EI、Scopus 收录
中文核心期刊

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

增材制造微结构演化及疲劳分散性计算

易敏 常珂 梁晨光 周留成 杨阳祎玮 易新 胥柏香

易敏, 常珂, 梁晨光, 周留成, 杨阳祎玮, 易新, 胥柏香. 增材制造微结构演化及疲劳分散性计算. 力学学报, 2021, 53(12): 3263-3273 doi: 10.6052/0459-1879-21-389
引用本文: 易敏, 常珂, 梁晨光, 周留成, 杨阳祎玮, 易新, 胥柏香. 增材制造微结构演化及疲劳分散性计算. 力学学报, 2021, 53(12): 3263-3273 doi: 10.6052/0459-1879-21-389
Yi Min, Chang Ke, Liang Chenguang, Zhou Liucheng, Yang Yangyiwei, Yi Xin, Xu Baixiang. Computational study of evolution and fatigue dispersity of microstructures by additive manufacturing. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(12): 3263-3273 doi: 10.6052/0459-1879-21-389
Citation: Yi Min, Chang Ke, Liang Chenguang, Zhou Liucheng, Yang Yangyiwei, Yi Xin, Xu Baixiang. Computational study of evolution and fatigue dispersity of microstructures by additive manufacturing. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(12): 3263-3273 doi: 10.6052/0459-1879-21-389

增材制造微结构演化及疲劳分散性计算

doi: 10.6052/0459-1879-21-389
基金项目: 国家海外高层次人才引进计划青年项目, 航空发动机及燃气轮机重大专项(J2019-IV-0014-0082)和中央高校基本科研业务费和德国科学基金DFG (CRC-TRR 270, DFG YI 165/1-1) 资助项目
详细信息
    作者简介:

    易敏, 教授, 主要研究方向: 先进材料结构和先进制造的多尺度多场耦合力学. E-mail: yimin@nuaa.edu.cn

  • 中图分类号: TB301

COMPUTATIONAL STUDY OF EVOLUTION AND FATIGUE DISPERSITY OF MICROSTRUCTURES BY ADDITIVE MANUFACTURING

  • 摘要: 为了预测增材制造中工艺参数−微结构−力学性能之间的关联规律, 提出了集成离散元、相场模拟、晶体塑性有限元和极值概率理论的计算方法, 揭示了激光扫描速度对微结构演化、屈服应力和疲劳分散性的影响. 首先, 采用离散元实现了重力作用下粉床在已凝固层表面上的逐层铺设; 其次, 通过热−熔体−微结构耦合的非等温相场模拟, 获得了熔体、气孔、晶界、晶粒取向等的时空演化以及最终形成的多晶微结构; 然后, 应用晶体塑性有限元计算了增材制造多晶微结构的宏观力学响应, 并得到表征疲劳裂纹萌生驱动力的疲劳指示参数(FIP); 最后, 采用极值概率理论分析了增材制造多晶微结构的FIP极值分布规律及疲劳分散性. 以316L不锈钢选区激光熔化增材制造为例的计算结果表明: 增材制造微结构的宏观屈服强度随激光扫描速度的增加而降低, 且呈各向异性; FIP极值符合Gumbel极值分布规律, 激光扫描速度增加可降低增材制造微结构疲劳分散性, 但会导致FIP极值升高, 使得疲劳裂纹萌生驱动力增加, 疲劳寿命降低.

