Physical Model Based on Data-Driven Analysis of Chemical Composition Effects of Friction Stir Welding
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JMEPEG https://doi.org/10.1007/s11665-020-05132-x
Physical Model Based on Data-Driven Analysis of Chemical Composition Effects of Friction Stir Welding J.Y. Li, X.X. Yao, and Z. Zhang (Submitted May 28, 2020; in revised form July 24, 2020) Variations in chemical compositions can lead to changes in the mechanical properties during friction stir welding (FSW). To facilitate control over the final mechanical properties of the friction stir weld, the relationship between the chemical compositions and final mechanical properties must be investigated. An artificial neural network was used for a data-driven analysis of the effects that chemical compositions have on the mechanical properties of FSW. A precipitate evolution model was implemented to examine the detailed contributions of different elements to the final mechanical properties. Experiments with different chemical compositions were conducted to validate the established models. Through both numerical and experimental analyses, it was determined that the yield strength in the stir zone increased with an increase in Mg/Si owing to the formation of Mg2Si. The mechanical properties also increased with Si, Mg, and Cu contents in the solid solution. The mechanical properties decreased with an increase in the Fe and Mn contents owing to the formation of an intermetallic compound a-Alx(MnFe)ySiz. The final mechanical properties were determined by both the welding temperature and chemical compositions. By utilizing a physical model based on a data-driven analysis, the mechanical properties could be optimally controlled. Keywords
aluminum alloy, chemical composition, friction stir welding, mechanical property
1. Introduction The final quality of a friction stir weld is controlled by many factors, including the rotational speed, transverse speed, penetration depth, tool geometry, and tilt angle (Ref 1-7). A higher rotational speed or lower transverse speed in friction stir welding (FSW) can lead to an increase in the welding temperature (Ref 8-10). An increase in the welding temperature can lead to a higher solution of precipitates for aluminum alloys during the heating process (Ref 11). During the cooling process, the precipitates can nucleate and grow. A higher volume fraction of precipitates with small average particle sizes (in nanoscale) can lead to an increase in the hardness, as well as the yield strength, of the final friction stir welds (Ref 12, 13). Although the design of welding parameters can optimize the weld quality in FSW, experimental tests reveal that the mechanical properties of friction stir welds can vary even under the same (or similar) welding parameters. Abdulstaar et al. (Ref 14) found that when the rotational and transverse speeds are 1200 rpm and 0.8 mm/s, respectively, the hardness is approximately 60 HV in the stir zone during the FSW of AA6061. When the rotational and transverse speeds are 1200 rpm and 0.7 mm/s, respectively, Fadaeifard et al. (Ref 15) found that the average hardness in the nugget zone is 59.85
J.Y. Li, X.X. Yao, and Z. Zhang, State
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