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机械测试过程中结构材料损伤的实时定量分析。

Real-time quantification of damage in structural materials during mechanical testing.

作者信息

Christian W J R, Dvurecenska K, Amjad K, Pierce J, Przybyla C, Patterson E A

机构信息

School of Engineering, University of Liverpool, Liverpool, UK.

University of Dayton Research Institute, Dayton, OH, USA.

出版信息

R Soc Open Sci. 2020 Mar 4;7(3):191407. doi: 10.1098/rsos.191407. eCollection 2020 Mar.

Abstract

A novel methodology is introduced for quantifying the severity of damage created during testing in composite components. The method uses digital image correlation combined with image processing techniques to monitor the rate at which the strain field changes during mechanical tests. The methodology is demonstrated using two distinct experimental datasets, a ceramic matrix composite specimen loaded in tension at high temperature and nine polymer matrix composite specimens containing fibre-waviness defects loaded in bending. The changes in the strain field owing to damage creation are shown to be a more effective indicator that the specimen has reached its proportional limit than using load-extension diagrams. The technique also introduces a new approach to using experimental data for creating maps indicating the spatio-temporal distribution of damage in a component. These maps indicate where damage occurs in a component, and provide information about its morphology and its time of occurrence. This presentation format is both easier and faster to interpret than the raw data which, for some tests, can consist of tens of thousands of images. This methodology has the potential to reduce the time taken to interpret large material test datasets while increasing the amount of knowledge that can be extracted from each test.

摘要

本文介绍了一种用于量化复合材料部件测试过程中产生的损伤严重程度的新方法。该方法利用数字图像相关技术结合图像处理技术来监测机械测试过程中应变场的变化速率。通过两个不同的实验数据集对该方法进行了验证,一个是高温拉伸加载的陶瓷基复合材料试样,另一个是九个含有纤维波纹缺陷的聚合物基复合材料试样的弯曲加载。结果表明,与使用载荷-伸长图相比,由于损伤产生导致的应变场变化是试样达到比例极限的更有效指标。该技术还引入了一种新方法,即利用实验数据创建地图,以显示部件中损伤的时空分布。这些地图指示了部件中损伤发生的位置,并提供了有关其形态和发生时间的信息。这种呈现形式比原始数据更易于解释,对于某些测试,原始数据可能包含数以万计的图像。该方法有可能减少解释大型材料测试数据集所需的时间,同时增加从每次测试中可以提取的知识量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba7/7137972/ef3bde7972fd/rsos191407-g1.jpg

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