Fundamental Studies of Process-Material Interactions in Advanced Adhesion-Driven Manufacturing with Automated Placement of Uncured Thermoset Tows as Model Process

自动化纤维束放置（ATP）是一种粘合剂驱动的聚合物基复合材料制造工艺，其中将一束浸渍了树脂的纤维（称为纤维束）放置在工具上或放置在先前放置的纤维束上。该技术广泛应用于航空航天工业，由于其提高生产率和减少材料浪费的潜力，也引起了汽车、军事和能源部门的兴趣。ATP工艺需要施加温度和压力，工艺条件可能导致缺陷（皱纹、褶皱），这些缺陷已知对复合材料粘合强度有害，并可能导致组件过早失效。该奖项支持缺陷形成的基础研究，这将实现更好的过程模拟，这将通过为ATP制造过程提供指导来提高复合材料零件的质量。关于工艺-材料相互作用的知识的发展可以显著地减少制造缺陷，这应该减少制造周期时间，以及增加制造成本的昂贵和时间密集的人工检查。提高对基本缺陷变形机制的理解，将有助于开发用于纤维复合材料的新兴增材制造工艺，以及用于轻质复合材料结构中具有弯曲路径的复杂几何形状的ATP加工。将作出具体努力，通过南卡罗来纳大学女工程师协会从代表性不足的群体中招收研究生和本科生。此外，本研究开发的ATP制造和过程模拟模块将被纳入本科和研究生的复合材料制造课程，以提供设计和制造的控制过程-结构-性能联系的知识。更好地理解粘合驱动制造的基本原理可以提高零件质量，同时降低与返工或再制造缺陷部件相关的总体成本。本研究旨在通过研究原位粘结强度-韧性如何发展以及未固化、富含聚合物的材料在接触和粘附过程中如何形成缺陷的基本原理来填补知识空白。特别地，在特征毫秒时间尺度上，时间-温度叠加原理将应用于从新型内聚实验和高速立体数字图像相关中收集的参数。同时，将开发一个多物理场工艺模型来研究工艺参数如何影响缺陷的形成，并采用数据驱动的机器学习技术来建立无缺陷的工艺参数窗口，并为增强的制造工艺提供指导。新的基础知识将使建立无缺陷拖根放置的加工参数窗口成为可能，并将作为提高复合材料零件质量的指南。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Automated tow placement (ATP) is an adhesion-driven manufacturing process for polymer matrix composites in which a bundle of fibers impregnated with resin—known as a tow—is placed onto a tool or onto a previously-placed tow. The technique is widely used in the aerospace industry and is also gaining interest in automotive, military, and energy sectors due to its potential for improved productivity and reduced material waste. The ATP process requires application of temperature and pressure, and the process conditions can result in defects (wrinkles, folds) that are known to be detrimental to composite bond strength and can lead to premature component failure. This award supports fundamental research into defect formation that will enable better process simulations, which will enhance composite part quality by providing guidelines for the ATP manufacturing process. Knowledge developed regarding process-material interactions can significantly decrease manufacturing defects, which should reduce manufacturing cycle time, as well as expensive and time-intensive manual inspection that increases manufacturing cost. Improved understanding of fundamental defect deformation mechanisms will enable development of emerging additive manufacturing processes for fiber composites and ATP processing for complex geometries with curved paths in lightweight composite structures. A specific effort will be made to recruit graduate and undergraduate students from under-represented groups through the Society for Women Engineers at the University of South Carolina. In addition, a module on ATP manufacturing and process simulations developed in this research will be incorporated into the Composites Manufacturing course for undergraduate and graduate students to provide knowledge on the governing process-structure-property links for design and manufacturing.Improved understanding of the fundamentals of adhesion-driven manufacturing can improve part quality while reducing the overall cost associated with re-work or remanufacturing of defective components. This research aims to fill knowledge gaps by investigating the fundamentals of how in-situ bond strength-toughness develops and how defects form during contact and adhesion of uncured, polymer-rich materials. In particular, the time-temperature superposition principle at characteristic millisecond time scales will be applied using parameters gleaned from novel cohesion experiments and high speed stereo digital image correlation. In parallel, a multi-physics process model will be developed to study how process parameters affect defect formation, with data-driven machine learning techniques employed to establish defect-free process parameter windows and provide guidance for enhanced manufacturing processes. The new fundamental knowledge will enable the establishment of processing parameter windows for defect-free tow placement and will serve as a guide to enhance composite part quality.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.