Integrated Multiscale Computational and Experimental Investigations on Fracture of Additively Manufactured Polymer Composites

该项目将利用实验研究创造新的计算能力，以了解3D打印聚合物复合材料中的断裂和失效。3D打印正在从示范原型过渡到功能性产品，影响到广泛的工业部门。然而，许多基于聚合物的3D打印部件容易破裂和失效。这限制了它们在承重部件中的应用。用颗粒和/或纤维增强的各种聚合物复合长丝正在被开发，以改善3D打印部件的性能。3D打印的复杂多变性阻碍了目前的研究和开发。因此，它在很大程度上仍处于反复试验阶段，没有足够的科学指导。该项目将开发一种以科学为基础的策略，将计算建模和模拟与一套最佳实验相结合。这种方法有助于对多尺度断裂有一个基本的了解，也有助于量化与3D打印聚合物复合材料相关的不确定性。通过这项研究获得的新知识可以为高性能部件的3D打印开发新技术。这项研究的结果可以应用于广泛的行业。这项研究将得到教育和外联活动的补充。其中包括课程改进、动手3D打印工作坊，以及面向K-12和代表性不足的少数族裔学生的STEM教育计划。本项目将承担量化过程-结构-性能-性能关系的挑战，并为添加制造的聚合物复合材料推导多尺度断裂力学机制。虽然添加剂制造能够打印具有相对复杂几何形状的部件，但在AM能够进一步生产功能复合材料之前，必须解决几个基本问题。目前的限制包括制造过程中引起的强烈温度梯度导致的微结构缺陷、异质界面结合条件以及较大的断裂和失效性能差异。因此，该项目的研究目标包括：1)开发能够预测添加剂制造过程中的热-力-化学耦合和流体-结构相互作用的直接中尺度模拟，这将解决关于细丝和增强颗粒/纤维之间的运动和变形、温度梯度、熔融/凝固与微裂纹的形核和扩展如何相互作用的基本问题；2)基于微裂纹模拟的机器学习和宏观裂纹预测的相场模型，推导出多尺度断裂模型，制造过程的现场监测和多尺度实验特征被用于直接模型验证；以及3)开发基于模型的最优不确定性量化协议，该协议组织计算和实验活动以验证模型、调查参数敏感性并量化过程/特性变化。研究成果将促进关于添加剂制造工艺参数和断裂行为之间复杂相互作用的基础知识。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 project will create new computational capabilities using experimental investigations to understand fracture and failure in 3D printed polymer composites. 3D printing is transitioning from demonstrative prototypes to functional products that impact a wide range of industrial sectors. However, many polymer-based 3D printed parts are prone to fracture and failure. This limits their applications in load-bearing components. Various polymer composite filaments reinforced with particles and/or fibers are being developed to improve the performance of 3D printed components. The current research and development are hindered by the complex variabilities of 3D printing. It thus largely remains in a trial-and-error stage with insufficient scientific guidance. This project will develop a science-based strategy that combines computational modeling and simulations with an optimal suite of experiments. This approach helps to gain a fundamental understanding of multiscale fracture as well as to quantify uncertainties associated with 3D printed polymer composites. The new knowledge achieved through this research can develop new technologies for 3D printing of high-performance components. The outcomes of this research can be applied to a broad array of industries. The research will be complemented by educational and outreach activities. These include curriculum enhancements, hands-on 3D printing workshops, and STEM education programs that engage K-12 and underrepresented minority students.This project will take on the challenges of quantifying the process-structure-property-performance relationship and deriving multiscale fracture mechanics mechanisms for additively manufactured polymer composites. Although additive manufacturing is capable of printing parts with relatively complex geometries, several fundamental issues must be addressed before AM can advance to producing functional composites. Current limitations include microstructural defects due to strong thermal gradients induced during manufacturing, heterogeneous interface bonding conditions, and large fracture and failure performance variations. The research objectives of this project thus include: 1) developing direct mesoscale simulations capable of predicting thermo-mechanical-chemical coupling and fluid-structure interactions during the additive manufacturing process, which will address fundamental questions of how motions and deformations, temperature gradients, melting/solidification between filaments and reinforced particles/fibers interplay with one other in assocoation with micro-crack nucleation and propagation; 2) deriving multiscale modeling of fracture based on machine learning of micro-crack simulations and phase-field models of macro-crack predictions, with in-situ monitoring of manufacturing processes and multiscale experimental characterizations being used for direct model validations; and 3) developing an optimal model-based uncertainty quantification protocol that organizes computational and experimental activities to validate the model, investigate parameter sensitivities, and quantify process/property variations. The research outcomes will advance fundamental knowledge of the complex interplay between additive manufacturing process parameters and fracture behaviors.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.