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A proper orthogonal decomposition approach to microstructure model reduction in Rodrigues space with applications to optimal control of microstructure-sensitive properties

机译:一种适当的正交分解方法,用于罗德里格斯空间微观结构模型的还原及其在微观结构敏感性质优化控制中的应用

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摘要

A novel reduced-order modeling approach to represent crystallographic texture in polycrystals is presented. This method involves generation of a reduced orthogonal basis for representing polycrystal texture in Rodrigues space. The reduced basis is generated from the textursobtained from different deformation modes (shear, uniaxial tension, etc.) using proper orthogonal decomposition and the method of snapshots. This model reduction can account for all essential information needed to describe the microstructure and leads to tremendous savings in computational time. Based on the above method a multiscale model for microstructure evolution during deformation is proposed driven by the macroscale velocity gradient. A continuum sensitivity-based gradient optimization framework is introduced in the above model for control of microstructure-sensitive material properties. Emphasis is given to relevant design problems that demonstrate the effectiveness of the above method for optimal control of texture-dependent material properties during deformation such as the magnetic hysteresis losses, the yield stress and the Lankford parameter R.
机译:提出了一种新的降阶建模方法来表示多晶中的晶体结构。该方法涉及生成用于表示罗德里格斯空间中多晶纹理的简化正交基。使用适当的正交分解和快照方法,从不同变形模式(剪切、单轴拉伸等)获得的纹理中生成还原基。这种模型简化可以解释描述微观结构所需的所有基本信息,并大大节省计算时间。基于上述方法,提出了一种由宏观速度梯度驱动的变形过程中微观组织演化的多尺度模型。在上述模型中引入了一种基于连续灵敏度的梯度优化框架,用于控制微观结构敏感材料性能。重点介绍了相关的设计问题,这些问题证明了上述方法在变形过程中对与织构相关的材料特性进行优化控制的有效性,例如磁滞损耗、屈服应力和兰克福德参数 R。

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