Rosario Ceravolo

Concrete has been one of the most common building materials used in construction in the world for many centuries. The manufacturing of concrete plays an important role in the generation of global warming emissions and waste and causes non-renewable resource depletion. This research assesses the environmental impacts of the use of supplementary cementitious materials (SCMs) and engineered nanomaterials (ENMs) (i.e., by-products) as partial replacement of ordinary Portland cement in concrete.

The performance of a monitoring system for civil buildings and infrastructures or mechanical systems depends mainly on the position of the deployed sensors. At the current state, this arrangement is chosen through optimal sensor placement (OSP) techniques that consider only the initial conditions of the structure. The effects of the potential damage are usually completely neglected during its design.

The interest in automatic modal parameter extraction techniques has increased significantly in recent years because of the rising demand for Continuous Structural Health Monitoring (CSHM) of civil structures and infrastructures. The wider use of CSHM is related to its capability for early damage detection and therefore to its usefulness for planning maintenance and strengthening interventions.

Effective diagnostic and monitoring systems are highly needed in the building and infrastructure sector, to provide a comprehensive assessment of the structural health state and improve the maintenance and restoration planning. Vibration-based techniques, and especially ambient vibration testing, have proved to be particularly suitable for both periodic and continuous monitoring of existing structures. As a general requirement, permanent systems must include a sensing network able to run a continuous surveillance and provide reliable analyses based on different information sources.

A reliable and predictive model of an existing structure entails the use of model updating techniques, which are usually performed on the basis of operational modal analysis campaigns. In this paper, a new model calibration strategy is proposed that adopts a multiphysics approach to exploit data collected by both static and dynamic monitoring systems. More specifically, mechanical and temperature data are assimilated into the model through a thermoelastic updating.

One of the main drawbacks of using entropy-based indicators for damage detection is known to be their sensitivity to the energy introduced into the system. Indeed, energy supply can lead to a more deterministic behavior of the structure and thus to a reduction of the entropy. As a solution to these issues, in this paper an indicator based on two measures of spectral entropy is proposed to assess the occurrence of damage in masonry buildings, even in the presence of an external unmeasured input (e.g. minor seismic event).

The theory of cointegration, usually employed in econometric studies, has proved very powerful in the context of Structural Health Monitoring (SHM), where it can be used to distinguish operational and environmental changes of dynamic features from those related to the evolution of damage. The different nature of the effects imposed by operational and environmental variations on structural response required here an extension of the theory of cointegration from the linear to the nonlinear field. For this purpose, a nonlinear multivariate regression has been developed.

Novel metamaterial concepts can be used to economically reduce flexural vibrations in coupled pipe-rack systems. Here, we model pipe on flexible supports as periodic systems and formulate dispersion relations using Floquet-Bloch theory which is verified by a finite element model. Owing to the flexibility of the coupled system, a narrow pass band is created in low frequency regime, in contrast to the case of pipe without any rack. Two types of vibration reduction mechanisms are investigated for pipe with different supports, i.e. simple and elastic support.

Recently, features and techniques from speech processing have started to gain increasing attention in the Structural Health Monitoring (SHM) community, in the context of vibration analysis. In particular, the Cepstral Coefficients (CCs) proved to be apt in discerning the response of a damaged structure with respect to a given undamaged baseline. Previous works relied on the Mel-Frequency Cepstral Coefficients (MFCCs).