Development and metrological characterization of cement-based elements with self-sensing capabilities for structural health monitoring purposes




structural health monitoring, piezoresistivity, self-sensing materials, resilience, metrological characterization


Mortar specimens containing conductive additions (i.e., biochar and recycled carbon fibres – both alone and together, and graphene nanoplatelets) were characterized from a metrological point of view. Their piezoresistive capability was evaluated, exploiting the 4-electrode Wenner’s method to measure electrical impedance in alternating current (AC); in this way, both material and electrode-material polarization issues were avoided. The selected mix-design was used to manufacture scaled concrete beams serving as demonstrators. Additionally, FEM-based models were realized for a preliminary analysis of the modal parameters that will be investigated through impact tests conducted after different loading tests, simulating potential seismic effects. The results show that the combined use of recycled carbon fibers and biochar provide the best performance in terms of piezoresistivity (with a sensitivity of 0.109 (µm/m)-1 vs 0.003 (µm/m)-1 of reference mortar). Conductive additions improve the Signal-to-Noise Ratio (SNR) and increase the material electrical conductivity, providing suitable tools to develop a distributed sensor network for Structural Health Monitoring (SHM). Such a monitoring system could be exploited to enhance the resilience of strategic structures and infrastructures towards natural hazards. A homogeneous distribution of conductive additions during casting is fundamental to enhance the measurement repeatability. In fact, both concrete intrinsic properties and curing effect (hydration phenomena, increasing electrical impedance) cause a high variability.

Author Biography

Gloria Cosoli, Università Politecnica delle Marche

G. Cosoli was born in Chiaravalle (AN) in 1989. She received the M.S. degree in electronic engineering (cum laude) from the Università Politecnica delle Marche (UNIVPM) in 2013 and the Ph.D. degree in mechanical engineering from the same university in 2017.
From 2016 to date, she has been a Postdoctoral Research Fellow with the Department of Industrial Engineering and Mathematical Sciences (DIISM) of UNIVPM. 






Research Papers