Zheng Xiaoyu, Kong Yi, Chang Tingting, Liao Xin, Ma Yiwu, Du Yong
State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, China.
College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
Materials (Basel). 2022 Aug 1;15(15):5296. doi: 10.3390/ma15155296.
It is of great academic and engineering application to study the evolution of microstructure and properties of age-strengthened aluminum alloys during heat treatment and to establish quantitative prediction models that can be applied to industrial production. The main factors affecting the peak aging state strength of age-strengthened aluminum alloys are the precipitates, solid solution elements, grain size effects, and textures formed during the material processing. In this work, these multi-scale factors are integrated into the framework of the knowledge graph to assist the following crystal plasticity finite elements simulations. The constructed knowledge graph is divided into two parts: static data and dynamic data. Static data contains the basic properties of the material and the most basic property parameters. Dynamic data is designed to improve awareness of static data. High-throughput computing is performed to further obtain clear microstructure-property relationships by varying the parameters of materials properties and the characteristics of the structure models. The constructed knowledge graph can be used to guide material design for 6XXX Al-Mg-Si based alloys. The past experimental values are used to calibrate the phenomenological parameters and test the reliability of the analysis process.
研究时效强化铝合金在热处理过程中的微观结构演变和性能，并建立可应用于工业生产的定量预测模型，具有重要的学术和工程应用价值。影响时效强化铝合金峰值时效状态强度的主要因素是析出相、固溶元素、晶粒尺寸效应以及材料加工过程中形成的织构。在这项工作中，这些多尺度因素被整合到知识图谱框架中，以辅助后续的晶体塑性有限元模拟。构建的知识图谱分为两部分：静态数据和动态数据。静态数据包含材料的基本性能和最基本的性能参数。动态数据旨在提高对静态数据的认知。通过改变材料性能参数和结构模型特征进行高通量计算，进一步获得清晰的微观结构-性能关系。构建的知识图谱可用于指导6XXX系Al-Mg-Si基合金的材料设计。利用过去的实验值校准唯象参数并测试分析过程的可靠性。
