Multi-Scale Modeling of the Stochastic Micro-Mechanical Response of Fibrous Composite Materials Based on Local Estimation and Control of Modeling Errors

基于局部估计和建模误差控制的纤维复合材料随机微机械响应的多尺度建模

• 批准号: 1100135
• 负责人: Albert Romkes
• 金额: $ 24.02万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-06-15 至 2012-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1100135&HistoricalAwards=false
• 关键词: Multi; Scale; Modeling; Stochastic; Micro

A multi-scale modeling methodology of the micro-mechanical response of fibrous composites is established. The proposed work considers nonlinear elastostatics problems in which there exists uncertainty in problem data such as material characteristics, boundary data, and loading conditions. The approach is based on the notion of model validation by controlling the modeling errors in terms of stochastic micro-scale features that are instrumental in the initiation and progression of micro-mechanical failure mechanisms. The research objectives are to: 1) investigate several variations of multi-scale modeling techniques in which easily computable homogenized material models are locally enhanced with the stochastic micro-structure; 2) develop estimates of the modeling errors, incurred by using the multi-scale surrogate descriptions; and 3) establish a methodology that can address two types of uncertainty in the problem: those governed by random variables with known probability distributions and those provided in terms of worst-case scenarios.The broader societal benefits of the proposed work are evident from the realization that heterogeneous media are encountered in many engineering disciplines such as: electrical engineering (heterogeneous conducting media), biomechanics and biomedical engineering (heterogeneities in soft tissue or bones), civil engineering (concrete structures), or petroleum engineering (subsurface flow through porous media). All those applications are inevitably accompanied with uncertainty in the problem data, generally obtained through experimental measurements (thus, inherently statistical in nature). Outreach initiatives on the high school, undergraduate, and graduate levels are proposed.

建立了纤维复合材料细观力学响应的多尺度建模方法。所提出的工作考虑非线性弹性静力学问题，其中存在的问题数据，如材料特性，边界数据和加载条件的不确定性。该方法是基于模型验证的概念，通过控制建模误差的随机微观尺度的功能，有助于在启动和发展的微观机械故障机制。研究目标是：1）研究多尺度建模技术的几种变化，其中易于计算的均匀化材料模型局部增强随机微观结构; 2）开发建模误差的估计，通过使用多尺度替代描述引起的;和3）建立一种方法，可以解决问题中的两种类型的不确定性：那些由随机变量与已知的概率分布和那些提供的最坏情况下的情况下。更广泛的社会效益的拟议工作是显而易见的，从实现异构介质中遇到的许多工程学科，如：电气工程（异质导电介质）、生物力学和生物医学工程（软组织或骨骼中的异质性）、土木工程（混凝土结构）或石油工程（通过多孔介质的地下流动）。所有这些应用都不可避免地伴随着问题数据的不确定性，这些数据通常是通过实验测量获得的（因此，本质上是统计性的）。建议在高中、本科和研究生各级开展外联活动。