Additive manufacturing features rapid production of complicated shapes and has been widely employed in biomedical,aeronautical and aerospace applications.However,additive manufactured parts generally exhibit deteriora...Additive manufacturing features rapid production of complicated shapes and has been widely employed in biomedical,aeronautical and aerospace applications.However,additive manufactured parts generally exhibit deteriorated fatigue resistance due to the presence of random defects and anisotropy,and the prediction of fatigue properties remains challenging.In this paper,recent advances in fatigue life prediction of additive manufactured metallic alloys via machine learning models are reviewed.Based on artificial neural network,support vector machine,random forest,etc.,a number of models on various systems were proposed to reveal the relationships between fatigue life/strength and defect/microstructure/parameters.Despite the success,the predictability of the models is limited by the amount and quality of data.Moreover,the supervision of physical models is pivotal,and machine learning models can be well enhanced with appropriate physical knowledge.Lastly,future challenges and directions for the fatigue property prediction of additive manufactured parts are discussed.展开更多
Nickel-based superalloy IN738LC produced by selective laser melting(SLM)exhibits inferior hightemperature creep properties than its cast counterparts due to relatively smaller grain size,particularly for the plane nor...Nickel-based superalloy IN738LC produced by selective laser melting(SLM)exhibits inferior hightemperature creep properties than its cast counterparts due to relatively smaller grain size,particularly for the plane normal to the building direction.This work studied effects of post heating strategy on the microstructure and especially the grain size to improve the high temperature creep resistance.The asbuilt microstructure exhibited a fine grain size and large quantities of MC carbides that could effectively hinder grain growth.It was found that unconventional two-step heat treatments could lead to substantial grain growth,and the effect is particularly prominent at a specific temperature.The ease of grain growth was explained after classifying the microstructural evolution(boundary carbide transformation)during each heating step and related to the reduced grain boundary pinning force from MC carbides.Creep tests validated the effect of the new heat treatment scheme on the SLM-processed IN738LC at 850℃.An extended creep fracture life(1.5 to 4 times improvement)and lower secondary creep rates were achieved with samples subjected to the newly optimized two-step heat treatment.The complete creep curves are also firstly presented for SLM-IN738LC,confirming the effectiveness of grain growth and highlighting the importance of dedicated heat treatment for SLM superalloys.展开更多
基金support of National Natural Science Foundation of China(No.U2241245)support of National Natural Science Foundation of China(No.91960202)+4 种基金National Key Laboratory Foundation of Science and Technology on Materials under Shock and Impact(No.6142902220301)Natural Science Foundation of Shenyang(No.23-503-6-05)support of Opening Project of National Key Laboratory of Shock Wave and Detonation Physics(No.2022JCJQLB05702)Aeronautical Science Foundation of China(No.2022Z053092001)support of Shanghai Engineering Research Center of High-Performance Medical Device Materials(No.20DZ2255500).
文摘Additive manufacturing features rapid production of complicated shapes and has been widely employed in biomedical,aeronautical and aerospace applications.However,additive manufactured parts generally exhibit deteriorated fatigue resistance due to the presence of random defects and anisotropy,and the prediction of fatigue properties remains challenging.In this paper,recent advances in fatigue life prediction of additive manufactured metallic alloys via machine learning models are reviewed.Based on artificial neural network,support vector machine,random forest,etc.,a number of models on various systems were proposed to reveal the relationships between fatigue life/strength and defect/microstructure/parameters.Despite the success,the predictability of the models is limited by the amount and quality of data.Moreover,the supervision of physical models is pivotal,and machine learning models can be well enhanced with appropriate physical knowledge.Lastly,future challenges and directions for the fatigue property prediction of additive manufactured parts are discussed.
基金financially supported by"Industrial Transformation Research Hub for Transforming Australia’s Manufacturing Industry through High Value Additive Manufacturing"of the Australian Research Council(grant No.IH130100008)the use of instruments and scientific and technical assistance at the Monash Centre for Electron Microscopy,a Node of Microscopy Australiathe financial support from the Monash Graduate Research Scholarship(MGS)and International Monash Postgraduate Research Scholarship(IMPRS)from the Monash University。
文摘Nickel-based superalloy IN738LC produced by selective laser melting(SLM)exhibits inferior hightemperature creep properties than its cast counterparts due to relatively smaller grain size,particularly for the plane normal to the building direction.This work studied effects of post heating strategy on the microstructure and especially the grain size to improve the high temperature creep resistance.The asbuilt microstructure exhibited a fine grain size and large quantities of MC carbides that could effectively hinder grain growth.It was found that unconventional two-step heat treatments could lead to substantial grain growth,and the effect is particularly prominent at a specific temperature.The ease of grain growth was explained after classifying the microstructural evolution(boundary carbide transformation)during each heating step and related to the reduced grain boundary pinning force from MC carbides.Creep tests validated the effect of the new heat treatment scheme on the SLM-processed IN738LC at 850℃.An extended creep fracture life(1.5 to 4 times improvement)and lower secondary creep rates were achieved with samples subjected to the newly optimized two-step heat treatment.The complete creep curves are also firstly presented for SLM-IN738LC,confirming the effectiveness of grain growth and highlighting the importance of dedicated heat treatment for SLM superalloys.
