Discrete dislocation dynamics(DDD)simulations reveal the evolution of dislocation structures and the interaction of dislocations.This study investigated the compression behavior of single-crystal copper micropillars u...Discrete dislocation dynamics(DDD)simulations reveal the evolution of dislocation structures and the interaction of dislocations.This study investigated the compression behavior of single-crystal copper micropillars using fewshot machine learning with data provided by DDD simulations.Two types of features are considered:external features comprising specimen size and loading orientation and internal features involving dislocation source length,Schmid factor,the orientation of the most easily activated dislocations and their distance from the free boundary.The yielding stress and stress-strain curves of single-crystal copper micropillar are predicted well by incorporating both external and internal features of the sample as separate or combined inputs.It is found that the machine learning accuracy predictions for single-crystal micropillar compression can be improved by incorporating easily activated dislocation features with external features.However,the effect of easily activated dislocation on yielding is less important compared to the effects of specimen size and Schmid factor which includes information of orientation but becomes more evident in small-sized micropillars.Overall,incorporating internal features,especially the information of most easily activated dislocations,improves predictive capabilities across diverse sample sizes and orientations.展开更多
A two-dimensional discrete dislocation dynamics （DDD） technology by Giessen and Needleman （1995）, which has been extended by integrating a dislocation-grain boundary interaction model, is used to computationally a...A two-dimensional discrete dislocation dynamics （DDD） technology by Giessen and Needleman （1995）, which has been extended by integrating a dislocation-grain boundary interaction model, is used to computationally analyze the micro-cyclic plastic response of polycrystals containing micron-sized grains, with special attentions to significant influence of dislocationpenetrable grain boundaries （GBs） on the micro-plastic cyclic responses of polycrystals and underlying dislocation mechanism. Toward this end, a typical polycrystalline rectangular specimen under simple tension-compression loading is considered. Results show that, with the increase of cycle accumulative strain, continual dislocation accumulation and enhanced dislocation-dislocation interactions induce the cyclic hardening behavior; however, when a dynamic balance among dislocation nucleation, penetration through GB and dislocation annihilation is approximately established, cyclic stress gradually tends to saturate. In addition, other factors, including the grain size, cyclic strain amplitude and its history, also have considerable influences on the cyclic hardening and saturation.展开更多
The hydrogen effect on the nucleation and motion of dislocations in single-crystal bcc Fe with(110)surface was investigated by both nanoindentation experiments and discrete dislocation dynamics(DDD)simulation.The resu...The hydrogen effect on the nucleation and motion of dislocations in single-crystal bcc Fe with(110)surface was investigated by both nanoindentation experiments and discrete dislocation dynamics(DDD)simulation.The results of nanoindentation experiments showed that the pop-in load decreased evidently for the electrochemical hydrogen charging specimen,indicating that the dislocation nucleation strength might be reduced by hydrogen.In addition,the decrease of hardness due to hydrogen charging was also captured,implying that the dislocation motion might be promoted by hydrogen.By incorporating the effect of hydrogen on dislocation core energy,a DDD model was specifically proposed to investigate the influence of hydrogen on dislocation nucleation and motion.The results of DDD simulation revealed that under the effect of hydrogen,the dislocation nucleation strength is decreased and the motion of dislocation is promoted.展开更多
We develop a new hierarchical dislocation-grain boundary （GB） interaction model to predict the mechanical behavior of poly- crystalline metals at micro and submicro scales by coupling 3D Discrete Dislocation Dynami...We develop a new hierarchical dislocation-grain boundary （GB） interaction model to predict the mechanical behavior of poly- crystalline metals at micro and submicro scales by coupling 3D Discrete Dislocation Dynamics （DDD） simulation with the Molecular Dynamics （MD） simulation. At the microscales, the DDD simulations are responsible for capturing the evolution of dislocation structures; at the nanoscales, the MD simulations are responsible for obtaining the GB energy and ISF energy which are then transferred hierarchically to the DDD level. In the present model, four kinds of dislocafion-GB interactions, i.e. transmission, absorption, re-emission and reflection, are all considered. By this methodology, the compression of a Cu mi- cro-sized bi-crystal pillar is studied. We investigate the characteristic mechanical behavior of the bi-crystal compared with that of the single-crystal. Moreover, the comparison between the present penetrable model of GB and the conventional impenetrable model also shows the accuracy and efficiency of the present model.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12192214 and 12222209).
