Collaborative Proposal: Integrated Computational System for Probability Based Multi-Scale Model (PMM) of Ductile Fracture in Lightweight Alloys

拟议的合作研究将建立在S. Ghosh（俄勒冈州立大学首席研究员）和R. Ghanem（南加州大学联合首席研究员）开发的计算模型的基础上，开发一个基于概率的多尺度模型（PMM）的综合计算系统，用于研究含有沉淀和夹杂物的轻质金属和合金的韧性断裂。它将包含(a)由多尺度图像构建器和基于形态学的域划分组成的概率多尺度预处理器；(b)基于图像的微结构Voronoi Cell有限元模型，用于塑性变形、应变局部化和韧性断裂的精确、高分辨率分析和概率表征；(c)多尺度材料模型中基于随机均质化的连续塑性损伤宏观分析模型。PMM模拟器将有助于开发具有最佳材料微观结构的轻合金部件，以获得优异的失效性能，如延展性。主要材料、汽车和航空航天工业将显著受益于该计算系统在处理不同材料、载荷和几何结构的各种问题时的理解和灵活性。具体来说，这项研究将有助于材料行业超越现有技术，将这些轻质合金用于新的安全关键应用。两所大学的研究生将与福特研究实验室的研究人员一起工作，以发展重要的跨学科专业知识和工业接触。这种互动将提供一个全面的教育，为学生进入技术劳动力的培训。开设随机材料建模和多尺度分析的新课程。π吗?美国将在各自的大学组织研讨会，向学生和工业合作伙伴介绍这一新颖的研究领域。

The proposed collaborative research will build on computational models developed by S. Ghosh (principal investigator, OSU) and R. Ghanem (co-principal investigator, USC) to develop an integrated computational system for probability based multi-scale model (PMM) of ductile fracture in lightweight metals and alloys with precipitates and inclusions. It will incorporate (a) a probabilistic multi-scale pre-processor consisting of a multi-scale image builder and morphology based domain partitioning; (b) image based microstructural Voronoi Cell finite element model for accurate, high resolution analysis and probabilistic characterization of plastic deformation, strain localization and ductile fracture; (c) stochastic homogenization based continuum plasticity-damage model for macroscopic analysis in the multi-scale material model. The PMM simulator will help in the development of light alloy components with optimal material microstructures for superior failure properties such as ductility.Major materials, automotive and aerospace industries will benefit significantly from the comprehension and flexibility of this computational system in handling a variety of problems for different materials, loading and geometric constructs. Specifically the research will aid the materials industry, to leapfrog present technology and use these lightweight alloys in new safety-critical applications. Graduate students at two institutions will work together with researchers at Ford Research Laboratory to develop significant interdisciplinary expertise and industrial exposure. This interaction will provide a well-rounded education as students train to enter the technical workforce. New courses in Stochastic Material Modeling and Multiscale Analysis will be developed. The PI?s will organize workshops at respective universities to introduce students and industrial partners to this novel area of research.