     

  • 图  1  用于增材制造微结构演化及疲劳分散性预测的集成离散元、相场模拟、晶体塑性有限元和极值概率理论的计算框架示意图(DEM: 离散元; PF: 相场; CPFEM: 晶体塑性有限元; FIP: 疲劳指示参数; EVD: 极值分布)

    Figure  1.  Computational framework integrating discrete element method, phase-field simulation, crystal plasticity finite element method, and extreme value statistics for the prediction of evolution and fatigue dispersity of microstructures by additive manufacturing (DEM: discrete element method; PF: phase field; CPFEM: crystal plasticity finite element method; FIP: fatigue indicator parameter; EVD: extreme value distribution)

    图  2  逐层选区激光熔化增材制造过程的微结构演化(v = 2 m/s)

    Figure  2.  Microstructure evolution during layer-by-layer selective laser melting (v = 2 m/s)

    图  3  选区激光熔化增材制造微结构及其孔隙率: (a) v = 2 m/s; (b) v = 1.5 m/s; (c) v = 1 m/s; (d) v = 0.5 m/s; (e) 图(a) ~ 图(d)中矩形区域(400 μm × 190 μm)的孔隙率, 其中圆形(90 W, 1 m/s)[44]和三角形(160 W, 1.2 m/s)[45]标记为实验结果

    Figure  3.  Microstructure and porosity obtained by selective laser melting: (a) v = 2 m/s; (b) v = 1.5 m/s; (c) v = 1 m/s; (d) v = 0.5 m/s; (e) porosity of the rectangular region (400 μm × 190 μm) in (a)-(d), with the circle (90 W, 1 m/s)[44] and triangle (160 W, 1.2 m/s)[45] markers indicating the experimental results

    图  4  选区激光熔化增材制造微结构力学性能

    Figure  4.  Mechanical property of microstructure from selective laser melting

    图  5  不同应变幅(εmax)下选区激光熔化增材制造微结构的循环应力-应变曲线

    Figure  5.  Macroscopic stress-strain cyclic response of microstructure from selective laser melting

    图  6  x方向不同应变幅(εmax)下单元FIP分布

    Figure  6.  Variation of elemental FIPs throughout the sample under different strain magnitude (εmax) along x axis

    图  7  体积平均FIP极值概率分布及其Gumbel函数拟合

    Figure  7.  Extreme value distributions of the volume averaged FIPs and their fit to the Gumbel distribution

