QRM: Microstructural Quantification and Virtual Reconstruction of Polymer Matrix Composites within the Integrated Computational Materials Engineering (ICME) Approach

这笔赠款将支持与复杂结构制造过程相关的新知识、促进科学进步、促进国家繁荣和保障国防安全的研究。聚合物复合材料是一种较轻的金属替代品，具有改变高能效航空航天、汽车和基础设施应用的潜力。纤维增强复合材料将嵌入在耐用聚合物中的高强度纤维结合在一起，使它们具有非常轻的定向性能。然而，与金属相比，这些材料在性能上的一致性较差，导致成本高昂的过度设计。这种性能差异的部分原因是纤维在纤维增强复合材料中的分散，因此，对纤维行为的基本了解对于可靠地制造纤维增强聚合物基复合材料至关重要。该奖项支持基础研究，通过了解纤维分散性和基于制造工艺的聚合物性能之间的联系来了解复合材料中的可变性。这项研究将能够量化复合材料在制造后的可变性，这将允许设计出更可靠的结构，具有更高的性能可预测性，增加安全性和降低成本。这项研究涉及多个学科，包括材料科学、制造、结构工程和数学。这种多学科的方法将对工程教育产生积极的影响，推广活动的目的是扩大对科学研究的参与。本研究旨在阐明纤维增强复合材料结构的制造工艺-微观结构-性能关系，并量化微观尺度的不确定性及其在复合材料水平上的传播。该研究团队将执行材料表征，包括高分辨率断层扫描和微拉曼散射研究，以量化微观尺度上的纤维空间分布和基质原位特性；实施纤维增强复合材料微结构的虚拟结构重建，确定基于物理的统计描述符，并虚拟复制统计上等效的固化模型。实验和建模相结合，以量化固化过程中的残余应力、局部微结构、性能和性能之间的关系。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This grant will support research that will contribute new knowledge related to the manufacturing process of complex structures, promoting the progress of science, advancing national prosperity and securing national defense. Polymer composites are a lighter-weight alternative to metals that have the potential to transform energy efficient aerospace, automotive and infrastructure applications. Fiber-reinforced composites combine high-strength fibers embedded within a durable polymer to give them directional properties with very little weight. However, these materials suffer from less consistency in performance than metals, resulting in costly over-design. Some of this performance variability is attributed to dispersion of fibers in fiber-reinforced composites, and thus a fundamental understanding of the fiber behavior is critical to reliable manufacturing of fiber-reinforced polymer matrix composites. This award supports fundamental research to understand variability in composites by understanding the tie between fiber dispersion and polymer properties based on the manufacturing process. This research will enable the quantification of variability in composites after manufacturing, which will allow the design of more reliable structures with higher performance predictability, increasing safety and reducing cost. This research involves several disciplines, including materials science, manufacturing, structural engineering and mathematics. The multi-disciplinary approach will positively impact engineering education, and outreach activities are aimed at broadening participation in scientific research.This research aims to elucidate the manufacturing process-microstructure-property relationships of fiber-reinforced composite structures, and quantify uncertainty at the micro scale and its propagation at the composite level. The research team will perform material characterization, including high-resolution tomography and micro-Raman scattering studies to quantify fiber spatial distribution and matrix in-situ properties at the micro-scale; implement virtual structure reconstruction of fiber-reinforced composite microstructures, determine physics-based statistical descriptors, and virtually reproduce statistically equivalent curing models. Experiments and modeling are integrated to quantify the relationships among residual stress during curing, local microstructure, properties and performance.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.