CAREER: Multiscale Reduced Order Modeling and Design to Elucidate the Microstructure-Property-Performance Relationship of Hybrid Composite Materials

职业：通过多尺度降阶建模和设计来阐明混合复合材料的微观结构-性能-性能关系

• 批准号: 2341000
• 负责人: Xiang Zhang
• 金额: $ 60万
• 依托单位: University of Wyoming
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-08-01 至 2029-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2341000&HistoricalAwards=false
• 关键词: CAREER; Multiscale; Reduced; Order; Modeling

High-performance composite materials, known for their combination of lightweight, high stiffness, strength, and toughness, have the potential to significantly reduce operational costs and enhance the performance of assets in industries such as energy, automotive, and aerospace engineering. Despite notable recent advancements, there is currently a lack of an effective predictive modeling and optimization framework to aid in designing these advanced composite materials, considering the optimal nonlinear behavior and complex geometries of the constituents. This Faculty Early Career Development (CAREER) award addresses this challenge through an integrated educational and research program. The research program focuses on advancing the state-of-the-art composite modeling and design capabilities for composites involving nonlinear behavior and potential damage under extreme loading conditions. This framework will be utilized to uncover the fundamental relationship between the microstructure's constituent properties, geometries, and structural performance. A comprehensive educational plan is to train the next generation of professionals with a strong background in composites to meet the nation’s growing demand for high-performance materials. The goal of this CAREER award is to elucidate the microstructure-property-performance relationship for composite materials by developing and exercising an efficient and accurate multiscale reduced order modeling and design framework. First, an adaptive multiscale reduced order model for rapid multiscale analysis and probing of the material response space will be developed. The model will consider realistic composite material behavior with a focus on viscoelastic behavior and damage of the matrix, damage of the reinforcement, and cohesive debonding of the material interface. The multiscale model will be thoroughly verified against direct numerical simulation and validated using experimental data for different hybrid composites. Finally, the model will be incorporated into a multi-resolution gradient-based reduced order design (material and shape) framework that enables the efficient design of hybrid composite microstructures. The modeling and design framework will empower us to develop advanced composites with tailored mechanical properties. It also has the potential to inform and guide advanced manufacturing techniques, facilitating precise fabrication of materials with optimized microstructures.This project is jointly funded by the Mechanics of Materials and Structures (MoMS) program and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

高性能复合材料以其轻巧，高刚度，强度和韧性的结合而闻名，有可能显着降低运营成本并提高能源，汽车和航空工程等行业的资产绩效。尽管最近有了显着进步，但考虑到构建体的最佳非线性行为和复杂的几何形状，目前缺乏有效的预测建模和优化框架来帮助设计这些先进的复合材料。该教师早期职业发展（职业）奖通过一体的综合教育和研究计划解决了这一挑战。该研究计划致力于推进涉及非线性行为和在极端负荷条件下潜在损害的复合材料的最新综合建模和设计能力。该框架将用于发现微观结构的组成特性，几何形状和结构性能之间的基本关系。一项综合的教育计划是培训具有强大作品背景的下一代专业人士，以满足该国对高性能材料的不断增长的需求。该职业生涯奖的目标是通过开发和行使有效，准确的多尺度降低订单建模和设计框架来阐明复合材料的微结构 - 绩效关系。首先，将开发一个自适应的多尺度减少订单模型，用于快速多尺度分析和对材料响应空间进行探测。该模型将考虑逼真的复合材料行为，重点是粘弹性行为和矩阵的损坏，加固的损坏以及材料界面的凝聚力剥离。多尺度模型将对直接数值模拟进行彻底验证，并使用不同混合组成的实验数据进行验证。最后，该模型将合并到基于多分辨率梯度的降低订单设计（材料和形状）框架中，该框架可以有效地设计混合复合微观结构。建模和设计框架将使我们能够开发具有量身定制的机械性能的高级构图。它还有可能告知和指导先进的制造技术，从而通过优化的微观结构来支持精确制造材料。该项目由材料和结构（MOMS）计划的机制和启发竞争性研究的既定计划（EPSCOR）共同资助。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的审查标准通过评估来通过评估来支持的。