    图  8  相对分散性参数($\;{\beta _0}/{u_0}$)变化曲线

    Figure  8.  Relative dispersion parameter ($\;{\beta _0}/{u_0}$) curves

  • [1] 卢秉恒. 增材制造技术-现状与未来. 中国机械工程, 2020, 31(1): 19-23 (Lu Bingheng. Additive manufacturing-current situation and future. China Mechanical Engineering, 2020, 31(1): 19-23 (in Chinese)
    [2] 王华明. 高性能大型金属构件激光增材制造: 若干材料基础问题. 航空学报, 2014, 35(10): 2690-2698 (Wang Huaming. Materials' fundamental issues of laser additive manufacturing for high-performance large metallic components. Acta Aeronautica ET Astronautica Sinica, 2014, 35(10): 2690-2698 (in Chinese)
    [3] 顾冬冬, 张红梅, 陈洪宇等. 航空航天高性能金属材料构件激光增材制造. 中国激光, 2020, 47(5): 0500002 (Gu Dongdong, Zhang Hongmei, Chen Hongyu, et al. Laser Additive manufacturing of high-performance metallic aerospace components. Chinese Journal of Lasers, 2020, 47(5): 0500002 (in Chinese) doi: 10.3788/CJL202047.0500002
    [4] 陈嘉伟, 熊飞宇, 黄辰阳等. 金属增材制造数值模拟. 中国科学: 物理学 力学 天文学, 2020, 50(9): 090007 (Chen Jiawei, Xiong Feiyu, Huang Chenyang, et al. Numerical simulation on metallic additive manufacturing. Scientia Sinica Physica,Mechanica &Astronomica, 2020, 50(9): 090007 (in Chinese)
    [5] 王超, 徐斌, 段尊义等. 面向增材制造的应力最小化连通性拓扑优化. 力学学报, 2021, 53(4): 1070-1080 (Wang Chao, Xu Bin, Duan Zunyi, et al. Additive manufacturing-oriented stress minimization topology optimization with connectivity. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(4): 1070-1080 (in Chinese) doi: 10.6052/0459-1879-20-389
    [6] 秋大闯, 李多生, 叶寅等. SLM成形镍基高温合金及其数值模拟的研究进展. 功能材料, 2019, 50(03): 03049-03058 (Qiu Dachuang, Li Duosheng, Ye Yin, et al. Research progress of SLM forming nickel-based superalloys and the simulation. Journal of Functional Materials, 2019, 50(03): 03049-03058 (in Chinese)
    [7] 张江涛, 谭援强, 纪财源等. 增材制造中滚筒铺粉工艺参数对尼龙粉体铺展性的影响研究. 力学学报, 2021, 53(9): 2418-2428 (Zhang Jiangtao, Tan Yuanqiang, Ji Caiyuan, et al. Research on the effects of roller-spreading parameters for nylon powder spreadability in additive manufacturing. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(9): 2418-2428 (in Chinese)
    [8] Sahoo S, Chou K. Phase-field simulation of microstructure evolution of Ti-6Al-4V in electron beam additive manufacturing process. Additive Manufacturing, 2016, 9: 14-24 doi: 10.1016/j.addma.2015.12.005
    [9] Liu PW, Ji YZ, Wang Z, et al. Investigation on evolution mechanisms of site-specific grain structures during metal additive manufacturing. Journal of Materials Processing Technology, 2018, 257: 191-202 doi: 10.1016/j.jmatprotec.2018.02.042
    [10] Yang M, Wang L, Yan WT. Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening. NPJ Computatioanl Materials, 2021, 7: 56 doi: 10.1038/s41524-021-00524-6
    [11] Lu LX, Sridhar N, Zhang YW. Phase field simulation of powder bed-based additive manufacturing. Acta Materialia, 2018, 144: 801-809 doi: 10.1016/j.actamat.2017.11.033
    [12] Yang Y, Ragnvaldsen O, Bai Y, et al. 3D non-isothermal phase-field simulation of microstructure evolution during selective laser sintering. NPJ Computatioanl Materials, 2019, 5: 81 doi: 10.1038/s41524-019-0219-7
    [13] Yang Y, Kühn P, Yi M, et al. Non-isothermal phase-field modeling of heat-melt-microstructure-coupled processes during powder bed fusion. JOM, 2020, 72(4): 1719-1733 doi: 10.1007/s11837-019-03982-y
    [14] Yang Y, Oyedeji TD, Kühn P, et al. Investigation on temperature-gradient-driven effects in unconventional sintering via non-isothermal phase-field simulation. Script Materialia, 2020, 186: 152-157 doi: 10.1016/j.scriptamat.2020.05.016
    [15] Yang Y, Doñate-Buendía C, Oyedeji TD, et al. Nanoparticle tracing during laser powder bed fusion of oxide dispersion strengthened steels. Materials, 2021, 14(13): 3463 doi: 10.3390/ma14133463
