The microstructure development during a cooling period of alloys being immiscible in the liquid state such as Al-Pb or AI-Bi has gained renewed scientific and technical interest during the last decades. Experiments ha...The microstructure development during a cooling period of alloys being immiscible in the liquid state such as Al-Pb or AI-Bi has gained renewed scientific and technical interest during the last decades. Experiments have been performed to investigate the phase transformation kinetics in the liquid miscibility gap and numerical models have been developed to simulate and analyze the solidification process. The recently developed computational modeling techniques can, to some extent, be applied to describe the decomposition, the spatial phase separation and the microstructure evolution during a cooling period of an immiscible alloy through the miscibility gap. This article overviews the researches in this field.展开更多
To design microstructure and microhardness in the additive manufacturing(AM)of nickel(Ni)-based superalloys,the present work develops a novel data-driven approach that combines physics-based models,experimental measur...To design microstructure and microhardness in the additive manufacturing(AM)of nickel(Ni)-based superalloys,the present work develops a novel data-driven approach that combines physics-based models,experimental measurements,and a data-mining method.The simulation is based on a computational thermal-fluid dynamics(CtFD)model,which can obtain thermal behavior,solidification parameters such as cooling rate,and the dilution of solidified clad.Based on the computed thermal information,dendrite arm spacing and microhardness are estimated using well-tested mechanistic models.Experimental microstructure and microhardness are determined and compared with the simulated values for validation.To visualize process-structure-properties(PSPs)linkages,the simulation and experimental datasets are input to a data-mining model-a self-organizing map(SOM).The design windows of the process parameters under multiple objectives can be obtained from the visualized maps.The proposed approaches can be utilized in AM and other data-intensive processes.Data-driven linkages between process,structure,and properties have the potential to benefit online process monitoring control in order to derive an ideal microstructure and mechanical properties.展开更多
Directional solidified turbine blades of Ni-based superalloy are widely used as key parts of the gas turbine engines.The mechanical properties of the blade are greatly influenced by the final microstructure and the gr...Directional solidified turbine blades of Ni-based superalloy are widely used as key parts of the gas turbine engines.The mechanical properties of the blade are greatly influenced by the final microstructure and the grain orientation determined directly by the grain selector geometry of the casting.In this paper,mathematical models were proposed for three dimensional simulation of the grain growth and microstructure evolution in directional solidification of turbine blade casting.Ray-tracing method was applied to calculate the temperature variation of the blade.Based on the thermo model of heat transfer,the competitive grain growth within the starter block and the spiral of the grain selector,the grain growth in the blade and the microstructure evolution were simulated via a modified Cellular Automaton method.Validation experiments were carried out,and the measured results were compared quantitatively with the predicted results.The simulated cooling curves and microstructures corresponded well with the experimental results.The proposed models could be used to predict the grain morphology and the competitive grain evolution during directional solidification.展开更多
文摘The microstructure development during a cooling period of alloys being immiscible in the liquid state such as Al-Pb or AI-Bi has gained renewed scientific and technical interest during the last decades. Experiments have been performed to investigate the phase transformation kinetics in the liquid miscibility gap and numerical models have been developed to simulate and analyze the solidification process. The recently developed computational modeling techniques can, to some extent, be applied to describe the decomposition, the spatial phase separation and the microstructure evolution during a cooling period of an immiscible alloy through the miscibility gap. This article overviews the researches in this field.
基金Jian Cao,Gregory J.Wagner,and Wing K.Liu acknowledge support from the National Science Foundation(NSF)Cyber-Physical Systems(CPS)(CPS/CMMI-1646592)Hengyang Li acknowledges support from the Northwestern Data Science Initiative(DSI+6 种基金171474500210043324)Jian Cao,Gregory J.Wagner,Wing K.Liu,Jennifer L.Bennett,and Sarah J.Wolff acknowledge support from the Digital Manufacturing and Design Innovation Institute(DMDII15-07)Jian Cao,Wing K.Liu,Zhengtao Gan,and Jennifer L.Bennett acknowledge support from the Center for Hierarchical Materials Design(CHiMaD70NANB14H012)This work made use of facilities at DMG MORI and Northwestern UniversityIt also made use of the MatCI Facility,which receives support from the MRSEC Program(NSF DMR-168 1720139)of the Materials Research Center at Northwestern University.
文摘To design microstructure and microhardness in the additive manufacturing(AM)of nickel(Ni)-based superalloys,the present work develops a novel data-driven approach that combines physics-based models,experimental measurements,and a data-mining method.The simulation is based on a computational thermal-fluid dynamics(CtFD)model,which can obtain thermal behavior,solidification parameters such as cooling rate,and the dilution of solidified clad.Based on the computed thermal information,dendrite arm spacing and microhardness are estimated using well-tested mechanistic models.Experimental microstructure and microhardness are determined and compared with the simulated values for validation.To visualize process-structure-properties(PSPs)linkages,the simulation and experimental datasets are input to a data-mining model-a self-organizing map(SOM).The design windows of the process parameters under multiple objectives can be obtained from the visualized maps.The proposed approaches can be utilized in AM and other data-intensive processes.Data-driven linkages between process,structure,and properties have the potential to benefit online process monitoring control in order to derive an ideal microstructure and mechanical properties.
基金financially supported by the National Basic Research Program of China (No.2005CB724105,2011CB706801)National Natural Science Foundation of China (No.10477010)+1 种基金National High Technology Research,Development Program of China (No.2007AA04Z141)Important National Science & Technology Specific Projects (No.2009ZX04006-041,2011ZX04014-052)
文摘Directional solidified turbine blades of Ni-based superalloy are widely used as key parts of the gas turbine engines.The mechanical properties of the blade are greatly influenced by the final microstructure and the grain orientation determined directly by the grain selector geometry of the casting.In this paper,mathematical models were proposed for three dimensional simulation of the grain growth and microstructure evolution in directional solidification of turbine blade casting.Ray-tracing method was applied to calculate the temperature variation of the blade.Based on the thermo model of heat transfer,the competitive grain growth within the starter block and the spiral of the grain selector,the grain growth in the blade and the microstructure evolution were simulated via a modified Cellular Automaton method.Validation experiments were carried out,and the measured results were compared quantitatively with the predicted results.The simulated cooling curves and microstructures corresponded well with the experimental results.The proposed models could be used to predict the grain morphology and the competitive grain evolution during directional solidification.
