbatim in the context of computer vision and machine learning. By leveraging this mathematical connection, the project will also develop new algorithms for automatically extracting grain boundaries in microscopy images of real polycrystalline materials.

该项目将开发新的算法，用于计算机模拟许多技术关键材料（如大多数金属和陶瓷）的内部结构（称为微观结构）如何在热处理等常见制造过程中发生变化。已知此类材料的微观结构对材料的物理性质（例如导电性或屈服强度）具有影响。虽然描述微观结构如何演变的模型，例如在热处理过程中，已经可用，但它们在足够大的尺度上的有效数值模拟仍然是材料科学家的实际兴趣。该项目将应对这一挑战。了解微观结构的演变有望使材料具有更理想的特性。该项目还将开发机器学习和计算机视觉算法，用于从这些材料的实验测量（显微镜图像）中自动提取微观结构信息，以便更容易根据实验检查要模拟的模型的预测。一个博士学生的训练和论文工作将是研究的一个组成部分。多晶材料中界面运动的连续介质模型通常采用描述表面网络几何流动的非线性偏微分方程系统的形式。对于某些重要的界面现象，例如晶界运动，其演化由通过网络平均曲率描述运动的二阶微分方程给出。对于这种设置，已经开发出一种令人惊讶的简单，优雅和高效的算法，称为阈值动态，使大规模模拟特别可行。其他现象，如薄的多晶膜的自由表面的运动，或烧结金属中的孔的运动，由更高阶的几何演化描述，如表面扩散的运动，并且更具有挑战性的模拟。本计画将针对高阶多阶段几何演化发展有效演算法。特别是，它将探讨是否可以设计阈值动力学或相场方法相结合，以模拟网络的表面，其中一些接口通过运动平均曲率，和其他通过运动的表面扩散，耦合沿着自由边界称为路口沿着，其中适当的边界条件得到满足的运动。其中一些描述界面网络的多相几何运动的模型也几乎逐字出现在计算机视觉和机器学习的背景下。通过利用这种数学联系，该项目还将开发新的算法，用于自动提取真实的多晶材料显微镜图像中的晶界。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

On the Voronoi Implicit Interface Method

关于Voronoi隐式接口方法

DOI：
10.1137/18m1222569
发表时间：
2019
期刊：
SIAM Journal on Scientific Computing
影响因子：
3.1
作者：
Zaitzeff, Alexander;Esedoglu, Selim;Garikipati, Krishna
通讯作者：
Garikipati, Krishna

Second order threshold dynamics schemes for two phase motion by mean curvature

平均曲率两相运动的二阶阈值动力学方案

DOI：
10.1016/j.jcp.2020.109404
发表时间：
2020
期刊：
Journal of Computational Physics
影响因子：
4.1
作者：
Zaitzeff, Alexander;Esedoḡlu, Selim;Garikipati, Krishna
通讯作者：
Garikipati, Krishna

Statistics of grain growth: Experiment versus the phase-field-crystal and Mullins models

晶粒生长统计：实验与相场晶体和 Mullins 模型的比较

DOI：
10.1016/j.mtla.2019.100280
发表时间：
2019
期刊：
Materialia
影响因子：
3.4
作者：
Martine La Boissonière, Gabriel;Choksi, Rustum;Barmak, Katayun;Esedoḡlu, Selim
通讯作者：
Esedoḡlu, Selim

High order, semi-implicit, energy stable schemes for gradient flows

DOI：
10.1016/j.jcp.2021.110688
发表时间：
2020-07
期刊：
J. Comput. Phys.
影响因子：
0
作者：
Alexander Zaitzeff;S. Esedoglu;K. Garikipati
通讯作者：
Alexander Zaitzeff;S. Esedoglu;K. Garikipati

A robust algorithm to calculate parent β grain shapes and orientations from α phase electron backscatter diffraction data in α/β-titanium alloys

一种强大的算法，用于根据 α/β 钛合金中的 α 相电子背散射衍射数据计算母体 β 晶粒形状和方向

DOI：
10.1016/j.scriptamat.2020.09.038
发表时间：
2021
期刊：
Scripta Materialia
影响因子：
6
作者：
Zaitzeff, Alexander;Pilchak, Adam;Berman, Tracy;Allison, John;Esedoglu, Selim
通讯作者：
Esedoglu, Selim