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Author(s):	Ge, Zhi; Wang, Dawei; Sun, Renjuan; Oeser, Markus
Title:
Abstract:	Im Rahmen dieser Arbeit wurden selbstüberwachende Probekörper aus Zement mit mehrlagigen Kohlenstoffnanoröhren (multiwall carbon nanotubes MWCNT) hergestellt und einer zyklischen Belastung unterzogen. Der elastische Widerstand und die Piezoresistivität der Probekörper wurden bei unterschiedlicher Temperatur und verschiedenen Wassergehalten untersucht. Die Ergebnisse zeigen, dass mit steigender Temperatur der elektrische Widerstand und die Piezoresistivität sinken. Mit erhöhtem Wassergehalt verringert sich der elektrische Widerstand, während die Piezoresistivität erst zu- und dann abnimmt. Die Hauptursache für die Änderung des spezifischen Widerstandes und der Piezoresistivität ist die Veränderung der Tunnelleitung unter verschiedenen Bedingungen. Der Zusammenhang zwischen Wassergehalt, Temperatur und der Resistivitätsänderung konnte mit einer Regressionsfunktion bei einem korrigierten Bestimmtheitsmaß R2 von 0,92 dargestellt werden. Carbon nanotube-cement composite for self-sensing concrete pavement Self-sensing materials could sense their own strain and damages without sensors. Smart concrete pavement made with cement based self-sensing materials could achieve in-situ monitoring for both structural integrity and traffic characteristics. This paper studied the electrical resistivity and piezoresistivity of cement with multiwall carbon nanotubes (MWCNTs) under cyclic loading. Effects of temperature and water content on both resistivity and piezoresistivity were investigated. Test results show that the resistivity decreased as the water content increased. Differently, the piezoresistivity and change in resistance first increased and then decreased. Temperature had significant effect on resistivity and piezoresistivity. As the temperature increased, resistivity decreased but the piezoresistivity increased. The major cause of the change in resistivity and piezoresistivity was the change of tunneling conduction under different conditions. The relationship between water content, temperature and the resistivity could be accurately represented with a regression function with an R2 of 0.92. Therefore, the data collected by self-sensing materials must be calibrated for the water content and temperature before interpretation.
Source:	Bautechnik 92 (2015), No. 3
Page/s:	189-195
Language of Publication:	German

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