    [16] 杨阳祎玮, 易敏, 胥柏香. 粉末增材制造微结构的非等温相场模拟. 中南大学学报, 2020, 51(11): 3019-3031 (Yang Yangyiwei, Yi Min, Xu Baixiang. Non-isothermal phase-field simulation of microstructure in powder-based additive manufacturing. Journal of Central South University, 2020, 51(11): 3019-3031 (in Chinese)
    [17] Lian YP, Lin S, Yan WT, et al. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing. Computational Mechanics, 2018, 61(5): 543-558 doi: 10.1007/s00466-017-1535-8
    [18] Lian YP, Gan Z, Yu C, et al. A cellular automaton finite volume method for microstructure evolution during additive manufacturing. Materials Design, 2019, 169: 107672 doi: 10.1016/j.matdes.2019.107672
    [19] 魏雷, 林鑫, 王猛等. 激光立体成形中熔池凝固微观组织的元胞自动机模拟. 物理学报, 2015, 64(1): 018103 (Wei Lei, Lin Xin, Wang Meng, et al. Cellular automaton simulation of the molten p o ol of laser solid forming process. Acta Physica Sinica, 2015, 64(1): 018103 (in Chinese) doi: 10.7498/aps.64.018103
    [20] Yan WT, Lian YP, Yu C, et al. An integrated process–structure–property modeling framework for additive manufacturing. Computer Methods in Applied Mechanics and Engineering, 2018, 339: 184-204 doi: 10.1016/j.cma.2018.05.004
    [21] Rai A, Markl M, Körner C. A coupled cellular automaton-lattice Boltzmann model for grain structure simulation during additive manufacturing. Computational Materials Science, 2016, 124: 37-48 doi: 10.1016/j.commatsci.2016.07.005
    [22] Rai A, Helmer H, Körner C. Simulation of grain structure evolution during powder bed based additive manufacturing. Additive Manufacturing, 2017, 13: 124-134 doi: 10.1016/j.addma.2016.10.007
    [23] Wang Z, Yan W, Liu WK, et al. Powder-scale multi-physics modeling of multi-layer multi-track selective laser melting with sharp interface capturing method. Computational Mechanics, 2019, 63(4): 649-661 doi: 10.1007/s00466-018-1614-5
    [24] King W, Anderson AT, Ferencz RM, et al. Overview of modelling and simulation of metal powder bed fusion process at lawrence livermore national laboratory. Materials Science and Technology, 2015, 31(8): 957-968 doi: 10.1179/1743284714Y.0000000728
    [25] Ahmadi A, Mirzaeifar A, Moghaddam NS, et al. Effect of manufacturing parameters on mechanical properties of 316L stainless steel parts fabricated by selective laser melting: a computational framework. Materials Design, 2016, 112: 328-338 doi: 10.1016/j.matdes.2016.09.043
    [26] 张昭, 葛芃, 谭治军等. 激光增材制造微观结构模拟与力学性能预测. 兵器材料科学与工程, 2018, 41(1): 1-7 (Zhang Zhao, Ge Peng, Tan Zhijun, et al. Numerical simulation of microstructural evolutions and prediction of mechanical properties in laser additive manufacturing. Ordnance Material Science and Engineering, 2018, 41(1): 1-7 (in Chinese)
    [27] Liu PW, Wang Z, Xiao YH, et al. Integration of phase-field model and crystal plasticity for the prediction of process-structure-property relation of additively manufactured metallic materials. International Journal of Plasticity, 2020, 128: 102670 doi: 10.1016/j.ijplas.2020.102670
    [28] DebRoy T, Wei HL, Zuback JS, et al. Additive manufacturing of metallic components–process, structure and properties. Progress in Materials Science, 2018, 92: 112-224 doi: 10.1016/j.pmatsci.2017.10.001
    [29] Smith J, Xiong W, Yan W, et al. Linking process, structure, property, and performance for metal-based additive manufacturing: computational approaches with experimental support. Computational Mechanics, 2016, 57: 583-610 doi: 10.1007/s00466-015-1240-4
    [30] Kozicki J, Donze FV. YADE-OPEN DEM: an opensource software using a discrete element method to simulate granular material. Engineering Computations, 2009, 26(7): 786-805 doi: 10.1108/02644400910985170
    [31] Tonks MR, Gaston D, Millett PC, et al. An object-oriented finite element framework for multiphysics phase field simulations. Computational Materials Science, 2012, 51(1): 20-29 doi: 10.1016/j.commatsci.2011.07.028
