Investigation of Heterogeneous Deformation for Discontinuous Fiber Composites Through Combined Experiments and Modeling

通过实验和建模相结合研究不连续纤维复合材料的非均匀变形

基本信息

批准号：
1662554
负责人：
Michael Sangid
金额：
$ 44.62万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1662554&HistoricalAwards=false
关键词：
Investigation Heterogeneous Deformation Discontinuous Fiber

项目摘要

The application of compression / injection molded fiber-reinforced polymer composites in automotive and aerospace applications has the potential to decrease weight while maintaining desirable mechanical performance. These discontinuous fiber reinforced composites offer an alternative to metals for improved efficiency. Even though injection molding has the ease of manufacturing benefit, this method, like all others, produces defects within the material. Uncertainties about how the complex microstructure and defects influence the mechanical response and integrity of discontinuous fiber-reinforced composites have prolonged adoption of these materials for structural applications. Uses of fiber-reinforced composites are subjected to large-scale testing programs, necessary for certification, which lead to excessive time and cost resulting from a trial-and-error approach to manufacturing. Computational models have the ability to cut the time and cost necessary for certification, but first confidence must exist in the model's predictions. In this research, measurements from x-ray tomography during in situ loading provide knowledge of the initial defects, neighboring microstructure, and strain states within the composite materials contributing to material failure. These experiments provide the foundational information and initial states to enable material strength models, in order to predict the strength of these fiber-reinforced composites. Additionally, the project efforts include a multi-objective approach to outreach, in order to educate and mentor third through eighth grade and undergraduate students and broadly disseminate the tools created during this project.In this research, the mechanical behavior of composites will be studied through x-ray tomography scans during in situ loading, followed by state-of-the-art image analysis to reconstruct, identify, and track microstructural features within the composite. Through digital volume correlation, the heterogeneous deformation of individual events such as fiber rotation, pull-out, and breakage will be quantified with respect to the local microstructure during deformation in 3D bulk material. The experiments will provide the cornerstone for strength modeling by quantifying the irreversible deformation with respect to microstructural features. Statistical modeling based on modern probability theory, including rare event modeling using large deviations, will be used to characterize the composites overall strength with respect to the multivariate spatially varying distributions. A forward modeling formulation will be used to design fiber-reinforced thermoplastics with superior strength properties. These composites will be fabricated and characterized via a similar in situ loading, x-ray tomography experiment to validate the predictive nature of the model.

压缩/注塑纤维增强聚合物复合材料在汽车和航空航天应用中的应用具有减轻重量的潜力，同时保持理想的机械性能。这些不连续纤维增强复合材料提供了金属的替代品，以提高效率。尽管注塑成型具有易于制造的优点，但与所有其他方法一样，这种方法也会在材料内产生缺陷。复杂的微观结构和缺陷如何影响不连续纤维增强复合材料的机械响应和完整性的不确定性，延长了这些材料在结构应用中的采用时间。纤维增强复合材料的使用需要经过认证所需的大规模测试计划，这会导致制造过程中的试错方法导致过多的时间和成本。计算模型能够减少认证所需的时间和成本，但首先必须对模型的预测有信心。在这项研究中，原位加载期间的 X 射线断层扫描测量提供了有关复合材料内导致材料失效的初始缺陷、邻近微观结构和应变状态的信息。这些实验提供了支持材料强度模型的基础信息和初始状态，以便预测这些纤维增强复合材料的强度。此外，该项目的工作还包括采用多目标的推广方法，以便教育和指导三年级到八年级的学生以及本科生，并广泛传播该项目期间创建的工具。在这项研究中，将通过以下方式研究复合材料的机械行为在原位加载期间进行 X 射线断层扫描扫描，然后进行最先进的图像分析，以重建、识别和跟踪复合材料内的微观结构特征。通过数字体积相关性，纤维旋转、拉出和断裂等单个事件的异质变形将根据 3D 块体材料变形过程中的局部微观结构进行量化。这些实验将通过量化微观结构特征的不可逆变形，为强度建模提供基础。基于现代概率论的统计建模，包括使用大偏差的罕见事件建模，将用于表征复合材料相对于多元空间变化分布的整体强度。正演模型配方将用于设计具有卓越强度特性的纤维增强热塑性塑料。这些复合材料将通过类似的原位加载、X 射线断层扫描实验来制造和表征，以验证模型的预测性质。

项目成果

期刊论文数量（13）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Observing progressive damage in carbon fiber epoxy laminate composites via 3D in-situ X-ray tomography

通过 3D 原位 X 射线断层扫描观察碳纤维环氧层压复合材料的渐进损伤

DOI：
10.1016/j.engfracmech.2021.107626
发表时间：
2021-04-01
期刊：
Engineering Fracture Mechanics
影响因子：
5.4
作者：
Alej;ra M. Ortiz;ra;I. Hanhan;J. Solano;M. Sangid
通讯作者：
M. Sangid

3D Fiber Segmentation with Deep Center Regression and Geometric Clustering

具有深中心回归和几何聚类的 3D 光纤分割

DOI：
发表时间：
2021-01
期刊：
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.
影响因子：
0
作者：
Aguilar, Camilo;Comer, Mary;Hanhan, Imad;Agyei, Ronald;Sangid, Michael
通讯作者：
Sangid, Michael

Comparing non-destructive 3D X-ray computed tomography with destructive optical microscopy for microstructural characterization of fiber reinforced composites

比较非破坏性 3D X 射线计算机断层扫描与破坏性光学显微镜对纤维增强复合材料微观结构表征的影响