Identifying Structure-Property Relationships Through DREAM.3D Representative Volume Elements and DAMASK Crystal Plasticity Simulations: An Integrated Computational Materials Engineering Approach
Identifying Structure-Property Relationships Through DREAM.3D Representative Volume Elements and DAMASK Crystal Plasticity Simulations: An Integrated Computational Materials Engineering Approach
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DOI：
10.1007/s11837-017-2303-0
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发表时间：
2017-05-01
期刊：
影响因子：
2.6
通讯作者：
Raabe, Dierk
中科院分区：
文献类型：
--
作者：
Diehl, Martin;Groeber, Michael;Raabe, Dierk
预测、理解和控制材料的力学行为是设计结构材料时最重要的任务。现代合金系统，其中多种变形机制，相，和缺陷，以克服逆强度-延展性关系，提高了多种可能性修改的变形行为，使传统的，完全基于实验的合金开发工作流程不合适。为了快速和有效的合金设计，因此期望通过模拟研究来预测候选合金的机械性能，以取代耗时和消耗资源的机械测试。适用于此任务的模拟工具需要根据合金成分、显微组织、织构、相分数和加工历史正确预测机械行为。在这里，一个集成的计算材料工程方法的基础上的开源软件包DREAM.3D和DAMASK（杜塞尔多夫先进材料模拟工具包），使这样的虚拟材料开发。更具体地说，我们的方法包括以下三个步骤：（1）获取描述微观结构的统计量，（2）基于这些量使用DREAM.3D构建代表性体积元素，以及（3）使用DAMASK提供的预测晶体塑性材料模型评估代表性体积。示例性地，这些步骤在此针对高锰钢进行。
Predicting, understanding, and controlling the mechanical behavior is the most important task when designing structural materials. Modern alloy systems-in which multiple deformation mechanisms, phases, and defects are introduced to overcome the inverse strength-ductility relationship-give raise to multiple possibilities for modifying the deformation behavior, rendering traditional, exclusively experimentally-based alloy development workflows inappropriate. For fast and efficient alloy design, it is therefore desirable to predict the mechanical performance of candidate alloys by simulation studies to replace time- and resource-consuming mechanical tests. Simulation tools suitable for this task need to correctly predict the mechanical behavior in dependence of alloy composition, microstructure, texture, phase fractions, and processing history. Here, an integrated computational materials engineering approach based on the open source software packages DREAM.3D and DAMASK (Dusseldorf Advanced Materials Simulation Kit) that enables such virtual material development is presented. More specific, our approach consists of the following three steps: (1) acquire statistical quantities that describe a microstructure, (2) build a representative volume element based on these quantities employing DREAM.3D, and (3) evaluate the representative volume using a predictive crystal plasticity material model provided by DAMASK. Exemplarily, these steps are here conducted for a high-manganese steel.