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Filippo Ubertini   Professor  Other 
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Filippo Ubertini published an article in May 2018.
Research Keywords & Expertise
0 A
0 Carbon Nanotubes
0 Reinforced Concrete
0 Resistance
0 Sensors
0 Structural Health Monitoring
Top co-authors See all
Franco Cotana

66 shared publications

Anna Laura Pisello

63 shared publications

Fabio Orlandi

36 shared publications

Carmelo Gentile

34 shared publications

Claudio Tamagnini

29 shared publications

36
Publications
30
Reads
0
Downloads
134
Citations
Publication Record
Distribution of Articles published per year 
(2007 - 2018)
Total number of journals
published in
 
22
 
Publications See all
Article 0 Reads 0 Citations Effect of PCM on the Hydration Process of Cement-Based Mixtures: A Novel Thermo-Mechanical Investigation Claudia Fabiani, Antonella D’Alessandro, Filippo Ubertini, F... Published: 23 May 2018
Materials, doi: 10.3390/ma11060871
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The use of Phase Change Material (PCM) for improving building indoor thermal comfort and energy saving has been largely investigated in the literature in recent years, thus confirming PCM’s capability to reduce indoor thermal fluctuation in both summer and winter conditions, according to their melting temperature and operation boundaries. Further to that, the present paper aims at investigating an innovative use of PCM for absorbing heat released by cement during its curing process, which typically contributes to micro-cracking of massive concrete elements, therefore compromising their mechanical performance during their service life. The experiments carried out in this work showed how PCM, even in small quantities (i.e., up to 1% in weight of cement) plays a non-negligible benefit in reducing differential thermal increases between core and surface and therefore mechanical stresses originating from differential thermal expansion, as demonstrated by thermal monitoring of cement-based cubes. Both PCM types analyzed in the study (with melting temperatures at 18 and 25 ∘C) were properly dispersed in the mix and were shown to be able to reduce the internal temperature of the cement paste by several degrees, i.e., around 5 ∘C. Additionally, such small amount of PCM produced a reduction of the final density of the composite and an increase of the characteristic compressive strength with respect to the plain recipe.
Article 1 Read 0 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
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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.
Article 0 Reads 0 Citations Automated crack detection in conductive smart-concrete structures using a resistor mesh model Austin Downey, Antonella D’Alessandro, Filippo Ubertini, Sim... Published: 19 February 2018
Measurement Science and Technology, doi: 10.1088/1361-6501/aa9fb8
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Various nondestructive evaluation techniques are currently used to automatically detect and monitor cracks in concrete infrastructure. However, these methods often lack the scalability and cost-effectiveness over large geometries. A solution is the use of self-sensing carbon-doped cementitious materials. These self-sensing materials are capable of providing a measurable change in electrical output that can be related to their damage state. Previous work by the authors showed that a resistor mesh model could be used to track damage in structural components fabricated from electrically conductive concrete, where damage was located through the identification of high resistance value resistors in a resistor mesh model. In this work, an automated damage detection strategy that works through placing high value resistors into the previously developed resistor mesh model using a sequential Monte Carlo method is introduced. Here, high value resistors are used to mimic the internal condition of damaged cementitious specimens. The proposed automated damage detection method is experimentally validated using a $500 x 500 x 50 $ mm reinforced cement paste plate doped with multi-walled carbon nanotubes exposed to 100 identical impact tests. Results demonstrate that the proposed Monte Carlo method is capable of detecting and localizing the most prominent damage in a structure, demonstrating that automated damage detection in smart-concrete structures is a promising strategy for real-time structural health monitoring of civil infrastructure.
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Experimental analysis on slamming reduction in rectangular liquid tanks subjected to harmonic motion Nicola Cavalagli, Chiara Biscarini, Andrea L. Facci, Filippo... Published: 01 January 2018
AIP Conference Proceedings, doi: 10.1063/1.5044009
