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Austin Downey  - - - 
Top co-authors
Simon Laflamme

118 shared publications

Associate Professor, Dept. of Civil, Construction, and Environmental Engineering and Dept. of Electrical and Computer Engineering, Iowa State Univ., Town Engineering #416A, Ames, IA 50011

Filippo Ubertini

108 shared publications

Department of Civil and Environmental Engineering, University of Perugia, Via G. Duranti, 93-06125 Perugia, Italy

Antonella D’Alessandro

49 shared publications

Department of Civil and Environmental Engineering, Via G. Duranti 93, 06125 Perugia, Italy

Enrique García-Macías

27 shared publications

Department of Civil and Environmental Engineering; University of Perugia; Perugia Italy

28
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Publication Record
Distribution of Articles published per year 
(2015 - 2018)
Total number of journals
published in
 
24
 
Publications See all
Article 0 Reads 0 Citations Incipient Damage Detection for Large Area Structures Monitored With a Network of Soft Elastomeric Capacitors Using Relat... Austin Downey, MohammadKazem Sadoughi, Simon Laflamme, Chao ... Published: 01 November 2018
IEEE Sensors Journal, doi: 10.1109/jsen.2018.2868135
DOI See at publisher website
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Passive Variable Friction Damper for Increased Structural Resilience to Multi-Hazard Excitations Austin Downey, MohammadKazem Sadoughi, Liang Cao, Simon Lafl... Published: 26 August 2018
Volume 2A: 44th Design Automation Conference, doi: 10.1115/detc2018-85207
DOI See at publisher website
PROCEEDINGS-ARTICLE 4 Reads 0 Citations Durability assessment of soft elastomeric capacitor skin for SHM of wind turbine blades Anna Laura Pisello, Claudia Fabiani, Luigi Torre, Elena Fort... Published: 27 March 2018
Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XII, doi: 10.1117/12.2296518
DOI See at publisher website
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Surrogate model for condition assessment of structures using a dense sensor network Jin Yan, Austin Downey, Alessandro Cancelli, An Chen, Filipp... Published: 27 March 2018
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, doi: 10.1117/12.2296711
DOI See at publisher website
PROCEEDINGS-ARTICLE 2 Reads 0 Citations Strain monitoring in masonry structures using smart bricks Antonella D'alessandro, Filippo Ubertini, Austin Downey, Sim... Published: 27 March 2018
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, doi: 10.1117/12.2297526
DOI See at publisher website
Article 2 Reads 2 Citations An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Na... Andrea Meoni, Antonella D’Alessandro, Austin Downey, Enrique... Published: 09 March 2018
Sensors, doi: 10.3390/s18030831
DOI See at publisher website ABS Show/hide abstract
The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.
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