Paper
7 January 2015 Mechanical properties of carbon fiber composites for applications in space
P. Hana, A. Inneman, V. Daniel, L. Sieger, M. Petru
Author Affiliations +
Proceedings Volume 9442, Optics and Measurement Conference 2014; 94420A (2015) https://doi.org/10.1117/12.2175925
Event: Optics and Measurement Conference 2014, 2014, Liberec, Czech Republic
Abstract
This article describes method of measurement mechanical properties of carbon fiber composites in space. New material structures are specifically designed for use on space satellites. Composite structures will be exposed to cosmic radiation in Earth orbit on board of a '2U CubeSat' satellite. Piezoelectric ceramic sensors are used for detection mechanical vibrations of composite test strip. A great deal of attention is paid to signal processing using 8-bit microcontroler. Fast Fourier Transformation is used. Fundamental harmonic frequencies and damping from on-board measurements will serve as the input data for terrestrial data processing. The other step of elaboration data is creation of the physical model for evaluating mechanical properties of Carbon composite - Piezoelectric ceramic system. Evaluation of anisotropic mechanical properties of piezoelectric ceramics is an interesting secondary outcome of the investigation. Extreme changes in temperature and the effect of cosmic rays will affect the mechanical properties and durability of the material used for the external construction of satellites. Comparative terrestrial measurements will be performed.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P. Hana, A. Inneman, V. Daniel, L. Sieger, and M. Petru "Mechanical properties of carbon fiber composites for applications in space", Proc. SPIE 9442, Optics and Measurement Conference 2014, 94420A (7 January 2015); https://doi.org/10.1117/12.2175925
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Cited by 5 scholarly publications.
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KEYWORDS
Composites

Sensors

Ceramics

Satellites

Finite element methods

Carbon

Statistical modeling

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