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This paper investigates the reduction of slamming effects related to liquid sloshing in moving tanks by using internal vertical perforated screens. The research is framed in the context of the evaluation of energy dissipation in Tuned Sloshing Dampers (TSD), generally applied in civil engineering for the structural vibration control of tall buildings. A deep understanding of the physical problem and the mechanisms generating and suppressing waves within the tank in relation to the dissipation energy which the device could be able to provide is much needed, yet not achieved in the literature. The paper presents some recent advances in this framework through an experimental campaign carried out on tanks with different dimensions subjected to harmonic motion.
Article 3 Reads 0 Citations Smart bricks for strain sensing and crack detection in masonry structures Austin Downey, Antonella D’Alessandro, Simon Laflamme, Filip... Published: 30 November 2017
Smart Materials and Structures, doi: 10.1088/1361-665x/aa98c2
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The paper proposes the novel concept of smart bricks as a durable sensing solution for structural health monitoring of masonry structures. The term smart bricks denotes piezoresistive clay bricks with suitable electronics capable of outputting measurable changes in their electrical properties under changes in their state of strain. This feature can be exploited to evaluate stress at critical locations inside a masonry wall and to detect changes in loading paths associated with structural damage, for instance following an earthquake. Results from an experimental campaign show that normal clay bricks, fabricated in the laboratory with embedded electrodes made of a special steel for resisting the high baking temperature, exhibit a quite linear and repeatable piezoresistive behavior. That is a change in electrical resistance proportional to a change in axial strain. In order to be able to exploit this feature for strain sensing, high-resolution electronics are used with a biphasic DC measurement approach to eliminate any resistance drift due to material polarization. Then, an enhanced nanocomposite smart brick is proposed, where titania is mixed with clay before baking, in order to enhance the brick's mechanical properties, improve its noise rejection, and increase its electrical conductivity. Titania was selected among other possible conductive nanofillers due to its resistance to high temperatures and its ability to improve the durability of construction materials while maintaining the aesthetic appearance of clay bricks. An application of smart bricks for crack detection in masonry walls is demonstrated by laboratory testing of a small-scale wall specimen under different loading conditions and controlled damage. Overall, it is demonstrated that a few strategically placed smart bricks enable monitoring of the state of strain within the wall and provide information that is capable of crack detection.
Article 0 Reads 1 Citation Experimental wind tunnel study of a smart sensing skin for condition evaluation of a wind turbine blade Austin Downey, Simon Laflamme, Filippo Ubertini Published: 30 October 2017
Smart Materials and Structures, doi: 10.1088/1361-665x/aa9349
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Condition evaluation of wind turbine blades is difficult due to their large size, complex geometry and lack of economic and scalable sensing technologies capable of detecting, localizing, and quantifying faults over a blade's global area. A solution is to deploy inexpensive large area electronics over strategic areas of the monitored component, analogous to sensing skin. The authors have previously proposed a large area electronic consisting of a soft elastomeric capacitor (SEC). The SEC is highly scalable due to its low cost and ease of fabrication, and can, therefore, be used for monitoring large-scale components. A single SEC is a strain sensor that measures the additive strain over a surface. Recently, its application in a hybrid dense sensor network (HDSN) configuration has been studied, where a network of SECs is augmented with a few off-the-shelf strain gauges to measure boundary conditions and decompose the additive strain to obtain unidirectional surface strain maps. These maps can be analyzed to detect, localize, and quantify faults. In this work, we study the performance of the proposed sensing skin at conducting condition evaluation of a wind turbine blade model in an operational environment. Damage in the form of changing boundary conditions and cuts in the monitored substrate are induced into the blade. An HDSN is deployed onto the interior surface of the substrate, and the blade excited in a wind tunnel. Results demonstrate the capability of the hybrid dense sensor network and associated algorithms to detect, localize, and quantify damage. These results show promise for the future deployment of fully integrated sensing skins deployed inside wind turbine blades for condition evaluation.