Collaborative Research: Analysis and design of material microstructure using stochastic simulation techniques

合作研究：利用随机模拟技术分析和设计材料微观结构

• 批准号: 0084547
• 负责人: George Deodatis
• 金额: $ 7.5万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-15 至 2003-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0084547&HistoricalAwards=false
• 关键词: Collaborative; Research; Analysis; design; material

0084547DeodatisIn recent years, tremendous progress has been made in the fabrication of advanced materials, such as composites. As these fabrication techniques have progressed, it has become apparent that models describing behavior of these materials need improvement in order to be properly introduced into engineering design. A major obstacle in improving these models for many materials is the high degree of randomness at the microstructural level. This research plan describes simulation-based methods that address both the improved analysis and the design of random composite microstructures, including advanced fibrous/particulate composites, cellular/porous materials, concrete, or other multi-phase materials. Specifically, the proposed research work will focus on the following three areas: 1) probabilistic characterization of material microstructures, 2) stochastic simulation of material microstructures, 3) sensitivity studies of material behavior - design issues. The sensitivity studies will identify critical sizes and clustering patterns of inclusions, volume fractions, etc. The above analyses serve two extremely important roles in engineering of composite materials: to characterize existing composite materials and to aid in improving and optimizing the design of new applications of composite materials. Because the proposed techniques are all based on finite element methods, they could potentially be applied to any phenomena that have been successfully modeled using standard (deterministic) finite element analyses, including critical stress, strain, or displacement response of mechanical/structural systems, general thermoelastic behavior, material or geometric nonlinearities, or nonlinear loadings. The study is a collaborative effort between Princeton University and The Johns Hopkins University supported under NSF initiative 00-26, Exploratory Research on Model-Based Simulation.***

0084547 Deodata近年来，在先进材料如复合材料的制造方面取得了巨大的进步。随着这些制造技术的发展，很明显，描述这些材料行为的模型需要改进，以便适当地引入工程设计。许多材料在改进这些模型中的一个主要障碍是微观结构水平上的高度随机性。该研究计划描述了基于模拟的方法，这些方法解决了随机复合材料微观结构的改进分析和设计，包括先进的纤维/颗粒复合材料，蜂窝/多孔材料，混凝土或其他多相材料。具体而言，拟议的研究工作将集中在以下三个领域：1）材料微结构的概率表征，2）材料微结构的随机模拟，3）材料行为的敏感性研究-设计问题。敏感性研究将确定夹杂物、体积分数等的临界尺寸和聚集模式。上述分析在复合材料工程中发挥着两个极其重要的作用：表征现有复合材料并帮助改进和优化新应用的设计复合材料。由于所提出的技术都是基于有限元方法，它们可以潜在地应用于任何现象，已成功地使用标准（确定性）有限元分析，包括临界应力，应变，或位移响应的机械/结构系统，一般的热弹性行为，材料或几何非线性，或非线性载荷建模。这项研究是普林斯顿大学和约翰霍普金斯大学在NSF倡议00-26，基于模型的模拟探索性研究的支持下的合作努力。