Multi-Information Source Fusion and Optimization to Realize ICME: Application to Dual-Phase Materials
Multi-Information Source Fusion and Optimization to Realize ICME: Application to Dual-Phase Materials
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多信息源融合与优化实现ICME：在双相材料中的应用
DOI：
10.1115/1.4041034
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发表时间：
2018
影响因子：
3.3
通讯作者：
Allaire, Douglas
中科院分区：
文献类型：
--
作者：
Ghoreishi, Seyede Fatemeh;Molkeri, Abhilash;Srivastava, Ankit;Arroyave, Raymundo;Allaire, Douglas
集成计算材料工程（ICME）要求将计算工具集成到材料和部件开发周期中，而材料基因组计划（MGI）则要求通过实验，模拟和数据的结合来加速材料开发周期。目前，ICME和MGI都没有规定如何实现必要的工具集成，或者如何有效地利用计算工具，结合实验，以加速新材料和材料系统的开发。本文解决了第一个问题，提出了一个框架的信息融合，利用源/模型之间的相关性和源之间的“地面真相”。第二个问题是通过一个多信息源优化框架来解决的，该框架在给定当前知识的情况下，确定要查询的下一个最佳信息源，以及在输入空间中通过一个新的值梯度策略来查询它。查询决策考虑了学习信息源之间的相关性的能力、查询信息源的资源成本以及期望查询在当前状态的改进方面提供什么。该框架上的双相钢，以最大限度地提高其强度归一化应变硬化率的优化。地面实况由基于微结构的有限元模型表示，而三个低保真度信息源-即，降阶模型--基于不同的均匀化假设--等应变、等应力和等工作--用于有效和最佳地查询材料设计空间。
Integrated Computational Materials Engineering (ICME) calls for the integration of computational tools into the materials and parts development cycle, while the Materials Genome Initiative (MGI) calls for the acceleration of the materials development cycle through the combination of experiments, simulation, and data. As they stand, both ICME and MGI do not prescribe how to achieve the necessary tool integration or how to efficiently exploit the computational tools, in combination with experiments, to accelerate the development of new materials and materials systems. This paper addresses the first issue by putting forward a framework for the fusion of information that exploits correlations among sources/models and between the sources and “ground truth.” The second issue is addressed through a multi-information source optimization framework that identifies, given current knowledge, the next best information source to query and where in the input space to query it via a novel value-gradient policy. The querying decision takes into account the ability to learn correlations between information sources, the resource cost of querying an information source, and what a query is expected to provide in terms of improvement over the current state. The framework is demonstrated on the optimization of a dual-phase steel to maximize its strength-normalized strain hardening rate. The ground truth is represented by a microstructure-based finite element model while three low fidelity information sources—i.e., reduced order models—based on different homogenization assumptions—isostrain, isostress, and isowork—are used to efficiently and optimally query the materials design space.
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