Prediction of Fatigue Property of SLM Metal Parts Based on Multi-scale Simulations

doi:10.3969/j.issn.1004-132X.2025.09.021

Abstract

Abstract:

A multi-scale ternary numerical model of “process-microstructure-properties” was proposed to investigate the relationships of the processing parameters of metal SLM， the microstructure of the formed parts and the fatigue properties. In detail， to analyze the evolution processes of temperature field， velocity field， and pore defects under different processing parameters， the meso dynamics process of the molten pool was studied with consideration of multiple physical field coupling phenomena such as recoil force. Using the temperature field data， the microstructure distribution of the representative volume element（RVE） was obtained based on cellular automaton model， and the effects of processing parameters on grain sizes and defect characteristics were investigated. Finally， the hazard levels of defects were evaluated under different processing parameters by stress intensity factors， and the macro fatigue strength of corresponding RVE was predicted. The results show that the proposed multi-scale model may effectively predict the fatigue properties of SLM metal parts under different processing parameters. This work provides a reference for optimizing SLM processing parameters.

Key words: selective laser melting（SLM）, pore defect, molten pool dynamics, cellular automata, fatigue property

摘要：

为研究金属选区激光熔化（SLM）工艺参数、成形件微结构及疲劳性能之间的关系，建立了“工艺-微结构-性能”三元多尺度数值模型。为了分析不同工艺参数下温度场、速度场和气孔缺陷的演化过程，研究了考虑反冲力等多物理场耦合现象的介观熔池动力学过程。利用熔池温度场数据，基于元胞自动机模型得到代表性体积元（RVE）的微观结构分布，并由此阐述了工艺参数对晶粒尺寸和缺陷特征的影响。利用应力强度因子评价了不同工艺参数下缺陷的危险程度，并预测了相应RVE的宏观疲劳强度。研究结果表明，所建立的多尺度模型有效预测了不同工艺参数下SLM金属构件的疲劳性能，可为SLM工艺参数优化提供参考。

关键词: 选区激光熔化, 气孔缺陷, 熔池动力学, 元胞自动机, 疲劳性能

CLC Number:

TH162

Jinyu ZHOU, Yifei CHEN. Prediction of Fatigue Property of SLM Metal Parts Based on Multi-scale Simulations[J]. China Mechanical Engineering, 2025, 36(9): 2087-2096.

周金宇, 陈逸飞. 基于多尺度模拟的选区激光熔化金属件疲劳性能预测[J]. 中国机械工程, 2025, 36(9): 2087-2096.

Figures/Tables 19

Fig.1 Computational domain of meso melten pool simulation

Fig.2 Cellular automata grids（two-dimension）

Fig.3 Temperature fields under different laser powers （v=80 mm/s）

Fig.4 Change of molten pool size with laser power

Fig.5 Cooling rate monitoring point

Fig.6 Temperature curves of the monitoring point under different laser powers

Fig.7 Cooling rates of the monitoring point under different laser powers

Fig.8 Velocity fields of molten pool under different laser powers

Fig.9 Effects of laser power on porosity and maximum pore projection area

Fig.10 The result comparison between numerical simulations and experiments

Fig.11 Comparison of the grain size

Fig.12 Selection of the RVE

Fig.13 Microstructure evolution process

Fig.14 Change of grain size with laser power

Fig.15 RVE stress field under transverse tensile

Fig.16 Stress distribution at the pore defects under transverse tensile

Tab.1 Maximum Mises stresses near pore defects under tensile loading

气孔序号	气孔投影面积/μm²		最大Mises 应力/MPa
气孔序号	横向加载	纵向加载	最大Mises 应力/MPa
1	295		684
1		295	678
2	310		627
2		275	565
3	415		627
3		405	621

Tab.2 Stress intensity factors of pore defects

气孔序号	气孔投影面积/μm²	缺陷至表面距离/μm	应力强度因子/（MPa·m^1/2）
1	295（横向加载）	30	103.2
1	295（纵向加载）	30	102.4
2	310（横向加载）	37	95.9
2	275（纵向加载）	34	83.8
3	415（横向加载）	40	103.1
3	405（纵向加载）	40	101.5

Fig.17 Relationship between process parameters and fatigue strength

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