In Situ Micro-computed Tomography of Re-entry Fabrics Under Tensile Loading

被引:0
作者
Foster, Collin [1 ]
Phillippe, Cutler [1 ]
Roca, Laura Villafane [1 ]
Panerai, Francesco [1 ]
机构
[1] Univ Illinois, Dept Aerosp Engn, Urbana, IL 61801 USA
来源
TMS 2024 153RD ANNUAL MEETING & EXHIBITION: SUPPLEMENTAL PROCEEDINGS | 2024年
关键词
Textile modeling; Microstructure; X-ray tomography; Synchrotron radiation; Machine learning; THICKNESS PERMEABILITY; COMPOSITES; COMPUTATION; GENERATION; FRAMEWORK;
D O I
10.1007/978-3-031-50349-8_144
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study addresses the lack of rapidly exploitable experimental data for benchmarking fluid structure interaction models used in simulating parachutes for planetary landing systems. Results from in mu-CT imaging of parachute textiles under loaded conditions using a 2D tensile tester are presented in tandem with the application of a high-accuracy segmented tomography produced via machine learning. The sample used in this study is MIL-C-44378(GL) Type II parachute textile. The images are processed to track the locations and dimensions of individual tows within the scanned region, enabling the reconstruction and monitoring of the microscale properties of each tow and the overall scanned volume. Specifically, the images highlight the importance of load history on textile performance for experiments with radial loads relevant to those in-flight. The material is found to have permanent deformation after removal of load, indicating irreversible changes to architecture when loaded. Pore sizes do not return to initial distributions after removal of load, but overall pore ratio does. This is a result of fewer smaller pores existing after load is removed due to fiber reorganization. Crimp angles do not change for the warp tows due to pretension during manufacturing, but the weft crimp angles do decrease with load, being mostly recovered after loading is reduced.
引用
收藏
页码:1681 / 1692
页数:12
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