Mimicking complex dislocation dynamics by interaction networks
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||European Physical Journal B|
|Early online date||13 Nov 2018|
|Publication status||Published - Nov 2018|
|Publication type||A1 Journal article-refereed|
Two-dimensional discrete dislocation models exhibit complex dynamics in relaxation and under external loading. This is manifested both in the time-dependent velocities of individual dislocations and in the ensemble response, the strain rate. Here we study how well this complexity may be reproduced using so-called Interaction Networks, an artificial intelligence method for learning the dynamics of complex interacting systems. We test how to learn such networks using creep data, and show results on reproducing individual and collective dislocation velocities. The quality of reproducing the interaction kernel is discussed.