Crystallographic slip activity fields identified automatically from DIC data, even for intersecting, diffuse and cross slip
Crystallographic slip activity fields identified automatically from DIC data, even for intersecting, diffuse and cross slip
复制标题
从 DIC 数据自动识别晶体滑移活动场,甚至是交叉滑移、扩散滑移和交叉滑移
DOI:
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
J. Hoefnagels
中科院分区:
文献类型:
--
作者:
T. Vermeij;R. Peerlings;M. Geers;J. Hoefnagels
Crystallographic slip system identification methods are widely employed to characterize the fine scale deformation of metals. While powerful and widely employed, they usually rely on the occurrence of discrete slip bands with clear slip traces and struggle when mechanisms such as cross-slip, curved slip, diffuse slip and/or intersecting slip occur. This paper proposes a novel slip system identification framework in which the measured displacement gradient fields (from Digital Image Correlation) are matched with the kinematics of one or multiple combined slip systems. To identify the amounts of slip that conform to the measured kinematics, an optimization problem is solved for every datapoint individually, resulting in a slip activity field for every considered slip system. The identification framework is demonstrated and validated on an HCP virtual experiment, for discrete and diffuse slip, incorporating 24 slip systems. Experimental case studies on FCC and BCC metals show how full-field identification of discrete slip, diffuse slip and cross-slip becomes feasible, even when considering 48 slip systems for BCC. Moreover, the methodology is extended into a dedicated cross-slip identification method, which directly yields the orientation of the local slip plane trace orientation, purely based on the measured kinematics and on one or two chosen slip directions. For even more challenging cases revealing a persistent uncertainty in the slip identification, a two-step identification approach can be employed, as is demonstrated on a highly challenging HCP virtual experiment.
影响因子:
9.4
作者:
Harte, A.;Atkinson, M.;da Fonseca, J. Quinta
通讯作者:
da Fonseca, J. Quinta
影响因子:
9.8
作者:
Bieler, T. R.;Eisenlohr, P.;Raabe, D.
通讯作者:
Raabe, D.