Solidification and crystallographic texture modeling of laser powder bed fusion Ti-6Al-4V using finite difference-monte carlo method

被引:2
作者
Whitney, Bonnie C. [1 ,2 ]
Rodgers, Theron M. [2 ]
Spangenberger, Anthony G. [1 ]
Rezwan, Aashique A. [2 ]
Zapiain, David Montes de Oca [2 ]
Lados, Diana A. [1 ]
机构
[1] Integrat Mat Design Ctr, Worcester Polytech Inst, Worcester, MA 01609 USA
[2] Sandia Natl Labs, Albuquerque, NM 87123 USA
来源
MATERIALIA | 2024年 / 38卷
关键词
Additive manufacturing; Finite difference; Monte Carlo; Microstructure prediction; STRUCTURE-PROPERTY LINKAGES; MICROSTRUCTURE EVOLUTION; PHASE-FIELD; SIMULATION; RECONSTRUCTION; ALLOY;
D O I
10.1016/j.mtla.2024.102279
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Laser powder bed fusion (LPBF) additive manufacturing makes near-net-shaped parts with reduced material cost and time, rising as a promising technology to fabricate Ti-6Al-4 V, a widely used titanium alloy in aerospace and medical industries. However, LPBF Ti-6Al-4 V parts produced with 67 degrees rotation between layers, a scan strategy commonly used to reduce microstructure and property inhomogeneity, have varying grain morphologies and weak crystallographic textures that change depending on processing parameters. This study predicts LPBF Ti-6Al4 V solidification at three energy levels using a finite difference-Monte Carlo method and validates the simulations with large-area electron backscatter diffraction (EBSD) scans. The developed model accurately shows that a < 001 > texture forms at low energy and a < 111 > texture occurs at higher energies parallel to the build direction but with a lower strength than the textures observed from EBSD. A validated and well-established method of combining spatial correlation and general spherical harmonics representation of texture is developed to calculate a difference score between simulations and experiments. The quantitative comparison enables effective finetuning of nucleation density (N0) input, which shows a nonlinear relationship with increasing energy level. Future improvements in texture prediction code and a more comprehensive study of N0 with different energy levels will further advance the optimization of LPBF Ti-6Al-4 V components. These developments contribute a novel understanding of crystallographic texture formation in LPBF Ti-6Al-4 V, the development of robust model validation and calibration pipeline methodologies, and provide a platform for mechanical property prediction and process parameter optimization.
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页数:19
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