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D2C - CONVERTING AND COMPRESSING DISCRETE DISLOCATION MICROSTRUCTURE DATA

机译:D2C - 转换和压缩离散位错组织数据

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Appropriate methods to describe materials microstructure are essential for connecting different simulation methods as well as experiments. Focusing on dislocations - the carrier of plastic deformation - we show how continuous field descriptions can be used to represent dislocation microstructure. These fields may be used as input for continuum simulations or for their validation, they allow the comparison of different discrete dislocation dynamics (DDD) implementations, and they are a means of "compressing" the data resulting from DDD simulations. We give an overview of the design choices for D2C, a Python software package designed to convert data from DDD simulations to continuous continuum dislocation dynamics (CDD) fields. The theory beneath each step of this conversion process is outlined.
机译:描述材料微观结构的适当方法对于连接不同的仿真方法以及实验至关重要。专注于脱位 - 塑性变形的载体 - 我们展示了如何使用持续现场描述如何代表错位微观结构。这些字段可以用作连续模拟或验证的输入,允许比较不同的离散位错动态(DDD)实现,并且它们是“压缩”由DDD仿真产生的数据的手段。我们概述了D2C的设计选择,一个旨在将数据从DDD模拟转换为连续连续脱位动态(CDD)字段的Python软件包。概述了该转换过程的每个步骤下方的理论。

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