计算辅助高性能增材制造铝合金开发的研究现状与展望

doi:10.11900/0412.1961.2022.00430

金属学报

2023, Vol. 59

Issue (1): 87-105 DOI: 10.11900/0412.1961.2022.00430

综述

本期目录 | 过刊浏览

计算辅助高性能增材制造铝合金开发的研究现状与展望

高建宝¹, 李志诚¹, 刘佳¹, 张金良², 宋波²(

), 张利军¹(

)

1.中南大学粉末冶金国家重点实验室长沙 410083
2.华中科技大学材料成形与模具技术国家重点实验室武汉 430074

Current Situation and Prospect of Computationally Assisted Design in High-Performance Additive Manufactured Aluminum Alloys: A Review

GAO Jianbao¹, LI Zhicheng¹, LIU Jia¹, ZHANG Jinliang², SONG Bo²(

), ZHANG Lijun¹(

)

1.State Key Lab of Powder Metallurgy, Central South University, Changsha 410083, China
2.State Key Laboratory of Materials Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, China

引用本文:

高建宝, 李志诚, 刘佳, 张金良, 宋波, 张利军. 计算辅助高性能增材制造铝合金开发的研究现状与展望[J]. 金属学报, 2023, 59(1): 87-105.
Jianbao GAO, Zhicheng LI, Jia LIU, Jinliang ZHANG, Bo SONG, Lijun ZHANG. Current Situation and Prospect of Computationally Assisted Design in High-Performance Additive Manufactured Aluminum Alloys: A Review[J]. Acta Metall Sin, 2023, 59(1): 87-105.

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摘要:

增材制造技术为高强铝合金复杂零部件的制造带来了前所未有的机遇，但目前增材制造铝合金体系仍局限于可铸造和可焊接的Al-Si系合金，制约了高性能增材制造铝合金的快速发展。近年来，不同尺度的计算方法逐步用于辅助高性能增材制造铝合金的开发。本文详细综述了国内外学者在计算辅助增材制造铝合金设计与制备领域的研究成果，列举了原子、介观和宏观尺度计算模拟及机器学习等计算方法辅助增材制造铝合金设计的代表性案例，分析了不同计算方法辅助合金设计的策略，并指出其不足。最后，针对如何推动多尺度计算在高性能增材制造铝合金开发中的应用进行了展望，并指出其发展方向。

关键词 ：增材制造铝合金, 计算热力学, 相场模拟, 机器学习, 集成计算材料工程, 多目标优化

Abstract：

Additive manufacturing technology has greatly increased opportunities in the production of high-strength aluminum alloy complex parts. However, current additive manufactured aluminum alloy systems are still limited to castable and weldable Al-Si alloys. This impedes the development of high-performance additive manufactured aluminum alloys. Recently, various computational techniques at different scales have been gradually used to promote the development of high-performance additive manufactured aluminum alloys. This paper summarizes the research achievements in the field of computationally-assisted design of additive manufactured aluminum alloys and their preparation from domestic and foreign scholars and presents representative cases from atomic, mesoscopic, and macroscopic scales and machine learning. The different calculation methods used to assist alloy designs are analyzed and their shortcomings are presented. Finally, the prospect on how to improve the application of multi-scale computation techniques in the development of high-performance additive manufactured aluminum alloys is presented, and some specific development directions are also clarified.

Key words： additive manufactured aluminum alloy computational thermodynamics phase-field simulation machine learning integrated computational materials engineering multi-objective optimization

收稿日期: 2022-08-31

ZTFLH:

TG146.2

基金资助:国家重点研发计划项目(2019YFB2006500);国家自然科学基金项目(51922044);广西重点研发计划项目(AB21220028);湖南省自然科学基金杰出青年项目(2021JJ10062);中国博士后科学基金面上项目(2021M701293)

作者简介: 高建宝，男，1993年生，博士生

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图1 Al-X固溶体中固溶强化效果随溶质浓度的变化，及Al-X固溶体中各元素的最大平衡固溶度与其在400℃下Al中扩散系数的关系[37]

图2 通过分子动力学构建的微型选区激光熔化(μ-SLM)模型处理Al纳米粉末床的最终凝固结构[41]

图3 计算热力学驱动的增材制造铝合金设计策略流程[53]

图4 热裂中具有特征温度的凝固组织示意图[60]及AlSi10Mg、6061、7075铝合金的Scheil-Gulliver凝固模拟结果和脆性温度范围ΔTBTR的比较[54]

图5 Kou准则中裂纹敏感因子示意图[55,66]及其在变形铝合金中的预测结果[67]与实验结果[62,63]对比

图6 Si改性Al7075合金凝固路径、裂纹敏感性计算结果及SLM工艺制备合金的微观组织形貌[58]

图7 一种用于SLM的新型无裂纹Ti改性Al-Cu-Mg合金设计流程[21]

表1 平衡和快速凝固条件(约106 K/s)下二元铝合金中溶质的溶解度极限值[79] (atomic fraction / %)

图8 有限界面耗散模型用于研究快速凝固条件下Al-Cu体系的溶质截留现象及动力学相图[102]

图9 激光熔池凝固过程中晶粒结构随时间的演变[98]

图10 Al-Cu-Mg合金裂纹形成机理[32]

图11 基于物理信息的机器学习方法设计无裂纹3D打印件流程图[33]

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