文摘Discrete dislocation dynamics(DDD)simulations reveal the evolution of dislocation structures and the interaction of dislocations.This study investigated the compression behavior of single-crystal copper micropillars using fewshot machine learning with data provided by DDD simulations.Two types of features are considered:external features comprising specimen size and loading orientation and internal features involving dislocation source length,Schmid factor,the orientation of the most easily activated dislocations and their distance from the free boundary.The yielding stress and stress-strain curves of single-crystal copper micropillar are predicted well by incorporating both external and internal features of the sample as separate or combined inputs.It is found that the machine learning accuracy predictions for single-crystal micropillar compression can be improved by incorporating easily activated dislocation features with external features.However,the effect of easily activated dislocation on yielding is less important compared to the effects of specimen size and Schmid factor which includes information of orientation but becomes more evident in small-sized micropillars.Overall,incorporating internal features,especially the information of most easily activated dislocations,improves predictive capabilities across diverse sample sizes and orientations.
基金supported by the National Natural Science Foundation of China(No.10672064).
文摘A two-dimensional discrete dislocation dynamics （DDD） technology by Giessen and Needleman （1995）, which has been extended by integrating a dislocation-grain boundary interaction model, is used to computationally analyze the micro-cyclic plastic response of polycrystals containing micron-sized grains, with special attentions to significant influence of dislocationpenetrable grain boundaries （GBs） on the micro-plastic cyclic responses of polycrystals and underlying dislocation mechanism. Toward this end, a typical polycrystalline rectangular specimen under simple tension-compression loading is considered. Results show that, with the increase of cycle accumulative strain, continual dislocation accumulation and enhanced dislocation-dislocation interactions induce the cyclic hardening behavior; however, when a dynamic balance among dislocation nucleation, penetration through GB and dislocation annihilation is approximately established, cyclic stress gradually tends to saturate. In addition, other factors, including the grain size, cyclic strain amplitude and its history, also have considerable influences on the cyclic hardening and saturation.
文摘The hydrogen effect on the nucleation and motion of dislocations in single-crystal bcc Fe with(110)surface was investigated by both nanoindentation experiments and discrete dislocation dynamics(DDD)simulation.The results of nanoindentation experiments showed that the pop-in load decreased evidently for the electrochemical hydrogen charging specimen,indicating that the dislocation nucleation strength might be reduced by hydrogen.In addition,the decrease of hardness due to hydrogen charging was also captured,implying that the dislocation motion might be promoted by hydrogen.By incorporating the effect of hydrogen on dislocation core energy,a DDD model was specifically proposed to investigate the influence of hydrogen on dislocation nucleation and motion.The results of DDD simulation revealed that under the effect of hydrogen,the dislocation nucleation strength is decreased and the motion of dislocation is promoted.
基金supported by the National Natural Science Foundation of China(Grant No. 10772096)the National Basic Research Program of China(Grand No. 2010CB631005)
文摘We develop a new hierarchical dislocation-grain boundary （GB） interaction model to predict the mechanical behavior of poly- crystalline metals at micro and submicro scales by coupling 3D Discrete Dislocation Dynamics （DDD） simulation with the Molecular Dynamics （MD） simulation. At the microscales, the DDD simulations are responsible for capturing the evolution of dislocation structures; at the nanoscales, the MD simulations are responsible for obtaining the GB energy and ISF energy which are then transferred hierarchically to the DDD level. In the present model, four kinds of dislocafion-GB interactions, i.e. transmission, absorption, re-emission and reflection, are all considered. By this methodology, the compression of a Cu mi- cro-sized bi-crystal pillar is studied. We investigate the characteristic mechanical behavior of the bi-crystal compared with that of the single-crystal. Moreover, the comparison between the present penetrable model of GB and the conventional impenetrable model also shows the accuracy and efficiency of the present model.
