DRAGen - 一个支持深度学习的RVE生成器框架,用于复杂的微观结构模型
Manuel Henrich1, Niklas Fehlemann1, Felix Bexter1
1Integrity of Materials and Structures, RWTH Aachen University, Intzestraße 1, Aachen, 52064, Germany.
Heliyon
|August 28, 2023
概括
改进的离散RVE自动化和生成框架 (DRAGen) 现在可以生成具有复杂特征的现实微结构. 这种强大的工具支持多个解决方案,并为ICME社区增强微结构研究.
科学领域:
- 计算材料科学科学 计算材料科学
- 材料 信息学 信息学
- 多物理模拟器 多物理模拟器
背景情况:
- 代表体积元素 (RVE) 对于准确的材料建模至关重要.
- 产生具有现实的微观结构特征的RVE在计算上具有挑战性.
- 现有的框架可能缺乏灵活性来结合各种微结构复杂性和解决方案兼容性.
研究的目的:
- 提出一个增强的离散RVE自动化和生成框架 (DRAGen).
- 为了实现具有复杂和现实的微观结构特征的RVE的生成.
- 扩大DRAGen与各种计算材料工程 (ICME) 解决方案的兼容性.
主要方法:
- 嵌入了从真实材料中提取的复杂微观结构特征的RVE发电机.
- 从训练有素的神经网络和 .csv 文件中启用了输入数据处理.
- 增加了模块,用于为有限元 (FE) 和光谱溶解器生成输入文件.
主要成果:
- 现在,DRAGen可以重建各种特征,包括毛孔,包裹,马石带,层次结构和晶体纹理.
- 该框架为DAMASK,Abaqus和MOOSE多物理框架生成输入文件.
- 评估和模拟证实了DRAGen在ICME研究中的力量和灵活性.
结论:
- 增强的DRAGen是一个多功能工具,用于生成具有复杂微观结构的现实RVE.
- 它的模块化设计允许轻松扩展和适应.
- DRAGen为研究人员提供了广泛的微结构,用于研究和设计开发.
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