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质、高刚度、强度和韧性的结合而闻名，尽管最近取得了显着的进展，但它有可能显着降低能源、汽车和航空航天工程等行业的运营成本并提高资产的性能。进步，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，考虑到成分的最佳非线性行为和复杂的几何形状，该学院早期职业发展（职业）奖通过一个解决这一挑战的方法。综合教育和研究该研究计划的重点是提高涉及极端载荷条件下非线性行为和潜在损伤的复合材料的最先进的复合材料建模和设计能力，该框架将用于揭示微观结构的组成特性之间的基本关系。一个全面的教育计划是培养具有强大复合材料背景的下一代专业人士，以满足国家对高性能材料不断增长的需求。首先，将考虑开发用于快速多尺度分析和探测材料响应空间的自适应多尺度降阶模型。真实的复合材料行为，重点关注粘弹性行为和基体损坏、增强材料损坏以及材料界面的内聚脱粘。多尺度模型将通过直接数值模拟进行彻底验证，并使用不同混合的实验数据进行验证。最后，该模型将被纳入基于多分辨率梯度的降阶设计（材料和形状）框架中，从而实现混合复合材料微观结构的高效设计。该建模和设计框架将使我们能够开发具有定制功能的先进复合材料。它还具有指导和指导先进制造技术的潜力，有助于精确制造具有优化微观结构的材料。该项目由材料与结构力学 (MoMS) 计划和刺激竞争既定计划联合资助。研究 (EPSCoR)。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。