    [32] Huang Y. A user-material subroutine incorporating single crystal plasticity in the ABAQUS finite element program. Mech. Report 178. Division of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, 1991
    [33] Fatemi A, Socie DF. A critical plane approach to multiaxial fatigue damage including out-of-phase loading. Fatigue & Fracture of Engineering Materials & Structures, 1988, 11(3): 149-165
    [34] Mcdowell L, Berard JY. A ΔJ-based approach to biaxial fatigue. Fatigue & Fracture of Engineering Materials & Structures, 1992, 15(8): 719-741
    [35] Castelluccio GM, McDowell DL. Assessment of small fatigue crack growth driving forces in single crystals with and without slip bands. International Journal of Fracture, 2012, 176(1): 49-64 doi: 10.1007/s10704-012-9726-y
    [36] Castelluccio GM, McDowell DL. Effect of annealing twins on crack initiation under high cycle fatigue conditions. Journal of Materials Science, 2013, 48(6): 2376-2387 doi: 10.1007/s10853-012-7021-y
    [37] Gu T, Stopka KS, Xu C, et al. Prediction of maximum fatigue indicator parameters for duplex Ti-6Al-4V using extreme value theory. Acta Materialia, 2020, 188: 504-516 doi: 10.1016/j.actamat.2020.02.009
    [38] Stopka KS, Gu T, McDowell DL. Effects of algorithmic simulation parameters on the prediction of extreme value fatigue indicator parameters in duplex Ti-6Al-4V. International Journal of Fatigue, 2020, 141: 105865 doi: 10.1016/j.ijfatigue.2020.105865
    [39] Musinski WD, McDowell DL. Simulating the effect of grain boundaries on microstructurally small fatigue crack growth from a focused ion beam notch through a three-dimensional array of grains. Acta Materialia, 2016, 112: 20-39 doi: 10.1016/j.actamat.2016.04.006
    [40] Stopka KS, McDowell DL. Microstructure-sensitive computational multiaxial fatigue of Al 7075-T6 and duplex Ti-6Al-4V. International Journal of Fatigue, 2020, 133: 105460 doi: 10.1016/j.ijfatigue.2019.105460
    [41] Stopka KS, McDowell DL. Microstructure-sensitive computational estimates of driving forces for surface versus subsurface fatigue crack formation in duplex Ti-6Al-4V and Al 7075-T6. JOM, 2020, 72(1): 28-38 doi: 10.1007/s11837-019-03804-1
    [42] Miller KJ. The behaviour of short fatigue cracks and their initiation part I-a review of two recent books. Fatigue & Fracture of Engineering Materials & Structures, 1987, 10(1): 75-91
    [43] Jan B, Goegebeur Y, Teugels J, et al. Statistics of Extremes: Theory and Applications. John Wiley & Sons, Ltd. 2004
    [44] Kumar P, Jayaraj R, Suryawanshi T, et al. Fatigue strength of additively manufactured 316L austenitic stainless steel. Acta Materialia, 2020, 199: 225-239 doi: 10.1016/j.actamat.2020.08.033
    [45] Obeidi MA, UíMhurchadha SM, Raghavendra R, et al. Comparison of the porosity and mechanical performance of 316L stainless steel manufactured on different laser powder bed fusion metal additive manufacturing machines. Journal of Materials Research and Technology, 2021, 13: 2361-2374 doi: 10.1016/j.jmrt.2021.06.027
    [46] Shrestha R, Simsiriwong J, Shamsaei N. Fatigue behavior of additive manufactured 316L stainless steel parts: Effects of layer orientation and surface roughness. Additive Manufacturing, 2019, 28: 23-38 doi: 10.1016/j.addma.2019.04.011
    [47] 韩世伟, 石多奇, 杨晓光等. 微结构相关的高循环疲劳分散性计算方法研究. 金属学报, 2016, 52(3): 289-297 (Han Shiwei, Shi Duoqi, Yang Xiaoguang, et al. Computational study on microstructure-sensitive high cycle fatigue dispersivity. Acta Metallurgica Sinica, 2016, 52(3): 289-297 (in Chinese) doi: 10.11900/0412.1961.2015.00322
  • 加载中
图(8)
计量
  • 文章访问数:  1464
  • HTML全文浏览量:  454
  • PDF下载量:  190
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-08-12
  • 录用日期:  2021-09-12
  • 网络出版日期:  2021-09-13
  • 刊出日期:  2021-12-18

目录

    /

    返回文章
    返回