COMPUTATIONAL STUDY OF EVOLUTION AND FATIGUE DISPERSITY OF MICROSTRUCTURES BY ADDITIVE MANUFACTURING
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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.Abstract: In order to predict the correlation among the processing parameters, microstructures, and mechanical properties for additive manufacturing, a computational framework integrating discrete element method, phase-field simulation, crystal plasticity finite element method, and extreme value statistics is proposed. The framework is applied to reveal the influence of laser scanning velocity on the microstructure evolution, yield stress, fatigue indicator parameter (FIP) distribution, and fatigue dispersity, in order to show its capability in simulating additive manufacturing process and the resultant mechanical properties. Firstly, discrete element method simulations are carried out to spread the powder bed layer by layer with the consideration of powder size distribution. The spreading is performed on the curved surface of the previously solidified layer. Secondly, the heat-melt-microstructure coupled non-isothermal phase-field simulations are performed to obtain the temporal and spatial evolution of melt, pore, grain boundary, grain distribution/orientation, etc., as well as the final polycrystal microstructure. Thirdly, crystal plasticity finite element method is utilized to attain the macroscopic mechanical response and stress/strain distribution of the additively manufactured polycrystal microstructure (AMPM) and FIP which is a surrogate measure for the driving force to form fatigue cracks. Fourthly, extreme value statistics are carried out to analyze the extreme value distribution of FIPs and the fatigue dispersity of the AMPM. Comprehensive simulations are put into practice for the selective laser melting based additive manufacturing of a typical metallic material 316L stainless steel. The simulation results indicate that the macroscopic yield stress of the AMPM is anisotropic and decreases with the increasing laser scanning velocity. The extreme value of FIPs from the AMPM with random distribution of grain orientations correlates well with the Gumbel extreme value distribution. The increase of laser scanning velocity could decrease the fatigue dispersity of the AMPM, but increase the FIP extremum and the associated driving force for fatigue crack initiation and thus notably decrease the fatigue life.
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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 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
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