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• W2534088894 endingPage "124009" @default.
• W2534088894 startingPage "124009" @default.
• W2534088894 abstract "A large-area electronics in the form of a soft elastomeric capacitor (SEC) has shown great promise as a strain sensor for fatigue crack monitoring in steel structures. The SEC sensors are inexpensive, easy to fabricate, highly stretchable, and mechanically robust. It is a highly scalable technology, capable of monitoring deformations on mesoscale systems. Preliminary experiments verified the SEC sensor's capability in detecting, localizing, and monitoring crack growth in a compact specimen. Here, a numerical simulation method is proposed to simulate accurately the sensor's performance under fatigue cracks. Such a method would provide a direct link between the SEC's signal and fatigue crack geometry, extending the SEC's capability to dense network applications on mesoscale structural components. The proposed numerical procedure consists of two parts: (1) a finite element (FE) analysis for the target structure to simulate crack growth based on an element deletion method; (2) an algorithm to compute the sensor's capacitance response using the FE analysis results. The proposed simulation method is validated based on test data from a compact specimen. Results from the numerical simulation show good agreement with the SEC's response from the laboratory tests as a function of the crack size. Using these findings, a parametric study is performed to investigate how the SEC would perform under different geometries. Results from the parametric study can be used to optimize the design of a dense sensor network of SECs for fatigue crack detection and localization." @default.
• W2534088894 created "2016-10-28" @default.
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• W2534088894 date "2016-10-21" @default.
• W2534088894 modified "2023-09-23" @default.
• W2534088894 title "Numerical simulation and experimental validation of a large-area capacitive strain sensor for fatigue crack monitoring" @default.
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• W2534088894 doi "https://doi.org/10.1088/0957-0233/27/12/124009" @default.
• W2534088894 hasPublicationYear "2016" @default.
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