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Austin Downey  - - - 
Top co-authors See all
Elena Fortunati

132 shared publications

Univ. degli Studi di Perugia (Italy)

Claudia Fabiani

43 shared publications

Univ. degli Studi di Perugia (Italy)

Filippo Ubertini

35 shared publications

James Ricles

30 shared publications

Leifur Leifsson

23 shared publications

Iowa State Univ. (United States)

24
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Publication Record
Distribution of Articles published per year 
(2015 - 2018)
Total number of journals
published in
 
16
 
Publications See all
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 2018, doi: 10.1117/12.2296711
DOI See at publisher website
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Condition assessment of civil infrastructures is difficult due to technical and economic constraints associated with the scaling of sensing solutions. When scaled appropriately, a large sensor network will collect a vast amount of rich data that is difficult to directly link to the existing condition of the structure along with its remaining useful life. This paper presents a methodology to construct a surrogate model enabling diagnostic of structural components equipped with a dense sensor network collecting strain data. The surrogate model, developed as a matrix of discrete stiffness elements, is used to fuse spatial strain data into useful model parameters. Here, strain data is collected from a sensor network that consists of a novel sensing skin fabricated from large area electronics. The surrogate model is constructed by updating the stiffness matrix to minimize the difference between the model’s response and measured data, yielding a 2D map of stiffness reduction parameters. The proposed method is numerically validated on a plate equipped with 40 large area strain sensors. Results demonstrate the suitability of the proposed surrogate model for the condition assessment of structures using a dense sensor network.
PROCEEDINGS-ARTICLE 1 Read 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 2018, doi: 10.1117/12.2297526
DOI See at publisher website
ABS Show/hide abstract
Monitoring a building’s structural performance is critical for the identification of incipient damages and the optimization of maintenance programs. The characteristics and spatial deployment of any sensing system plays an essential role in the reliability of the monitored data and, therefore, on the actual capability of the monitoring system to reveal early-stage structural damage. A promising strategy for enhancing the quality of a structural health monitoring system is the use of sensors fabricated using materials exhibiting similar mechanical properties and durability as those of the construction materials. Based on this philosophy, the authors have recently proposed the concept of "smart-bricks" that are nanocomposite clay bricks capable of transducing a change in volumetric strain into a change in a selected electrical property. Such brick-like sensors could be easily placed at critical locations within masonry walls, being an integral part of the structure itself. The sensing is enabled through the dispersion of fillers into the constitutive material. Examples of fillers include titania, carbon-based particles, and metallic microfibers. In this paper, experimental tests are conducted on bricks doped with different types of carbon-based fillers, tested both as standalone sensors and within small wall systems. Results show that mechanical properties as well as the smart brick’s strain sensitivity depend on the type of filler used. The capability of the bricks to work as strain monitoring sensors within small masonry specimens is also demonstrated.
PROCEEDINGS-ARTICLE 1 Read 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
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Renewable energy production has become a key research driver during the last decade. Wind energy represents a ready technology for large-scale implementation in locations all around the world. While important research is conducted to optimize wind energy production efficiency, a critical issue consists of monitoring the structural integrity and functionality of these large structures during their operational life cycle. This paper investigates the durability of a soft elastomeric capacitor strain sensing membrane, designed for structural health monitoring of wind turbines, when exposed to aggressive environmental conditions. The sensor is a capacitor made of three thin layers of an SEBS polymer in a sandwich configuration. The inner layer is doped with titania and acts as the dielectric, while the external layers are filled with carbon black and work as the conductive plates. Here, a variety of samples, not limited to the sensor configuration but also including its dielectric layer, were fabricated and tested within an accelerated weathering chamber (QUV) by simulating thermal, humidity, and UV radiation cycles. A variety of other tests were performed in order to characterize their mechanical, thermal, and electrical performance in addition to their solar reflectance. These tests were carried out before and after the QUV exposures of 1, 7, 15, and 30 days. The tests showed that titania inclusions improved the sensor durability against weathering. These findings contribute to better understanding the field behavior of these skin sensors, while future developments will concern the analysis of the sensing properties of the skin after aging.
PREPRINT 0 Reads 0 Citations An Experimental Study on Static and Dynamic Strain Sensitivity of Smart Concrete Sensors Doped with Carbon Nanotubes for... Andrea Meoni, Antonella D'Alessandro, Austin Downey, Enrique... Published: 07 February 2018
doi: 10.20944/preprints201802.0063.v1
DOI See at publisher website
PROCEEDINGS-ARTICLE 0 Reads 0 Citations An Iterative Signal Fusion Method for Reconstruction of In-Plane Strain Maps from Strain Measurements by Hybrid Dense Se... Mohammadkazem Sadoughi, Austin Downey, Chao Hu, Simon Laflam... Published: 07 January 2018
2018 AIAA Information Systems-AIAA Infotech @ Aerospace, doi: 10.2514/6.2018-0467
DOI See at publisher website
Article 10 Reads 0 Citations Recent Advances on SHM of Reinforced Concrete and Masonry Structures Enabled by Self-Sensing Structural Materials Filippo Ubertini, Antonella D'Alessandro, Austin Downey, Enr... Published: 14 November 2017
Proceedings, doi: 10.3390/ecsa-4-04889
DOI See at publisher website